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Template Subsidy Application Form

The Subsidy Application Form template is used in the full proposal phase. It must be filled in completely and be accompanied by:

1. Full proposal – project plan (see Annex 4)2. Project budget (see Annex 5)3. Partner agreement (see Annex 6)

A. Project name and durationProject name: SALOMO – Situational Awareness for LOgistic Multimodal Operations in

container supply chains and networksCommencement date: 1-8-2011

End date: 31-7-2015

B. Project applicant and project leader Company / organization: TRAIL Research School

Contact person: Prof.dr.ir. A. Verbraeck

E-mail address: [email protected]

Authorized to sign:

Financial administrator: Felicita Viglietti

E-mail address: [email protected]

Applicant’s visiting address : TU Delft, TBM, Jaffalaan 5

Postal code: 2628 BX City: Delft

Postal address: TU Delft, TBM, Systeemkunde, Postbus 5015

Postal code: 2600 GA City: Delft

Project leaderCompany / organization: Trail Research School represented by

Delft University of TechnologyFaculty of Technology, Policy and ManagementDepartment of System Engineering

Contact person: Alexander Verbraeck

E-mail address: [email protected]. Partners in consortiumOrganization’s name Type of organization SME

TRAIL Research School

Knowledge institute No

Delft University of Technology, Faculty of Technology, Policy and Management

Knowledge institute No

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mailto:[email protected]

Open University, Center for Learning Sciences and Technologies

Knowledge Institute No

TBA Company No

In There Company Yes

Rotterdam World Gateway

Company No

APM Terminals Maasvlakte 2

Company No

Teamsupport Company Yes

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D. Signatures

By signing this form, I certify that all the required documents are attached and that I am familiar with Dinalog´s conditions and procedures.

Applicant’s organization: TRAIL / TU Delft / TBM

Authorized to sign: Position: City: Delft

Date: Signature:

Submit to Dinalog:

1.E-mail, all documents in PDF, but also original Word and Excel documents to [email protected];

2.Post, printed versions of all documents requested to Dinalog Management, Princehagelaan 13, 4813 DA Breda

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mailto:[email protected]

Table of Contents

Annex 4. Template Project Plan...............................................................................................5

Summary.........................................................................................................................5

A. Orientation and Project Goals.........................................................................................6

Motivation........................................................................................................................6

Relation to Dinalog´s innovation themes........................................................................7

Objectives and goals.......................................................................................................8

Research questions......................................................................................................12

Expected results............................................................................................................13

Orientation.....................................................................................................................15

References....................................................................................................................15

B. Activities and Work Packages.......................................................................................17

Planning........................................................................................................................24

C. Consortium and Project Organization...........................................................................24

Research Team.............................................................................................................24

Project organization......................................................................................................25

D. Evaluation and Monitoring.............................................................................................26

Evaluation......................................................................................................................26

E. Valorization and Implementation Strategy....................................................................27

Valorization and knowledge dissemination...................................................................27

Implementation..............................................................................................................27

Annex 4A. CVs of Researchers in the SALOMO project........................................................28

TRAIL / TU Delft Researchers.............................................................................................28

Open University Researchers.............................................................................................32

University of Maryland Researchers...................................................................................35

Annex 4B. Company overview and CVs of the key company personnel................................38

InThere................................................................................................................................38

TBA......................................................................................................................................39

TeamSupport.......................................................................................................................42

Annex 4C. Letters of Companies Interested to Participate in the User Group.......................43

Annex 4D. Example prototype of a container terminal berth planning tool.............................44

Annex 4E. Training games developed earlier at TU Delft......................................................46

Annex 4F. Example Automatically Generated 3D-model of a Container Terminal................49

Annex 4G. TBA’s CONTROLS for testing operations in dynamic situations..........................50

Annex 4H. Background on learning theory from Open University CELSTEC........................52

Annex 4I. Overall budget breakdown......................................................................................55

Annex 4J. Overall project plan................................................................................................57

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Annex 4. Template Project Plan SummaryModern supply chains become longer and more complex due to increasing globalization, labor offshoring, and growth. Mainports such as the Port of Rotterdam play an important role as a gateway to Europe and beyond especially given increased competition between the ports in the Le Havre – Hamburg range. Longer, complex supply chains are much more vulnerable to disturbances, which resonate throughout the network and make planning more difficult. Robust and flexible hubs which are efficiently connected to the hinterland are therefore crucial for The Netherlands. The focus of the SALOMO project is to address challenges of uncertainty, variation, increasing demands for performance, and an improved degree of quality. The SALOMO project aims to empower the terminals in the Port of Rotterdam and their hinterland connections by facilitating better decisions and planning through increased situational awareness as well as better trained staff able to deal with dynamic circumstances. We further expect a significant multiplier effect from improvement in hubs in Rotterdam, consecutively leading to economic growth in the larger Rotterdam area, but also along the hinterland connections.

In more closed supply chains, collaborative planning and forecasting tools have already shown to be beneficial. SALOMO will bring key insights about real-time and collaborative supply chain management to practice. For this purpose, novel visual, real-time decision support tools need to be combined with training to empower planners to collaborate more effectively. These training tools will also be available for general use in education. The project will start with developing and testing the decision support tools and training tools at container terminals in the Port of Rotterdam. Subsequently, the tools will be tested at other types of organizations in the supply chain to generalize their use, applicability and dissemination.

The project focuses on eight innovations (uncertainty handling, real-time planning, cross-partner collaboration, information visualization, intelligent decision support, probabilistic forecasting, mobile data input and output, and virtual reality training) to be studied in the container terminals. The resulting multiple purposes tools (information provision, planning, reacting on disturbances), will be tested in the consortium and a User Committee involving the wider supply chain community. Around the tools we will develop micro-games that will be studied for effectiveness and used in the consortium and in educational settings (STC Rotterdam, TU Delft, Dinalog).

The innovations are expected to improve the hinterland transportation chain by providing more efficient and safer operational processes in terminals, better synchronization between partners, a higher load factor of transportation equipment, a cheaper and environmentally friendly modal split, and a better use of scarce resources and capacity. Prior experiences of partners in the SALOMO project clearly confirm that by improving decision-making capabilities of planners can benefit terminal performance with at least 5%, and potentially even in the range of 10-20%.

The Dutch supply chain hubs will be first adopters of the innovations, giving them some competitive advantage. Further, the (training) tools provide an interesting export product, as is confirmed by logistic companies abroad (e.g. DP World in Dubai, Ports of Felixstowe, Port of Valencia, and Terminal Link, the terminal organization of CMA-CGM).

The practical results of the project will be shared with the project partners and with the SALOMO User Committee that concerns the wider supply chain community, and tested in a number of cases that demonstrate the practical applicability. The academic results will be shared with the international scientific community through publications in high-end journals, presentations at conferences, and demonstrations at workshops. A number of international supply chain specialists have agreed to participate pro bono in the project and help anchor the results in the most recent supply chain tradition. The wider audience will be informed through a number of non-specialist publications and web presence.

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A. Orientation and Project Goals

MotivationSupply chain management has changed considerably over the past ten years. Supply chain management departed from traditional logistics elements such as sourcing, inbound logistics, inventory management, manufacturing, outbound logistics, and after-market service (Mabert & Venkataramanan, 1998; Bowersox, Closs & Cooper, 2002; Simchi-Levi et al., 2003). As Poirer (1999) and Poirer & Bauer (2000) show, the availability of information and the use of the Internet becomes a dominating factor in supply chain management and forces supply chain partners to link their systems and exchange information with others. Boyson, Harrington & Corsi (2004) extend on this by demonstrating that real-time information is the driver of the 21st century supply chains. Gattorna (2006) argues that the dominant worldview of companies competing with companies has now definitely changed: it is now supply chains competing with supply chains, in other words, supply chains are the business. With the increasing complexity and dominance of supply chains, they become harder to plan, and more vulnerable for disruptions (Harrington, Boyson & Corsi, 2011). Craighead, Blackhurst, Rungtusanatham & Handfield (2007) provide insight into the severity of supply chain disruptions and estimate the effect to be as large as 10% of market capitalization. Wilson (2007) demonstrates that transporttation disruptions have long-lasting ripple effects on the entire supply chain. Designing flexible or adaptive supply chains (Gattorna, 2006) and collaborative intermodal hub networks (Groothedde, Ruijgrok & Tavasszy, 2005) can help to handle the large volumes of freight in a world dominated by globalization, smaller shipment sizes, high frequencies, and last-minute changes. Still, adoption of new technology by supply chain partners is low (Patterson, Grimm & Corsi, 2003), and planning and collaborating across organizational boundaries remains an issue. Observations of the research-ers in this project at marine container terminals, inland container terminals, and other major transportation hubs reveal ineffective processes, waiting times, unnecessary handling, unsafe situations, transport routes that are longer than necessary, and a use of non-optimal modalities.

Despite increasing availability of information throughout the supply chains, critical hubs in our infrastructure struggle to efficiently plan an optimal use of resources and an efficient and flexible throughput of cargo. For example, container terminals are the most important seaside-hinterland hub in containerized supply chains. Higher volumes, larger transportation sizes, and dynamics in the sea and hinterland connections increase the difficulty of planning and effective decision making. In this proposal we therefore aim to empower planners and decision makers at critical hubs in the supply chain with enhanced situational awareness and more intelligent planning tools, that help them to collaborate with supply chain partners in creating a more flexible and sustainable supply chain. Senter Novem (2007) concluded in a study on logistics and supply chains that the innovation of the Dutch transportation sector is lagging behind and that collaboration between supply chain partners and the use of innovative ICT tools is the way forward to become competitive again.

To motivate the focus of this proposal, we identified three critical challenges of planning and decision making in supply chain hubs that will be addressed in this proposal.

First, there is a lack of skills and tools to establish a shared situational awareness that is critical for coordinated joint decisions by stakeholders, to improve efficiency and leanness in the transportation supply chain. Due to this lack of shared situational awareness, decision makers often work from an individual perspective, which leads to propagation of uncertainty throughout the supply chain, making it less agile, flexible and sustainable. Planners miss the tools and skills to effectively communicate and attune aspects of situational awareness and uncertainty.

A second critical challenge is a lack of insight in implications of decisions, and in the range of alternative outcomes of planning decisions due to the vast amount if dynamic and uncertain information involved. This is strengthened by the inability of (automated) decision support systems to display and visualize this real-time and ever-changing information in an intuitive way. This lack of situational awareness leaves decision makers ‘disconnected’ from the actual system state and offers them ineffective or disruptive proposals for changes in the planning cycle.

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Finally, there is a lack of a safe and effective training environment for planners and decision makers in the supply chain to practice and experiment in dealing with these uncertainties and complexities in a collaborative and holistic way. To innovate and experiment in a fully operational supply chain can have vast negative consequences, which form a barrier to try out new approaches and means of collaboration, while such a ‘playground’ is critical for innovation.

These challenges stress the importance of shared situational awareness, and insight in implications of decisions throughout the supply chain to create a leaner container supply chain. We therefore focus on empowering planners and decision makers in the container supply chain at all levels to align the tools that they have in a holistic manner to improve overall supply chain performance. The project differs from earlier approaches in that it tries to address the ‘decision making under uncertainty’ issue, through empowerment and training of decision makers, rather than a more ‘disconnected’ optimization of container flows or information flows. In this way, SALOMO offers a bridge between the current situation and a future scenario in which information systems are more integrated and connected.

Relation to Dinalog´s innovation themes

SALOMO links to the theme “Main Ports / Transport Hubs in Control”. The performance and reliability of container supply chain networks is dependent on the performance and reliability of its major hubs. Container terminals in the mainport Rotterdam, and other critical hubs in our logistic cargo infrastructure with their high volume, linkage to various modalities and high level of automation are complex to manage, and complex to align to the previous steps and next steps in the transportation chain.

Where the Dinalog ULTIMATE proposal studies the effect of making changes in the structure of the supply chain through the extended gate concept, the SALOMO proposal tries to put the transport hubs truly back in control, but not from a top-down perspective. Transport hubs should function instead as a critical node in networked bottom-up models of the supply chain coordination. From we perspective we aim to enable the transport hubs to better deal with uncertainty, to make use of innovative planning, collaboration, decision support, and forecasting tools, to apply mobile tools to gather data and novel ways to visualize information, in logical, geographical, or 3D spaces. This aligns nicely with the R&D innovations from the Commissie Van Laarhoven report (2008, p.17), where focus is put on:

Advanced Planning and Scheduling (addressed in topics ‘planning tools’ and ‘uncertainty handling’);

Real-Time Monitoring (addressed in topics ‘mobile data collection’ and ‘information visualization’);

Sense & Response Systems (addressed in topics ‘forecasting tools’ and intelligent decision support’).

The proposal also links to the themes from the Commissie Van Laarhoven report (2008) on p.28, where attention is asked for:

Inter-organizational Systems for Information Exchange (addressed in topic ‘collaboration’);

Logistic Concepts for Network Planning (addressed in topic ‘planning tools’, combined with the suite of other tools);

Dynamic Real-time Planning (addressed in topics ‘planning tools’ and ‘intelligent decision support’).

New planning tools are of the utmost importance because shared situational awareness and intelligent tools that help dealing with uncertainties will enable staff to use the automation at the terminal better, and to focus on exceptions and deviations. It will allow staff to minimize effects of disturbances on the container supply chain, and empower them to plan a more optimal use of resources.

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Training for using these new planning tools will make employees aware of the impact of the terminal performance on the entire container supply chain (training and the use of human capital is also addressed by the Commissie Van Laarhoven report in chapter 7). The Dinalog initiative aims to increase the number of people employed in the high-value-added part of logistics. The new-generation of highly automated terminals needs educated highly skilled staff, exactly the type of employees that Dinalog targets. The training and planning tools that we aim to develop in the SALOMO project can be used to improve education in logistic planning and supply chain management.

Finally, the Commissie Van Laarhoven points out that there is a gap between education and practice in the field of logistics/supply chain management. Improved training tools will bring Van Laarhoven’s vision of flexible supply chain professionals that can work in various companies, one step closer.

Objectives and goals

The objective of the SALOMO proposal is to develop 8 tools to help address 8 types of issues in the supply chain. Each of the tools will be developed in close collaboration with the container terminal partners in the project, and based on most recent academic insights of the partners. The tools will subsequently be tested in other major hubs from partners in the SALOMO User Group. In parallel, training tools will be developed and tested in the form of Web-based micro-games, which place the users in a realistically visualized situation in which the training takes place. The training tools and micro-games will be tested for effectiveness as well.

From an overarching perspective, the three major objectives are:

Objective 1: to develop and enhance a theoretical model to understand situational awareness and collaboration in supply chain planning and decision making. Each of the tools and each of the companies where we test the concepts will provide us with a set of data points that we can use to further enhance the theoretical model. Because we test the model with different types of supply chain hubs, we strive for a broad validity of the theory, so it can be used broadly by the supply chain community.

Objective 2: to develop and test a toolbox for planning and decision making with intelligent tools that enable planners and decision makers to create shared situational awareness and support collaboration for a more effective use of resources to improve flexibility and sustainability of the transportation supply chain. The tools should be able to deal with incomplete information, uncertainty, disturbances, and real-time data provision.

Objective 3: to develop and evaluate a training suite that will teach planners and decision makers to make their planning based on a more holistic shared situational awareness and in a more collaborative fashion. The training environment will offer an ‘overlay’ simulation on top of existing systems, but independent of terminal operating systems. The simulation will use real data but will not affect real systems, and instead offer a game and training environment that allows for safe practicing, experimenting, innovation and learning. This will be supported via a kind of mixed reality simulation, which uses real world data but allows training sessions based on a simulation model. The training environment will use embedded technology such as mobile devices or ambient display technologies. The training tools should enable supply chain hubs to improve the skills of their personnel. In addition the tools should be ready to use for training of the next generation of supply chain professionals in both practical education (e.g., STC), and academic education (e.g., universities).

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The picture below shows the relationship between the three objectives, and their relationship with the application of the tools in industry and the application of the training instruments in industry and wider education.

Applicationwith Partners

Applicationin User Group

Trainingwith Partners

Trainingin Education

Objective 2: Develop and TestDSS Methods and Tools

Objective 3: Develop and TestTraining Tools and Microgames

Objective 1: Develop Theory

Dissemination to the Wider Community(Academic and Industry)

The ultimate objective of the SALOMO project is to improve the effectiveness of the critical hubs in the transportation supply chain (both by improving the internal effectiveness and by better alignment with supply chain partners) by at least 5%.

The breakthroughs are realized through the eight research areas. Three research areas are aimed externally to improve planning and scheduling between partners (areas A, B, and C). Three research areas are aimed internally at a Supply Chain hub to improve the internal process effectiveness and provide the essential information necessary to better collaborate with other supply chain partners (areas F, G, and H). Two areas look more generally into tools that can visualize dynamic information and help with better planning in general (areas D and E). The figure below depicts the relationship between the research areas.

B.ProbabilisticForecasting

C.Cross-partnerCollaboration

Support

A.Uncertainty

Monitoring &Disruption Handling

E.IntelligentDecisionSupport

D.InformationVisualization

F.Real-timePlanning

H.3D ProcessAwareness

G.Mobile Data

Input / Output

Longer-term information and decisions (hours – days) Shorter-term information and decisions (minutes – hours)

Tools aimed externally (between SC hubs) Tools aimed internally (within SC hub)

Core toolsLinkage between

Internal andExternal tools

A. Uncertainty monitoring and disruptions handlingVolatility in the supply chain is a common theme nowadays (Harrington, Boyson and Corsi, 2011). At transportation hubs, where many supply chains converge in the complicated global network, the effects of uncertainty and disruptions are observed most, and have a ripple effect through the rest of the supply chain. Methods and tools to dampen the effects of uncertainty and disruptions are in high demand. Unfortunately most planning and control tools in terminals deal with point estimates, can only plan using available data, and invoke major planning changes when disruptions occur. The ‘uncertainty monitoring and disruptions handling’ methods and tools should enable planners in supply chain hubs to monitor information uncertainty, visualize it, and

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create a more robust plan based on historically observed patterns of system behavior. The effectiveness of these plans to deal with disruptions will be researched. The goal is to create planning tools that cause minimal disruptions in the ‘downstream’ supply chain when disturbances occur in the ‘upstream’ supply chain.

B. Probabilistic forecastingRobust scheduling in complex transportation networks is a major issue. On terminals, SALOMO partner TBA has already researched the topic of dispatching AGV’s under uncertain information; they found that the Hungarian algorithm (assuming deterministic due times, driving times, and times jobs are ready) is worse than (simple) heuristic rules. There is clearly room for improvement. The same holds for hinterland transportation scheduling under continuously changing circumstances with disturbances. The CONTROLS software that TBA has developed (see Annex 4G) to investigate various solutions can probably be applied to truck dispatching, train scheduling, and barge scheduling as well.

Moving from deterministic forecasts (point estimates) in our planning to stochastic forecasts (range estimates) will help to address many issues in transportation planning. Many of the tools that planners in supply chains use, however, cannot deal with uncertainty. Bringing uncertainty into the tools that we use will improve planners’ ability in hubs to create better schedules will help the overall supply chain to become more robust.

C. Cross-partner collaborationIn most supply chains, uncertainty and/or lack of current information causes organizations and their trading partners to accumulate inventory as insurance against potential service or fulfillment failures that cause long storage times in major transportation hubs as a result (Boyson et al., 2004). One way to minimize such inventory buildups is to reduce uncertainty by improving the flow of information within an organization, and between an organization and its extended enterprise supply chain partners. This increased sharing of information is often referred to as Collaborative Planning, Forecasting, and Replenishment or CPFR for short. Boyson et al. (2004) discusses the CPFR movement in greater detail, and demonstrates that portaled environments in which the different parties in the supply chain share information adds tremendous value to the supply chain. CPFR is about sharing information (about demand forecasts, component availability and inventory, manufacturing schedules, and so on) in real time and providing an environment in which dialogue and discussions can occur with regard to the shared information. Facilitating a dialogue in which information is exchanged in an effective way, but key commercial information is not shared with competitors, is one of the challenges of the SALOMO project. Earlier research in the APPROACH-2 project from Transumo will be used to help overcome this challenge (Douma, 2008). The software from the company TeamSupport will be used to orchestrate the interactions between the supply chain partners, both ‘upstream’ and ‘downstream’ from the transportation hub, in a structured manner.

D. Information visualizationVisualizing information gets separate attention in the SALOMO project, because it is core to create shared understanding by the users of the tools and the users of the training instruments. SALOMO will look at data integration, combining information from various sources (e.g., maintenance system, vessel tracking system, resource scheduling system), and presentation of complex and rapidly changing data to the participants. Examples of innovative data presentation are shown in Annex 4H, in the sections from partner Open University about awareness and augmented reality & human perception.

E. Intelligent decision supportFor current decision support in supply chains, lots of data is available from many different automated systems in each of the supply chain partner’s organizations. These tools include (Boyson et al, 2004) enterprise resource planning (ERP) systems, supply chain execution (SCE) solutions – i.e., warehouse management (WMS), labor management (LMS), transportation management (TMS) and international trade logistics (ITL) applications. Furthermore, real-time traffic monitoring, weather information, is available in combination with GIS data (maps). Right

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now, transportation hubs have a very difficult time to integrate all different types of data. First examples to integrate these types of data have already shown nice results. An example is the berth planner and yard look-ahead project that TBA and TU Delft have executed (see Annex 4D). Based on this example, the project expects to develop a number of key decision support modules for transportation hubs. These modules are expected to be quite different from earlier decision support systems because of the availability of real-time information, collaboration with supply chain partners, and (mobile) data collection in the supply chain nodes.

F. Real-time planningBeing able to use real-time information is the driver for better supply chain management (Boyson, Harrington & Corsi, 2004). The theory of Dynamic Data Driven Application Systems (DDDAS) paradigm can be used to incorporate real-time data into (planning) models (Celik at al., 2010). Simulation will be an important instrument to utilize the DDDAS paradigm and make it a component in real-time planning. The planning tools feed directly on newly available and dynamically changing data, and adapts the model of the supply chain continuously to use it as an input for the planning algorithms.

Real-time planning consists of three steps. First, real-time sensor data has to be gathered at various spots in the supply chain, including at the hub itself. After a technical evaluation, it might be possible to immediately determine the nature of the problem and possible solutions. If the sensor-data evaluation indicates a more critical problem, communication capabilities with supply chain partners can help identify and locate key decision makers, enabling real-time assembly of a decision team to deal with the critical event, in other words, provide shared situational awareness to the decision makers. This streamlined process contrasts sharply with the current environment in which the response to deviations and events is much slower and less efficient. There are delays in identifying the deviations or events, developing alternative coping strategies, identifying and locating key decision makers, and facilitating a meeting for decision-making. Valuable time is lost in responding, and as a result, the supply chain and the hub become less efficient and less competitive. Currently, decisions are often reached without access to shared data. As a result, the actions taken may disrupt the supply chain when alternative, non-disruptive actions would have more effectively addressed the problem.

In order to reach real-time planning solutions for critical hubs in transportation supply chains, DDDAS, simulation, and sensor data (area G) will be combined in for real-time planning.

G. Mobile data input and outputSuccess of the tools in SALOMO heavily depends on the availability of data and the empowerment of the workers in operations, as was mentioned before. Right now, outdoor staff often has no information about what is being moved, where is goes, how much slack there is in the current activity, etc. Augmented reality (see Annex 4H) can be a way to provide innovative data output for workers in operations, leading to much more effective operations than with audio devices that are hard in conveying more ‘visual’ messages or complex information, or handheld that do not work with gloves and in harsh environments. We plan to extend our tools to provide this information by combining GPS, mobile devices and central information to project this as augment reality on vehicles, containers, etc. Also think of customs that can ‘see’ the container load, it origin when it drives through the gate, without looking at computer screens. When devices and handhelds have GPS on-board, or when they are tagged with (RFID) tags, real-time and detailed information can be made available to planner and decision makers in an operational context.

Environmental and object bound sensors can provide relevant data about the spatial distribution of goods in a container terminal. These sensors can effectively contribute to location and object awareness when they are linked to real-time data. These sensors can be used to track containers as well as staff and vehicles on the site. This information can be get used to increase the spatial awareness of outdoor workers through personalized and contextualized information access using augmented reality techniques on mobile devices. This enables different actors to access relevant real-time contextual information for example by pointing on one container.

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Mobile data input plays an important role for extending contextual information that is relevant for awareness processes (de Jong, Specht, & Koper, 2008). Pre-defined sampling triggers help end-users to develop a better spatial awareness and increases the quality of data that is available for planning algorithms.

H. 3D process awareness for safer workTransportation hubs have indicated that one of the key areas where they want to improve is process awareness, where employees in operations are much better aware of the 3D environ-ment around them to a) be able to better adjust their activities to the changing environment around them, and b) be able to work in a more safe manner. Hubs with movements of heavy equipment and heavy loads are still unsafe and could benefit from a safer working environment. Examples are practicing procedures to salvage AGV’s in a fully automated areas, training in awareness of where it’s safe, and where it’s not. Now people stand in a large area without line markings, and with many vehicles driving around them without sensors. Here also augmented reality, but also training of the operational staff will improve safety and as such efficiency. The 3D modules that will be developed for area H will be aligned to the work on mobile data input and output (area G), and visualization (D). In order to function in a real hub, real-time data has to be available to feed the available information. Still, activity H is put early in the project because the container terminal partners see an immediate differentiator (commercial, safety) in applying the tools developed for area H.

Research questionsThe six major research questions addressed in SALOMO are therefore:

1. What types of awareness and situated information filtering are required to establish SSA at a level that enables holistic collaboration in decision making and planning?

Here we will develop an SSA framework of the most important components, resources, processes and decision intelligence to make adequate decisions.

2. What are the incentives and barriers for effective collaboration in the supply chain?

Based on these questions we will develop a theoretical model of collaboration and social information sharing in the terminals, this will lead to a clear incentive and collaboration strategy in the training system that can be extended to real world collaboration scenarios.

3. How can we support shared situational awareness for holistic planning?

This question will be the basis for the suite of innovative tools for holistic planning and decision making. Beside situational awareness also holistic approaches are mostly important for understanding and motivating cooperation and relevance of the personal contribution in a complex system.

4. How can we improve collaboration among various planners and decision makers at different places in the container supply chain by establishing shared situational awareness, using modern techniques for visualization, interaction, data integration, gaming and simulation?

This question will be the basis for the development of the training suite that can be used for education and professional training.

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5. How can we improve data collection and local situational awareness in operations within a supply chain hub?

This question looks how the basis for collecting the necessary data in operations can be improved, and how data can be made available to employees in operations to better, safer, and faster perform their jobs.

6. How can we best train operators, planners, and future supply chain professionals in capitalizing on improved shared situational awareness, and what is the added value of visualization, interaction, data integration, gaming, and simulation in this type of training?

This question will be answered by testing the training suite in in-company training (terminal partners), professional training (STC), and university education (TU Delft, U Maryland).

Expected results The main deliverables of SALOMO are: To provide a theoretical model and an associated library of mechanisms that describe

effective planning and decision making to create understanding of the different strategic perspectives that need to be integrated to create a holistic system perspective, and shared situational awareness as a basis for more effective and lean planning. The mechanisms will be captured as design patterns that will constitute a library of design principles. Throughout the SALOMO project the initial model and library will be improved and extended.

To provide a suite of innovative intelligent planning and decision tools and techniques that can deal with uncertain, incomplete, and rapidly changing information. These tools and techniques should link to existing information systems used in the container supply chain, offer forecasting and give planning suggestions, and give insight in implications of planning and decision making. The techniques will be developed and tested in the field, the tools will be developed as prototypes. A development and learning cycle will be used in which the model and principles are used to (re)design the tools and techniques, and experiences with the tools and techniques are used to further enhance and improve the model and the library of mechanisms.

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To provide innovative and adaptable training environment (using serious gaming and the model and planning tools describe above) to train planners and decision makers in light of four learning goals: a) deal with uncertain, incomplete, and rapidly changing information, b) use situational awareness in aligning with horizontal and vertical partners enabling better decision making, c) repeatedly practice scenarios and after action reviews to be ready for real decision making, d) develop and adopt new ways of multidisciplinary collaboration, which stimulates innovation and intensified collaboration. The training and gaming environment will be based on a simulation of the dynamic processes in the supply chain, and will have a 3d virtual world interface. The training environment should offer a safe environment for training and a realistic environment for experiments and innovation.

In the highly competitive industry of transport and logistics with small margins, hubs that excel in efficiency and reliability have a competitive advantage. Human factors are still critical for innovation and competitive advantage. With the planning tools, Rotterdam terminal operators will increase their flexibility, efficiency and sustainability, and therewith develop a competitive advantage. As competition is fought on various aspects – service levels, hinterland connections, safety – any improvement matters. We expect to be able to increase overall competitiveness by at least 5%, as such substantially impacting the market position. Due to the consequential business, container handling generates in the hinterland, we expect that the impact on the Dutch economy could easily be 50 – 100 times more than the project budget.

The training tools, simulation model and environment, will originally be developed for container terminals. In the final phase of the research, we will work on a generalization and further dissemination of these training tools. For this purpose we will generalize the tool set, distill scenarios that can be used for education to develop a new generation of supply chain professionals that possess a more flexible set of skills, tools and techniques to support effective supply chain management. Furthermore, we will select several prototypes of tools to implement in different supply chain hubs such as advanced berth planning tools, yard look ahead tools, pre-operational simulation tools, mobile augmented reality tools, and virtual reality training tools. These disseminations will be executed in the context of master thesis projects in various logistic supply chain hubs such as KLM Cargo, DFDS Seaways (Norfolkline), Ahold, and many others. We have already engaged with a number of organizations to see if they are interested to become part of the User Committee, and we already received many positive replies. This training environment can furthermore be used to develop trainings and training tools that can be sold to a variety of hubs and nodes in supply chains in the Netherlands and abroad.

Relation to government policyThe training suite we envision supports the ambitions of the Ministry of Social Affairs and the Ministry of Economic Affairs, to strengthen the knowledge-driven economy, to become the supply chain “brainport” of Europe, and to ensure employability of well-trained professionals. Our project therefore builds on the report of the Commissie Van Laarhoven and aligns with Dinalog’s ambition to play a leading role in education and training in the logistics and transportation field.

The Ministry of Transport’s policy on sea ports aims at increased capacity of the throughput, while becoming more sustainable; a higher volume with the same (or even lower) footprint. This project provides a way to realize this vision with new tools for providing intelligent SSA to enable better use of transport capacity.

SALOMO aligns well with the long-term vision of the Port of Rotterdam (June 2009), to solve capacity problems and improve access to the terminals with multi-modal transportation.

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Orientation SALOMO will make use of the latest insights from innovative theories about planning under uncertainty, artificial intelligence, SSA, shared understanding, collaborative planning, forecasting, and serious gaming. While serious gaming and real time simulations have been used in logistic planning, their combination is innovative, and their combination with intelligent forecasting is highly innovative. The tools will further provide an overlay system, and are therefore platform independent, and thus more flexibly deployable. The SALOMO proposal is complementary to the work done in ULTIMATE as it focuses on terminal (hub) operations instead of the broad context of hinterland networks. We expect that the new designs of hinterland network services such as produced in ULTIMATE will create new requirements for terminal operations in terms of spatial layout, handling priority, pricing etcetera. SALOMO will link up to these results to and assist the terminals to satisfy these new requirements.

SALOMO will balance scientific rigor and societal relevance. The tool suite will be developed in close interaction with several container terminals to ensure international applicability and relevance. Extensive scientific evaluation of the tool suite and underlying theory in the field will guard innovativeness and scientific rigor. The development of new theories on creating SSA in a dynamic environment can be applied outside the container supply chain. Furthermore, experience will be gained in applying uncertainty handling, real-time planning, cross-partner collaboration, information visualization, intelligent decision support, probabilistic forecasting, mobile data input and output, and virtual reality training in the logistics domain.

References

Bowersox, D.J., D.J. Closs and M.B. Cooper. Supply Chain Logistics Management. Boston, MA: McGraw-Hill, 2002

Boyson, S., L.H. Harrington and T.M. Corsi. In Real Time: Managing the New Supply Chain. Westport, CT: Praeger Publishers, 2004

Celik, N., S. Lee, K. Vasudevan and Y.-J. Son, “DDDAS-based multifidelity simulation framework for supply chain systems”. IIE Transactions. 42(5), 2010, 325 - 341

Commissie Van Laarhoven. Logistiek en Supply Chains: Innovatieprogramma. 2008Craighead, C.W., J. Blackhurst, M.J. Rungtusanatham, and R.B. Handfield. “The Severity of

Supply Chain Disruptions: Design Characteristics and Mitigation Capabilities”. Decision Sciences 38(1), 2007, 131-156

De Jong, T., Specht, M., & Koper, R. Contextualised Media for Learning. Journal of Educational Technology & Society, 11(2), 2008, 41-53.

Douma, A. Aligning the operations of barges and terminals through distributed planning. PhD Thesis, University of Twente, 2008

Gattorna, J. Living Supply Chains. How to Mobilize the Enterprise around what your Customers Want. London, UK: Pearson Education / Prentice-Hall, 2006

Groothedde, B., C. Ruijgrok and L. Tavasszy, “Towards collaborative, intermodal hub networks. A case study in the fast moving consumer goods market”. Transportation Research Part E 41, 2005, 567-583

Harrington, L.H., S. Boyson and T.M. Corsi. X-SCM. The New Science of X-treme Supply Chain Management. New York, NY: Routeledge / Taylor & Francis, 2011

Hevner, A., S. March, et al. Design Science Research in Information Systems. Management Information Systems Quarterly 28(1): 2004, 75-105.

Mabert, V.A. and M.A. Venkataramanan. “Special Research Focus on Supply Chain Linkages: Challenges for Design and Management in the 21st Century”. Decision Sciences 28(3), 1998, 537-552

Patterson, K.A., C.M. Grimm and T.M. Corsi, “Adopting new technologies for supply chain management”. Transportation Research Part E 39, 2003, 95-121

Poirer, C.C. Advanced Supply Chain Management. San Francisco, CA: Berrett-Koehler Publishing, 1999

Poirer, C.C. and M.J. Bauer. E-Supply Chain. San Francisco, CA: Berrett-Koehler Publishing, 2000

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SenterNovem. Innovation Intelligence - verkenning Logistiek en Supply Chains. Report DII0786071. SenterNovem, October 2007

Simchi-Levi, D., P. Kaminsky and E. Simchi-Levi. Designing & Managing the Supply Chain, 2ed. Boston, MA: McGraw-Hill, 2003

Wilson, M.C. “The impact of transportation disruptions on supply chain performance”. Transportation Research Part E 43, 2007, 295-320

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B. Activities and Work Packages

In the Salomo project we intend to work in an iterative cycle to develop the model, tools and training environment. This means that an initial rudimentary model of shared situational awareness will be iteratively improved and extended over the period of the project. Parallel to this, prototypes of tools and games will be developed and tested in both the container terminal context in which they will be developed and in other supply chain hubs. Figure 1 shows the overall development path of the project. Note that this is not intended as a linear path, but rather as an iterative cycle of model and principle development, prototype development learning to improve the model and principle library.

WP0. Project M

anagement

WP1.1. General SSA Theory Development

A. Uncertainty Monitoring

B. Probabilistic Forecasting

C. Cross-Partner Collaboration

D. Information Visualization

E. Intelligent Decision Support

F. Real-time Planning

G. Mobile Data Input / Output

H. 3D Process Awareness

WP1.2. SSA Design Patterns

WP1.3. SSA Publications

WP2.1. SSA Tool Architecture

WP2.2 SSA Tools Lessons Learned









WP1. SSA Theory

WP2. SSA Tools

WP3.1. SSA Tool Evaluation

WP3.2 SSA Tool Evaluation Lessons Learned









WP3. Evaluation

WP6. Dissem

ination

WP4.1. M.Sc. Project Setup for User Group (2 M.Sc. Students per application area)

WP4.2 SSA User Group Evaluation Lessons Learned









WP3. User Group

WP5.1. SSA Training Tool Architecture and Evaluation Setup

WP5.2 SSA Training Tool Evaluation Lessons Learned, Availability to Educational Institutes









WP3. User Group

Work Package 0. Project Management

0.1 Management0.2 Finance0.3 Establishing User Group

WP0Project Management 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12


YEAR 1 YEAR 2 YEAR 3 YEAR 4

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WP0 TRAIL TUD-SK TUD-TLO (MSc) OU (UMD) TBA InThere TS RWG APM (UG) TOTAL PARTNER

Project Management 490 340 0 0 0 0 180 0 0 0 0 40 1050 10100.1 Management 140 320 160 620 6200.2 Finance 330 330 3300.3 Establishing User Group 20 20 20 40 100 60

In this work package we will organize the project. TU Delft and TBA will jointly perform the coordinating tasks in the project, where TU Delft will focus on the scientific quality and TBA will focus on the utility of the deliverables for the industry partners. Trail will facilitate the project management, as is further explained in the organization section below.

Milestones are the establishment of the SALOMO User community and the financial and progress reports as required by Dinalog.

Work Package 1. Shared Situational Awareness Theory

1.1. General SSA Theory1.A Uncertainty Monitoring1.B. Probabilistic Forecasting1.C. Cross-Partner Collaboration1.D. Information Visualization1.E. Intelligent Decision Support1.F. Real-time Planning1.G. Mobile Data Input/Output1.H. 3D Process Awareness1.2. Capture design patterns1.3. Generalization and publishing

The theoretical work in activities 1.A till 1.H is aimed at the SSA theory that relates to the topic addressed, and will help to develop the tools in the subsequent work packages based on a rigorous study of the available knowledge. As was mentioned before, a lot of theory already exists for each of the topics, but it is not yet applied in the transportation supply chain.

WP1SSA Theory Development 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12




SSA Theory Development 0 1760 280 0 920 640 400 210 210 320 320 0 5060 44201.1. General SSA Theory 400 200 80 20 10 10 720 6401.A Uncertainty Monitoring 160 160 20 20 40 40 440 2801.B. Probabilistic Forecasting 120 20 20 40 40 240 2401.C. Cross-Partner Collaboration 160 40 40 40 40 320 3201.D. Information Visualization 160 80 20 20 40 40 360 3601.E. Intelligent Decision Support 120 80 80 20 20 40 40 400 4001.F. Real-time Planning 160 160 20 20 40 40 440 2801.G. Mobile Data Input/Output 320 20 40 40 40 460 4601.H. 3D Process Awareness 160 160 20 20 40 40 440 4401.2. Capture design patterns 120 80 80 280 2001.3. Generalization and publishing 320 80 160 160 80 80 80 960 800

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In this work package the theoretical foundation of the planning and decision support solutions is anchored. The theoretical framework of shared situational awareness will be initially developed based on literature and field studies, and will be iteratively improved and enhanced during the various case studies. The principles behind the various innovative tools will further be captured as design patterns. Design patterns provide a format for the capturing of lessons learned in a transferable way. Furthermore, design patterns are combined in a pattern language that explains the relation between the various principles of shared situational awareness.

TU Delft is the leading partner in this work package, supported by the Open University. For the various innovation teams work load is divided based on expertise. The terminals are involved to derive practical feedback on each innovation theme.

Milestones are the initial SSA framework, and the final framework based on various iterations. Further the establishment of the design pattern library is a key deliverable as well as the key design guidelines for each of the innovation themes.

Work Package 2. Shared Situational Awareness Tool Development

2.1. Generic Tool Architecture and requirements elicitation2.A Uncertainty Monitoring2.B. Probabilistic Forecasting2.C. Cross-Partner Collaboration2.D. Information Visualization2.E. Intelligent Decision Support2.F. Real-time Planning2.G. Mobile Data Input/Output2.H. 3D Process Awareness2.2. Generalization and publishing

WP2SSA Tool Development 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12

2.1. Generic Tool Architecture2.A Uncertainty Monitoring2.B. Probabilistic Forecasting2.C. Cross-Partner Collaboration2.D. Information Visualization2.E. Intelligent Decision Support2.F. Real-time Planning2.G. Mobile Data Input/Output2.H. 3D Process Awareness2.2. Generalization and publishing



SSA Tool Development 0 1480 80 0 320 0 2000 280 760 160 160 0 5240 52402.1. Generic Tool Architecture 200 80 200 40 40 560 5602.A Uncertainty Monitoring 160 160 120 20 20 480 4802.B. Probabilistic Forecasting 120 20 320 40 20 20 540 5402.C. Cross-Partner Collaboration 160 160 320 20 20 680 6802.D. Information Visualization 160 160 40 80 20 20 480 4802.E. Intelligent Decision Support 120 20 120 40 120 20 20 460 4602.F. Real-time Planning 160 160 40 20 20 400 4002.G. Mobile Data Input/Output 120 20 80 360 40 20 20 660 6602.H. 3D Process Awareness 120 80 320 40 20 20 600 6002.2. Generalization and publishing 160 20 80 40 40 40 380 380

The tools for each of the innovations will have very different natures in the way they are based on real time dynamic data and expertise, in the way they analyses and visualize this data to support planning and decision making, and in the way the offer means to explore the

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implications of alternatives and to capture decisions and choices for direct communication and collaboration and for future organizational learning. Tools will be developed in a generic way, so they can be effective for the terminals, but easily adapted to other application settings in the Msc projects.

TU Delft and TBA are core partners in the tool design, other partners are involved based on expertise. The terminals will provide initial feedback on the design and will be involved in requirements elicitation.

The key deliverables of this work package are the 8 tools or tool sets for each of the innovation themes. Each tool should have a sound theoretical foundation and an innovative character.

Work Package 3. Tool Evaluation with Partners

3.1. Setup of evaluation3.A. Uncertainty Monitoring3.B. Probabilistic Forecasting3.C. Cross-Partner Collaboration3.D. Information Visualization3.E. Intelligent Decision Support3.F. Real-time Planning3.G. Mobile Data Input/Output3.H. 3D Process Awareness3.2. Integrate evaluation results

WP3SSA Tool Evaluation with Partners 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12




SSA Tool Evaluation with Partners 0 920 240 0 160 0 360 100 110 960 960 0 3810 38103.1. Setup of evaluation 200 40 40 20 10 310 3103.A. Uncertainty Monitoring 80 40 20 120 120 380 3803.B. Probabilistic Forecasting 80 40 20 120 120 380 3803.C. Cross-Partner Collaboration 80 40 20 120 120 380 3803.D. Information Visualization 80 40 20 20 120 120 400 4003.E. Intelligent Decision Support 40 40 40 20 20 120 120 400 4003.F. Real-time Planning 80 40 20 120 120 380 3803.G. Mobile Data Input/Output 40 40 40 20 120 120 380 3803.H. 3D Process Awareness 40 40 40 20 120 120 380 3803.2. Integrate evaluation results 320 40 40 20

In this work package we will evaluate the tools on rigor and relevance by testing them in the field with the terminal partners. The tools will be implemented and will use real data from the terminal’s. The tools will be evaluated by users and where applicable with experts and students.

The evaluation will require use and experimentation by the terminals. The evaluation will have both a practical and scientific nature. Different evaluation instruments will be developed by the knowledge institutes involved. The developing companies will support the case studies and test implementations.

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Key milestones are the delivery of the evaluation instruments, the experiments for evaluation and data collection and the analysis of the evaluation results. The evaluations will be a basis for publication and dissemination activities.

Work Package 4. Tool evaluation with User Group in Wider Supply Chain Community

4.1. Setup of MSc assignments4.A. Uncertainty Monitoring4.B. Probabilistic Forecasting4.C. Cross-Partner Collaboration4.D. Information Visualization4.E. Intelligent Decision Support4.F. Real-time Planning4.G. Mobile Data Input/Output4.H. 3D Process Awareness4.2. Integrate evaluation results

WP4SSA Tool Evaluation with User Group 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12




SSA Tool Evaluation with User Group 0 580 140 13200 120 0 360 110 120 0 0 1280 15910 14304.1. Setup of MSc assignments 80 20 20 20 10 150 1504.A. Uncertainty Monitoring 40 1650 40 20 160 1910 1004.B. Probabilistic Forecasting 40 1650 40 20 160 1910 1004.C. Cross-Partner Collaboration 40 1650 40 20 160 1910 1004.D. Information Visualization 20 1650 20 40 20 20 160 1930 1204.E. Intelligent Decision Support 20 20 1650 40 20 20 160 1930 1204.F. Real-time Planning 40 1650 40 20 160 1910 1004.G. Mobile Data Input/Output 20 1650 20 40 20 160 1910 1004.H. 3D Process Awareness 20 1650 20 40 20 160 1910 1004.2. Integrate evaluation results 320 40 40 20 10 10

In this work package the tools will be adapted to fit one or two other implementation domains. In these case studies, performed by Msc students, the key objective will be to show how the tool can be applied in different contexts. The evaluation of the tool will be part of the master thesis project and thus will be performed on a smaller scale than in the partner implementation.

These implementations and evaluations will be performed by msc students. The developing partners will support adaptation of the tools, while the knowledge institutes will supervise the Msc students and support them in the use of the evaluation tools and methods from the previous phase.

The core deliverable consists of one or two Msc dissertations per innovation

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Work Package 5. Training Tool Development and Testing


WP5Training Tool Development & Test 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12




Training Tool Development & Test 0 1040 0 0 50 480 180 800 80 320 320 0 3270 27905.1. Generic Tool Architecture 240 10 20 80 350 3505.A Uncertainty Monitoring 80 80 20 80 40 40 340 2605.B. Probabilistic Forecasting 80 40 20 80 40 40 300 2605.C. Cross-Partner Collaboration 80 40 20 80 80 40 40 380 3405.D. Information Visualization 80 80 20 80 40 40 340 2605.E. Intelligent Decision Support 80 80 20 80 40 40 340 2605.F. Real-time Planning 80 80 20 80 40 40 340 2605.G. Mobile Data Input/Output 80 20 40 20 80 40 40 320 2805.H. 3D Process Awareness 80 20 40 20 80 40 40 320 2805.2. Generalization and publishing 160 80 240 240

In this work package the training environment around the tools is developed, and the training approach and scenarios are developed based on the experiences with the tools in the partner and Msc projects. The training environment will contain a 3D game interface and a collaboration and interaction environment for the training.

The core partner involved in the training environment is in there as they will build the micro games. They will be assisted in the design by TBA and TU Delft also to ensure the coupling of the tools and the training environment.

The core deliverable is a 3d interface to each of the tools for training and a training approach with learning goals and a training scenario.

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Work Package 6. Dissemination

6.1. Capture results in dissertation6.2. User group meetings (2/year)6.3. Half-way Dinalog workshop6.4. Final SALOMO/Dinalog workshop

WP6Dissemination 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12




Dissemination 0 1305 80 0 80 0 1145 40 40 160 160 640 3650 30106.1. Capture results in dissertation 825 825 1650 16506.2. User group meetings (2/year) 176 48 48 176 24 24 96 96 384 1072 6886.3. Half-way Dinalog workshop 152 16 16 72 8 8 32 32 128 464 3366.4. Final SALOMO/Dinalog workshop 152 16 16 72 8 8 32 32 128 464 336

The final work package contains the various dissemination activities that are also described in section E below.

All partners will be involved in the workshops, while TU Delft and TBA will take the lead in capturing the results of the two phd’s in the project in dissertations.

Milestones proposed are the workshops and the dissertations at the end of the project.

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Planning

The planning can be found in Annex 4J, and was detailed in the previous section.

C. Consortium and Project Organization

Research TeamThis section describes the research team, each specific role and input in the project (if necessary per activity / work package) and their quality / specific expertise.

Short CVs (max ½ page A4) of the scientific researchers should be included as Annexes, along with a shortlist (titles and sources) of their 5 most relevant publications or relevant project experience.

Also describe the relevant past performance of the other consortium partners.

Partner’s name Role and input Specific competence

TRAIL TRAIL will facilitate the project mainly from a network perspective offering access to experts and researchers in the field and a platform for dissemination of scientific results.

The TRAIL researchers will form an excellent source of scientific input and challenge for the SALOMO project. The PhD students in the project will become TRAIL PhD students, benefiting from the large network, training, and conferences / workshop.

TRAIL will also act as an outlet to demonstrate the developed instruments and training tools to the wider supply chain community.

Within TRAIL, Erasmus University of Rotterdam, Delft University of Technology, Eindhoven University of Technology, University of Twente and Radboud University Nijmegen collaborate. Twelve faculties and institutes (spanning the fields of economics, technology, policy and management, and the social and behavioral sciences) form a strong concentration of scientific experts in the fields of traffic and transport. Over 200 researchers, of whom about 80 are PhD candidates, are active in TRAIL.

Delft University of Technology, Faculty of Technology, Policy and Management, department of Systems Engineering and department of Transport and Logistics

The Systems Engineering department will provide the project leaders. Its role will be focused on the design of the various tools and training environments, the scientific foundations for these tools and the modeling of situational awareness.

The transport and logistics department will bring in

Systems Engineering has an extensive history in two core disciplines of the proposal. Firstly, the simulation research, particularly related to logistics and supply chains, e.g. with projects on AGV’s and rail simulations. Second, decision support and enhancement tools such as the Group Decision room, serious games on supply

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extensive expertise in the transport and logistics domain.

chain management and decision enhancement studio’s.

The Transport and Logistics department also has extensive experience in games, tools and simulations for logistics and transport.

Open University, Centre for Learning Sciences and Technologies (CELSTEC)

CELSTEC will offer a theoretical foundation for the training tools and will introduce specific innovative learning methods and environments in the context of gaming and simulation.

CELSTEC has extensive experience in innovative educational design and development of educational technologies. The department has also shown innovative educational Augmented Reality applications.

TBA TBA is the main link between the research and industry partners in the project. They bring in existing control software for container terminal planning, and they will ensure the link between the innovative training tools to be developed and the existing tools and operating systems. TBA will mainly focus on the development of the tools for planning and decision making

TBA has experience in the development of systems for control, simulation and planning and decision making in supply chains.

InThere InThere will develop the virtual 3D gaming environment for the training tools.

InThere has experience in the (rapid) design of 3d virtual serious games

Teamsupport Teamsupport will develop the collaborative interface for the collaboration tools and the training environment

Teamsupport has developed a generic collaboration support tool for brainstorming, clustering and voting

Project organizationAs indicated in the work packages, the project adopts an iterative approach to the design of the tool and training suite. This iterative design cycle will contain a rigor and relevance cycle for each deliverable, based on Hevner et al’s (2004) design science approach. The rigor cycle ensures that the tools have a foundation on theories, frameworks and approaches in literature, and that findings are captured as new or modified knowledge contributions. The relevance cycle ensures that the tools are build based on real requirements, and that they are evaluated on usefulness by the industry partners. Core responsibility for the rigor cycle is positioned with the senior researchers of the systems engineering department, that will involve the other academic partners in this effort. Core responsibility for the relevance cycle will be positioned with TBA, that will be the linking partner to the industry partners. Close collaboration and coordination between TBA and Systems Engineering will be established though a joint PhD student working at TBA , in addition to the PhD at Systems Engineering, and close collaboration between the TBA and SE project leaders. Collaboration and coordination in the consortium will be facilitated by regular joint workshops where all participants exchange progress and challenges, and jointly design key foundations of the tools and training instruments in concurrent design efforts. This organizational

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design focused on guarding quality is supplemented by the involvement of the User Community for further relevance feedback and the supply chain experts for further rigor feedback. The quality management approach is visualized below.

D. Evaluation and Monitoring

EvaluationMetrics and evaluation instruments will be developed to evaluate the effectiveness of the tools and techniques in supporting planning and decision making, and to evaluate the training with respect to it’s learning goals. Each tool and technique and associated training will be evaluated in the context of container terminals, and some will be evaluated in the context of another supply chain hub. The evaluation will be conducted in field studies, where actual planners and decision makers will use the tools and techniques in a training setting. Evaluations will take place in groups with representative sizes and compositions, and should be reproduced in several cases. We will further aim to evaluate all tools and techniques and associated trainings in education as well.

Where possible, we will add expert feedback and/ or qualitative evaluations (interviews, observations) for corroboration. Each tool/technique and training approach should be evaluated rigorously and in sufficient cases in order to enable publication in international conferences with peer-reviewed proceedings. While the aim is to submit findings to journals, publication of journal papers might not be feasible within the scope of the project because of the length of the review cycle.

To validate the conceptual model, the mechanism library and the simulation model, expert panels will be used. Similarly, these validations have to be sufficiently rigorous to enable publication in international conferences with peer-reviewed proceedings. We will use group support systems to efficiently collect expert feedback. These evaluations will at least take place after establishing the initial models that are used as a basis for design and after the final additions and modifications based on experiments have been accommodated.

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For each tool/training combination the following evaluations are required:

1. theoretical foundation rigor verification (literature, experts)2. requirements relevance verification (user focus groups, survey’s interviews)3. design rigor evaluation (experts)4. design relevance evaluation (users)5. tool rigor evaluation e.g. effectiveness, decision enhancement (survey’s interviews, user

workshops)6. tool relevance evaluation e.g. usefulness (survey’s interviews, user workshops)7. training rigor & relevance evaluation e.g. learning effects (survey’s interviews, user

workshops, training performance)

These evaluations have to be performed for the terminal implementation of each tool/training combination, and in less rigorous and extensive form in the dissemination case studies. Further, some can be performed in educational setting. Some evaluations for rigor and relevance can be combined.

E. Valorization and Implementation Strategy

Valorization and knowledge dissemination The SALOMO project will install a SALOMO User Group, which consists of a wide set of companies that are active in the supply chain. The SALOMO researchers and associated companies will meet twice a year with the User Group to solicit input, discuss progress, and demonstrate results. Once a year, the User Community meeting will be connected to a working conference, co-organized with Dinalog, to inform the entire Dinalog community.

The academic results will be shared with the international scientific community through publications in high-end journals, presentations at conferences, and demonstrations at workshops. A number of international supply chain specialists from the Supply Chain Management Center, R.H. School of Business of the University of Maryland have agreed to participate pro bono in the project and help anchor the results in the most recent supply chain tradition (see Annex 4A).

The wider audience will be informed through a number of non-specialist publications and demonstrations of the micro-games at various conferences and professional presentations.

ImplementationThe developed methods and tools will be implemented at the project partners as part of the research. In addition, each innovation will be part of one or two MSc student projects in which we will implement the methods and tools, and test the applicability and effects of the 8 tools at a number of supply chain hubs of the SALOMO User Community partners. We have already received a number of emails and letters from interested partners (see Annex 4C) who would like to host one or more students for half a year. In this way, we gather a large number of cases where the SALOMO deliverables are introduced and evaluated.

The training tools that have been developed will be implemented at several educational institutes: Delft and Maryland are planning to implement it in their regular education. PhD education will be addressed through TRAIL. Later, Dinalog and other universities will be provided with the training instruments to use in their educational programs.

The developed decision support and training products will be made available to the market through TBA (DSS), InThere (Microgames) and TeamSupport (collaboration tools). As they are part of the project with only partial payment, they expect to be able to go to a wider market with the developed tools after the project.

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Annex 4A. CVs of Researchers in the SALOMO project

TRAIL / TU Delft Researchers

Alexander VerbraeckAlexander Verbraeck is Full Professor of Systems and Simulation in the Faculty of Technology, Policy and Management at Delft University of Technology, The Netherlands. In addition, he is part-time Research Professor in Supply Chain Management at the R.H. Smith School of Business of the University of Maryland in the USA. He has a BS in Mathematics, and an MSc and PhD in Computer Science, all from Delft University of Technology. His research focuses on discrete-event simulation, serious gaming and training, logistics and transportation, and project management. He is a member of the Center for Project Management at TU Delft, and he is heavily involved in project management research and training for industry. As a co-director of TU Delft's serious gaming institute, he researches novel applications of interactive simulation and virtual worlds.

Dr. Verbraeck served on the editorial boards of Simulation and Simulation Modelling Practice and Theory, and is currently on the boards of Journal of Simulation, International Journal of Simulation and Process Modelling and Simulation and Gaming. Many of his multi-year research projects have been funded by national programs and by the European Union. His applied research in simulation and gaming has been funded by many organizations, among which The Royal Dutch Navy, Maersk, Shell, KLM, Amsterdam Airport Schiphol, Port of Rotterdam, the National Forensics Institute, and Dutch Railroads.

He presented over 100 refereed papers at conferences, wrote close to 20 book chapters, and published his work in journals such as Journal of the Operational Research Society, Computers & Education, Transportation Research part E, Simulation, Journal of Simulation, and Simulation Practice and Theory.

Selected publications

T.M. Corsi, S. Boyson, A. Verbraeck, S.P.A. van Houten, C. Han, J. MacDonald, "The Real-Time Global Supply Chain Game: New Educational Tool for Developing Supply Chain Management Professionals". Transportation Journal, 45(3), 2006, pp. 61-73.

S. Boyson, T.M. Corsi, A. Verbraeck. "The e-supply chain portal: a core business model". Logistics and Transportation Review Part E, Vol. 39, 2003, pp. 175-192.

M.C. van der Heijden, Y.A. Saanen, A. van Harten, E.C. Valentin, M.J.R. Ebben, A. Verbraeck. "Safeguarding Schiphol Airports accessibility for freight transport - The design of a fully automated underground transport system with an extensive use of simulation". Interfaces Vol. 32, No 4, July-August 2002, pp. 1-19.

G.L. Kolfschoten, S.G. Lukosch, A. Verbraeck, E.C. Valentin, G.J. deVreede. "Cognitive learning efficiency through the use of design patterns in teaching". Computers & Education. Vol. 54, No.3, April 2010, Pages 652-660.

C.A. Boer, A. de Bruin, A. Verbraeck. “A Survey on Distributed Simulation in Industry”. Journal of Simulation. Vol. 3, Issue 1 (March 2009), 3-16.

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Gwendolyn KolfschotenGwendolyn L. Kolfschoten is an assistant Professor at Delft University of Technology, Faculty of Technology Policy and Mangement, department of Systems Engineering in the Netherlands. She is an experienced facilitator of thinkLets-based Group Support Systems workshop having worked with numerous public and private organizations. Her research focuses on the quality of thinkLet-based collaboration process design for complex tasks. Her research has been presented at HICSS and CRIWG, AMCIS and GDN conferences and has been published in the International Journal of Computer Application in Technology, International Journal of Human-Computer Studies and Group Decision and Negotiation.

Selected publications

Kolfschoten, G.L., Vreede, G.J.de., Briggs, R.O., Sol, H.G. (2010) Collaboration 'Engineerability'. Group Decision and Negotiation (19)3, pp 301-321

Kolfschoten, G.L., Lukosch, S.G., Verbraeck, A., Valentin, E., Vreede, G.J.de. (2010) Cognitive Learning Efficiency Through the Use of Design Patterns in Teaching. Computers and Education 54(3), pp. 652-660

Lei, T. E. van der, Kolfschoten, G.L., Beers, J.P. (2010) “Complexity in multi-actor system research: towards a meta-analysis of recent studies” Journal of Design Research 8 (4), pp 317-342

Kolfschoten, G.L. and de Vreede G.J., (2009) "A Design Approach for Collaboration Processes: A Multi-Method Design Science Study in Collaboration Engineering," Journal of Management Information Systems. 26(1), pp. 225-256.

Renger, D.R.M. Kolfschoten, G.L. and de Vreede, G.J. (2008) "Challenges in Collaborative Modelling: a Literature Review and Research Agenda," International Journal of Simulation and Process Modelling. 4, pp. 248-263.

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Lori Tavasszy

Prof. dr. ir. L.A. Tavasszy (Lóri) is senior advisor Mobility & Logistics at the research institute TNO in Delft and Professor in Freight and Logistics at the Delft University of Technology. He studied Civil Engineering at the Delft University of Technology with specialisations in transport modelling and spatial development. He completed his PhD. study in 1996 on a strategic model of freight transport flows within Europe. His research has since then focused on the modelling of linkages between logistics, freight transport and spatial development. He has extensive experience in project management for Dutch and European clients in the area of logistics, transport forecasting and policy analysis. Member of Association for European Transport; Chair of Committee, Freight & Logistics of the European Transport Conference; Scientific Committee Member Mo.Ve Mobility Forum (2003-2005); International Member of Transportation Research Board Freight Modelling Task Force (2005-2007); Board of Management Transport & Mobility Leuven; Expert Member of National Council for Transport, Waterways and Public Works; Member of ERTRAC (European Road Transport Research Advisory Council) Working Group on Long Distance Freight Transport; NECTAR (Network on European Communications and Transport Activities Research); Academic member of Logistics knowledge council of Dutch shippers' association EVO. Reviewer for various Journals and conferences (ETC, TRB, ERSA, WCTR, TVW, TRAIL, JTEP, EJTIR, JTP, TRC); editorial board of EJTIR and Netherlands Transport Science journal, advisory board of ETRR. Awards: 1998 Yokohama Prize at World Conference for Transport Research in Antwerpen, Belgium Lectures on freight transport modelling and policy at the Faculty of Civil Engineering and Faculty of Systems Engineering and Policy Analysis of Delft University. Guest lectures abroad at several institutes (MIT Boston, MA; RAND, Santa Monica, Cal.; UCNL, London, UK; UGD, Gdansk Poland; Leuven University, Belgium; RUG, Groningen, NL, DTU Denmark, ITMMA, UFSIA, Antwerpen University).

Selected publications Tavasszy, L.A., Smeenk, B., C.J. Ruijgrok (1998), A DSS for modelling logistics

chains in freight transport systems analysis, International Transactions. in Operational Research, Vol. 5, No. 6, pp. 447-459. Republished in K. Button, P.Nijkamp, A. McKinnon (eds), Classics in Transport Analysis: Transport Logistics, Edward Elgar Publishers, 2003

Tavasszy, L.A., C.J. Ruijgrok, M.J.P.M. Thissen (2003), Emerging global logistics networks: implications for transport systems and policies, Growth and Change: A Journal of Urban and Regional Policy, Vol. 34 No. 4, pp. 456-472

Groothedde, B., C.J. Ruijgrok, L.A. Tavasszy (2005), Towards collaborative, intermodal hub networks. A case study in the fast moving consumer goods market, Transportation Research E, Vol. 41 Issue 6, pp. 567-583

Koike, A., L.A.Tavasszy, K. Sato (2009), Spatial Equity Analysis on Expressway Network Development in Japan, Transportation Research Record 2133, 46-55 Tavasszy, L.A, I.

Tavasszy, L.A., F. Combes (2010), Endogeneous value of time in freight transportation models, in: van de Voorde, E., T. Vanelslander (eds.): Applied Transport Economics, a management and policy perspective, Uitgeverij de Boeck: Antwerpen

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J.H.R. van Duin

Ron van Duin works as an assistant professor in logistics at the Delft University of Technology. After his study econometrics at the Erasmus University Rotterdam he worked for five years on several logistic business problems at an operations research division of the national applied science organization TNO. Afterwards he started as an entrepreneur in building advanced simulation models, developing and teaching educational courses in logistics and simulation, and implementing logistics information systems (SAP/R3). Since 1994 he works at the faculty of Technology, Policy and Management doing research and teaching on logistics concept/policy development in multi-actor environments. City logistics and policy making have his main research interests. He acts as ad-hoc reviewer for many journals, conferences and research foundations in logistics.

Selected publications:

Van Duin, J.H.R., Quak, H., Muñuzuri Sanz, J., “New challenges for urban consolidation centers: A case study in The Hague”, in Procedia Social and Behavioral Sciences 2 (2010), pp 6177-6188, Elsevier Ltd.

Duin, JHR van, Quak, HJ, & Munuzuri, J (2007), Revival of the cost benefit analysis for evaluating the city distribution center concept? In E Taniguchi & RG Thompson (Eds.), City Logistics V (pp. 93-107). Japan: Insitute for City Logistics.

Duin, JHR van, Tavasszy, LA, & Taniguchi, E (2007). Real time simulation of auctioning and re-scheduling processes in hybrid freight markets. Transportation research part B-methodological, 41, 1050-1066.

Duin, JHR van, & Wee, GP van (2007). Globalization and Intermodal Transportation: Modeling Terminal Locations Using a Three-Spatial Scales Framework. In R Cooper, K Donaghy, & G Hewings (Eds.), Globalization and Regional Economic Modeling (pp. 133-152). Heidelberg: Springer.

Taniguchi, E., Thompson R.G., Yamada, T., van Duin, R. (2001), City Logistics: Network Modelling and Intelligent Transport Systems, ISBN: 0-08-04903-9, 260 pages, Pergamon

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Open University Researchers

Prof. Dr. Marcus Specht

Marcus Specht is Professor for Advanced Learning Technologies at Centre for Learning Sciences and Technologies at the Open University of the Netherlands. He is currently involved in several national and international research projects on competence based life long learning, personalized information support and contextualized and mobile learning. He received his Diploma in Psychology in 1995 and a Dissertation from the University of Trier in 1998 on adaptive information technology. From 1998 until 2001 he worked as senior researcher at the GMD research center on HCI and mobile information technology. From 2001 he headed the department "Mobile Knowledge" at the Fraunhofer Institute for Applied Information Technology (FIT). From 2005 he was Associated Professor at the Open University of the Netherlands and working on competence based education, learning content engineering and management, and personalization for learning. Currently he is working on Mobile and Contextualized Learning Technologies, Learning Network Services, and Social and Immersive Media for Learning.

Selected publications:

Specht, M. (2009). Learning in a Technology Enhanced World. Maastricht, The Netherlands: OCÉ.

Ternier, S., Specht, M., De Vries, F., De Jong, T., & Börner, D. (2010). ‘Mobile Augmented Reality’ voor het Onderwijs. Surfnet & Kennisnet, Innovatie-programma.

http://hdl.handle.net/1820/2431 de Jong, T., Specht, M., & Koper, R. (2010). A Study of Contextualised Mobile

Information Delivery for Language Learning. Educational Technology & Society, 13 (3), 110–125.

Specht, M. (2009). Towards Contextualized Learning Services. In Koper, R. (Ed.). Learning Network Services for Professional Development. Springer 2009. pp 241-254

De Jong, T., Specht, M., & Koper, R. (2008). A Reference Model for Mobile Social Software for Learning. International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL). 18(1), 118-138.

De Jong, T., Specht, M., & Koper, R. (2008). Contextualised Media for Learning. Journal of Educational Technology & Society, 11(2), 41-53.

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http://hdl.handle.net/1820/2431

Dr. Christian Glahn

Christian Glahn has more than 10 years of experience in technology-enhanced learning. Before 2000 he developed innovative customer-binding solutions for e-commerce systems in Greece and Germany. Between 2000 and 2002 he has been the technical lead at Innsbruck University for the first university-wide deployment of a learning management system in the German-speaking countries. From 2003 to 2005 he researched innovative solutions for educational technologies for organizational and mobile learning at the Austrian Research Centers. Since 2006 Christian Glahn works at the Centre for Learning Sciences and Technologies (CELSTEC) where is assistant professor. His research focuses on mobile and awareness systems for self-organized and organizational learning. He took responsibilities in international research and technical development projects, including the TENCompetence (FP6), GRAPPLE (FP7) and STELLAR (FP7). Glahn has more than 30 international publications and is member of several program committees and review boards of international journals and conferences.

Selected publications: Kelle, S., Börner, D., Kalz, M., Specht, M., & Glahn, C. (2010). Ambient Displays

and Game Design Patterns for Social Learning. In B. Chang, T. Hirashima, & H. Ogata (Eds.), Joint Proceedings of the Work-in-Progress Poster and Invited Young Researcher Symposium for the 18th International Conference on Computers in Education (pp. 47-50). November, 29 - December, 3, 2010, Putrajaya, Malaysia: Asia-Pacific Society for Computers in Education.

Börner, D., Glahn, C., Stoyanov, S., Kalz, M., & Specht, M. (2010). Expert concept mapping study on mobile learning. Campus-Wide Information Systems, 27(4), 240-253.

Glahn, C., & Specht, M. (2010). Embedding Moodle into Ubiquitous Computing Environments. In M. Montebello, et al. (Eds.), 9th World Conference on Mobile and Contextual Learning (MLearn2010; pp. 100-107). October, 19-22, 2010, Valletta, Malta.

Börner, D., Glahn, C., & Specht, M. (2009). Mobile Informal Learning. Presentation for the Education in the Wild: contextual and location-based mobile learning in action workshop at the STELLAR Alpine Rendez-Vous 2009. November, 30-December, 3, 2009, Garmisch-Partenkirchen, Germany.

Loskyll, M., Heckmann, D., & Glahn, C. (2009). Visualization of Spatial Knowledge with Ontology Trees and Adaptable Search Result Grids in the Era of Web3.0. In K. Tochtermann & H. Maurer (Eds.), Proceedings of the I-Know'09, 9th International Conference on Knowledge Management and Knowledge Technologies (pp. 385-390). Graz, Austria: Verlag der Technischen Universität Graz.

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Dr. Wolfgang Greller

Associate Professor Dr. Wolfgang Greller is International Projects Manager at the Centre for Learning Sciences and Technologies (CELSTEC) of the Open University of the Netherlands. He holds a PhD and has for the past eighteen years been involved in a leading role in the domain of Technology Enhanced Learning and Learning Technology and its institutionalization at various universities around Europe and beyond. He played a substantial strategic role in the creation of networked universities like the University of the Highlands and Islands or the University of the Arctic. Before joining OUNL, he was Head of E-Learning at the University of Klagenfurt, Austria, and therefore brings into the project an inside understanding of innovation management and change from different European countries. He also acquired and managed several EU funded projects from various sources (Lingua, ERDF, ESF, Grundtvig, EBLUL, etc.). He joined OUNL in 1997 taking up responsibilities in the projects TENCompetence (FP6) and idSpace (FP7). Most recently, he coordinated a project on interaction design and evaluation for innovative technologies.

Selected publications: Dimensions of Mobile Augmented Reality: A First Inventory; Stefaan Ternier,

Wolfgang Greller, Marcus Specht. In: Journal of the Research Center for Educational Technology (RCETJ) Spring 2011 issue

Educational Innovation with Learning Networks: some pertinent tools and developments; Adriana Berlanga, Peter Sloep, Wolfgang Greller. In: Proceedings of the 2nd International Conference on Technology Enhanced Learning, Quality of Teaching and Reforming Education Conference (TechEducation 2011), 18th-20th May 2011, Corfu, Greece (forthcoming)

Personal perspectives on knowledge development in Learning Networks: Hendrik Drachsler, Wolfgang Greller, Wendy Kicken. In: Sloep, P. and Van de Klink, M. (Eds.) Learning Networks – A Handbook for Practitioners. Springer 2011 (forthcoming)

Language Technologies for Lifelong Learning: Wolfgang Greller; in: Proceedings of the Workshop on Natural Language Processing in Support of Learning: Metrics, Feedback and Connectivity, Bucharest, 14 September 2010

e-Portfolios for Learning and Development: Without Constant Internet or Electric Grid Access: James Uhomoibhi, John Casey, Wolfgang Greller and Gayle Calverley; in: Proceedings of the 5th International Conference on ICT for Development, Education, and Training - eLearning Africa; Lusaka, Zambia 26-28 May 2010

Designing for Change: Visual Design Tools to Support Process Change in Education; John Casey, Wolfgang Greller, et al. in: 'Handbook of Visual Languages for Instructional Design: Theories and Practices'; edts. Luca Botturi & Todd Stubbs, 2008

The RDA of Healthy e-Learning Standards; Wolfgang Greller, John Casey; in: Journal of e-learning and Knowledge Society (Je-LKS) 2007/2; Società Italiana di e-Learning

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University of Maryland Researchers

The researchers from the R.H. Smith School of Business are not a funded part of the project, but they provide external support and challenge for complex and volatile supply chain management.

Thomas M. Corsi

Professor Corsi joined the Robert H. Smith School of Business in 1976 as a Professor of Logistics and Transportation. He served as Chairperson of the Logistics and Transportation Group from 1986 through 1994. During that time, the Group received recognition from the Transportation Journal as the most prolific faculty group in the nation based on published research in the field. He is an associate editor of the Logistics and Transportation Review and the Journal of Business Logistics and serves on the editorial review board of the Transportation Journal and the International Journal of Physical Distribution and Logistics Management. He has authored more than 100 articles on logistics and transportation, and co-authored four books. He has consulted for such organizations as the Interstate Commerce Commission, the Maryland State Department of Transportation, the National Science Foundation, the United States Department of Transportation, the National Truck Stop Operators, United Parcel Service, the United States Department of Energy, and the U.S. Army Logistics Agency.

Selected publications (in addition to the 3 books listed with Lisa Harrington):

Rabinovich, Elliot; Dresner, Martin; Windle, Robert J.; and Corsi, Thomas M., "Outsourcing of Integrated Logistics Functions: An Examination of Industry Practices," International Journal of Physical Distribution and Logistics Management, Vol. 29, No. 5, 1999, pp.353-373.

Corsi, Thomas M. (with Curtis Grimm and Kirk Patterson), "Adopting New Technologies for Supply Chain Management," Transportation Research: Part E, The Logistics and Transportation Review, Vol. 39, March 2003, pp. 95-122.

Corsi, Thomas M. (with Sandor Boyson and Alexander Verbraeck), "The e- Supply Chain Portal: a Core Business Model," Transportation Research: Part E, The Logistics and Transportation Review, Vol. 39, March 2003, pp. 175-192.

Corsi, Thomas M. (with A. Micheal Knemeyer and Paul Murphy),"A Comparison of Key Logistics Outsourcing Relationship Constructs Across Levels of Partnership Development," Journal of Business Logistics, March 2003, Vol. 24, No. 1, pp. 77-110.

Corsi, Thomas M. (with Curtis M. Grimm and Kirk Patterson), "Diffusion of Supply Chain Technologies," Transportation Journal, Summer 2004, Vol. 43, No. 3, pp. 5-23.

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Sandor Boyson

Dr. Boyson has significant expertise in Technology Management and Supply Chain Management, with over thirtyears experience in strategic technology planning, systems development/management, and enterprise-wide process integration. He has served as a technology and strategy consultant to public organizations as varied as the World Bank and the Department Of Defense; and private sector organizations such as Allied Signal, Hughes Network Systems and the Chicago Tribune.

He served as Chief Information Officer at the Robert H. Smith School of Business at the University of Maryland, College Park and is currently the Co-Director of the Supply Chain Management Center and a Research Professor at the Smith School. He has generated and managed approximately $12million in research contracts over the past fifteen years from organizations including National Science Foundation, DARPA, and NIST (National Institute of Standards and Technology). In addition, he has initiated partnerships with leading edge companies ranging from Sun, Oracle, Cisco, Avaya, General Electric, IBM and Manugistics that have resulted in $7.4 million of booked contributions in hardware, software and services to the Smith School. He is the co-author of three books on Supply Chain Management with Thomas M. Corsi and Lisa Harrington.

Selected publications (in addition to the 3 books listed with Lisa Harrington) Boyson, Sandor (with Thomas M. Corsi), "Real-time e-supply chain management:

diffusion of new technologies and business practices," Transportation Research: Series E (The Logistics and Transportation Review), Vol. 39, March 2003, pp. 79-82.

Boyson, Sandor “ The Netcentric Supply Chain In Practice”, IEEE Transcripts Of The 2002 Hawaii Conference On Information Systems, Washington, D.C.

Boyson, Sandor (with Thomas M. Corsi), "North America Logistics Insights and Challenges," in volume edited by Anne M. Brewer, Kenneth J. Button, and David Hensher, entitled Handbook of Logistics and Supply-Chain Management, Transport and Supply Chain and Logistics Handbook, Elsevier Science, Ltd., Oxford, U.K., 2001, pp. 47-58.

Boyson, Sandor "The Real-Time Supply Chain," Supply Chain Management Review, Vol. 5, No. 1, January/February 2001, pp. 44-51.

Boyson, Sandor; Corsi, Thomas M.; Dresner, Martin; and Rabinovich, Elliot," Managing Effective Third Party Logistics Partnerships: What Does It Take,” Journal of Business Logistics, Vol. 20, No. 1, 1999, pp. 73-100.

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Lisa Harrington

Lisa H. Harrington is the president of Harrington Associates, a provider of a variety of consulting and communications services within the general industry topic areas of supply chain management, logistics, transportation, warehousing and e-commerce. These services include strategic consulting for clients in the area of supply chain management best practices. Clients include: A.T. Kearney, BP-Amoco, Cushman & Wakefield, Ernst & Young LLP—Supply Chain Management Practice, Evolve Software Inc., Exel plc, Georgetown University Graduate School of Business, i2 Technologies, Intel Corp., Manugistics Software Inc., Mercer Management Consulting—Supply Chain Management Practice, National Private Truck Council, NorthAmerican Logistics, PricewaterhouseCoopers – Supply Chain Management Practice, REM Associates Inc., Ryder Corp. -- Integrated Logistics, Standard Corporation, USFreightways Corp., and the Warehousing Education & Research Council. She is a Senior Fellow at the Supply Chain Management Center, Robert H. Smith School of Business as well as an Adjunct Professor at the Smith School. She also holds a research position for the Center for Policy Studies within the School of Public Policy at the University of Maryland.

Selected publications: Boyson, S., Corsi, T.M., Dresner, M., and Harrington, L.H. Logistics and the

Extended Enterprise. New York: Wiley, 2000. Boyson, S., L.H. Harrington and T.M. Corsi. In Real Time: Managing the New

Supply Chain. Westport, CT: Praeger Publishers, 2004 Harrington, L.H., S. Boyson and T.M. Corsi. X-SCM. The New Science of X-

treme Supply Chain Management. New York, NY: Routeledge / Taylor & Francis, 2011

Boyson, S., Corsi, T., Dresner, M., and Harrington, L., “Global Supply Chain Management Style Depends on Company Size and Scale,” World Trade, October 2007, pp. 32-36.

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Annex 4B. Company overview and CVs of the key company personnel

InThere

Inthere is a young, dynamic company specializing in the production of Microgames. This form of gaming is more powerful, faster and has a sharper learning goal. The maximum running time is 15 minutes and this microgames are particularly suited for use during daily activities. Microgames are linked to our online platform where user accounts are linked to results from the games. This creates a better understanding of progression and participation of users producing an effective learning environment.

Inthere interacts with other companies to develop products. We have a wide network of programmers, designers and developers so we are both small and large projects successfully completed.We work with:

buffalo Studio for graphic design http://studiobuffalo.nl/ TheLabs for communication and change: http://thelabs, en Roy Korpell for Art: http://www.roykorpel.nl/ and various self-employed professionals and freelancers to produce.

Each microgame is considered a separate project in order to create a highly controllable process. In this way we can give young, enthusiastic developers (including students from TU Delft) the opportunity to develop a game. Giving them experience, knowledge, and of course the income from micro projects.

Microgaming is a fusion of serious gaming and micorlearning. Both techniques have been used successfully in the market, but the combination of both is new. Inthere has successfully implemented a number of prototypes and is currently running several projects focused on the security field and in the nursery. Currently we are actively setting up a complete learning environment within an existing organization. In cooperation with TU Delft, we investigate this new way of learning and work to demonstrate how effective microgaming can be. In the production and development of this area we cooperate with various other parties. Include the programming, interface design, graphic and 3D modeling has been outsourced to other parties.

InThere: Ir. Daan Groen

Daan Groen founded the Delft Centre for Serious Gaming at the Faculty of Technology, Policy and Management, TU Delft, in 2008. The Delft Centre for serious gaming (in short: The Gaming Street) is a group of young professionals with more than an average interest and experience in game development. They create games, simulations or other relevant tools and software for research at TU Delft. Daan’s role was to start and organize a team and he had a large responsibility in leading the production of the gaming projects within the TU Delft.

After two years in this role he transferred his work in 2010 to start the company ‘InThere’. His main responsibility is concept formation and (serious) game development. He is always looking for new opportunities and specialize in making customers excited about the possibilities within their organization. With his experience in 3D visualization, a major responsibility is the 3D work within the games. As a founder he has a large role in creating and developing the company. One of the concepts that ‘InThere’ is pursuing is the further development and deployment of so-called micro-games that provide short training sessions through a realistic Web-based environment.

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http://www.roykorpel.nl/

http://thelabs/

http://studiobuffalo.nl/

TBA

TBA has been established in 1996, as specialist in design and simulation of container terminals. Besides container terminals, TBA works also in the field of airports, warehouses and factories. In total approximately 70 fulltime engineers are working at TBA, plus 4 supporting people, divided over three offices on projects all over Europe, Asia, Africa and the US.

In total, TBA worked on the design and improvement of over 80 container terminals ranging from 50,000 yearly lifts to 4 million yearly lifts, with Straddle Carriers, Automated Lifting Vehicles, AGVs, Shuttle Carriers, Terminal Trucks, Forklifts, MT handlers, RMGs, RTGs and/or OHBCs.

TBA carried out studies for gate design, layout design, handling system design, quay crane design, design of operating strategies, evaluation of TOS systems and many more. TBA VR training success has been proven at the Port of Gothenburg in Sweden, Northport in Malaysia and at the Port of Callao in Peru.

In TBA’s VR training is CONTROLS, TBA’s virtual terminal used as a Training Tool. This enables the user to interact with a “virtual terminal” and therefore directly sees what the impact of his decision was. The main objective of the training is to support increased terminal productivity by giving the operators knowledge how to use the full potential of their Terminal Operation System.

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http://www.tba.nl/index.php?mid=30&lang=en

TBA: Yvo Saanen

Dr. Yvo A. Saanen is Managing Director and Founder (1996) of TBA, a leading terminal design and simulation company in The Netherlands. He is in charge of all port & terminal related projects all over the world in their design process of container terminals by means of simulation. During the last 12 years, he has carried out over 150 large terminal design projects, ranging from long term development, process improvement, terminal extensions and redesign of handling systems to design of greenfield terminals. Examples are the APM facility in Virginia, DPWorld’s facility in Antwerp, and HPH’s Euromax facility in Rotterdam.

Dr. Saanen holds an MSc in Systems Engineering and a PhD on the design and simulation of robotized container terminals, both from Delft University of Technology. He is a lecturer at Delft University of Technology, Lloyd’s Maritime Academy and the institute of Maritime Economics and Logistics (Erasmus University Rotterdam), teaching simulation and logistics and, in various bodies, lectures about terminal design by means of simulation.

Selected publications: Saanen Y.A. and U. Franzke (2000), Preparing simulations for more advanced

purposes: design of an automated container terminal. In: Kai Mertins, Markus Rabe (eds.). The New Simulation in Production and Logistics – Prospects, Views and Attitudes. Proceedings 9. ASIM Fachtagung Simulation in Produktion und Logistik. Berlin, Germany, 8-9 March 2000. IPK, Berlin. ISBN 3-8167-5537-2. p. 233-244.

Saanen Y.A., J. van Meel, and A. Verbraeck (2003). The Design and Assessment of Next Generation Automated Container Terminals. In: ESS’2003, Proceedings 15th European Simulation Symposium 2003 – Simulation in Industry. SCS European Publishing House, Germany, 2003. pp. 577-584.

Saanen Y.A., (2006). Using emulation to improve the performance of your TOS, in: Port Technology International 3/2006.

Saanen Y.A. and M. Valkengoed (2007), Comparison of three automated stacking alternatives by means of simulation. In: Proceedings of the 2005 Winter Simulation Conference.

Boer C.A. and Y.A. Saanen, (2008). CONTROLS: Emulation to improve performance of container terminals, Proceedings of the 2008 Winter Simulation Conference, S. J. Mason, R. R. Hill, L. Moench, O. Rose, eds.

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TBA: Menno Bruggeling

Menno Bruggeling is a Consultant at TBA, a leading terminal design and simulation company in The Netherlands. He joined TBA in May 2010 for a master thesis project on container terminal berth planning, which was completed in 2011. In this capacity, he conceptualized a berth planning decision support tool and successfully completed a prototype. After joining TBA as an employee, he conducted a trial of this prototype at a terminal facility in the United States.

The projects Menno Bruggeling participated in are organized by order of execution, starting in 2000.

Developed a parser to convert simulation models encoded in a proprietary file format into models in an open-source Java modeling library, as well as an XML format. At: TU Delft (2008), external project. Role: student intern.

Was part of a student team that developed a prototype of TeamUp, a TU Delft game in which virtual teams or smalls groups can test, train and reinforce their team’s ‘learning abilities’. At: TU Delft (2009), game design project. Role: student team member.

Trialed a prototype of a container terminal berth planning tool at a customer’s site in the United States. At: TBA (2009). Role: lead consultant.

TBA: Jonatan L. Bijl

Jonatan L. Bijl is a software developer with a special interest in 3D graphics and game engine technology. He has laid the foundations for the 3D visualization of TBA's container terminal simulations, and is currently responsible for the further development and improvement of this 3D animation component. He is also developing an Augmented Reality framework for the Delft University of Technology, which uses a 3D rendering engine to augment indoor scenes with virtual 3D objects.He has a BSc in Software Engineering, and an MSc in Computer Graphics, both from Delft University of Technology.

The projects Jonatan Bijl participated in are: Improvement and optimization of the Java3D-based visualization of TBA's

container terminal simulations. (BSc research, 2006) Implementation of a novel 3D visualization component, based on an open source

game engine, to increase the realism of the 3D visualization. (MSc research, 2008-2009)

Animation of several types of container terminals, for use as instruction material on container terminal operation. (2010)

Optimization and further development of the 3D visualization component (2009-2011)

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TeamSupport

TeamSupport is a software company specialized in building Group Support Systems (GSS). The company is founded by three Computer Science graduates from the Delft University of Technology. The company has built an easy-to-use and modular Group Support System. Next to selling their GSS, TeamSupport also offers full customization of the tool. This can range from layout changes to completely developing new modules and functionalities to optimally support certain areas of expertise, e.g. risk management, strategy implementation, supply chain management, etc. Customized GSS’s have been developed for several customers already. In that sense experience in building a customized GSS according to the wishes of the customer is readily available. The modular infrastructure of the TeamSupport software enables quick and robust customization.

The TeamSupport tool can be used effectively for decision making during anytime in the (logistic) process. For example when in the game a situation has developed where a quick and adequate response/decision has to be made to deal with the situation; the situational information can be imported into the TeamSupport tool after which a quick brainstorm can be done on the possible solutions. These solutions can then be voted on to find the “best” solution that will be taken into action.

Next to this specific example the TeamSupport tool can be connected to (operational) systems to import all kinds of information as input for the decision making process in the field of for example: risk management, strategic decision making, crisis management, planning, etc.

TEAMSUPPORT: Calvin Lee

Calvin successfully completed his master’s programme in Computer Science, specialization Information Architecture, at the Delft University of Technology in 2006. Since then he strives to contribute in the field of Enterprise Architecture (EA) and Business Process Management (BPM) with various publications and guest lectures.

Together with a fellow graduate Calvin founded the consultancy firm Genuince in 2007. As a Genuince consultant Calvin has done various projects in the public sector where he uses the DEMO approach (Design & Engineering Methodology for Organizations) to help organizations align their business with their ICT systems.

In 2009 Calvin co-founded TeamSupport which is a company specialized in developing customized Group Support Systems. Within this company Calvin is responsible for coordinating the development process and Marketing & Sales. In this role his main focus is to introduce the world how simple it is to make organizations’ collaboration efforts more creative, sustainable and of greater value.

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Annex 4C. Letters of Companies Interested to Participate in the User Group

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Annex 4D. Example prototype of a container terminal berth planning tool

The prototype shown here relates to container terminal planning and has been developed as part of a master thesis project at two SALOMO consortium members: the faculty of Technology, Policy and Management of TU Delft and TBA. It deals with the allocation of berths, which are the locations where vessels will moor. The challenge for terminals is that these decisions have to be made well ahead of the vessel call, at a time when the information on which they have to be based is often still incomplete, inaccurate or ambiguous. This prototype is a fully functional program that has already been implemented at a terminal.

Currently, most terminals’ planning tools do not allow for experimentation with the plan, they do not provide the planner with insight into the various possible alternatives and their consequences, and they are not linked to the various information sources relevant to the planning decisions at hand.

This prototype has a strong focus on integrating the available information and providing decision support in a direct way, by allowing the planner to interact with the plan and its consequences. Feedback on the plan is immediate, visual, interactive and intuitive. This not only allows the planner to build up better situation awareness himself, but will also allow him to better communicate about the plan to other stakeholders inside and outside the terminal in order to create shared situation awareness.

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As opposed to earlier research approaches where the only decision support offered are finished plans that have issues in taking the uncertainty and limitations in information supply into account, this approach enables a planner to learn and adapt best practices for planning. Planners can try out and compare various options in an environment that is completely linked to other sources of information, but produces no effect on any live system when the planner is still experimenting. This means that the planner retains total control of the situation.

Next to being able to offer support in a live setting, the tool can also be used in a microgame where a number of fixed scenarios can be tried that are linked to the planners past or future environment. In that way, decision support not just deals with the current decisions. It can also be used to evaluate past decisions, or practice for future situations.

Finally, the prototype offers avenues to implement more hard systems approaches, while still retaining the advantages of an interactive tool. One possible example is the use of statistical forecasting techniques that can predict yard states several days ahead, thus providing a clearer picture on possible discharge locations. Another example is to build an optimizer that has the ability to generate several alternative plans that are ‘good’, but still significantly different. This would provide the planner with solid, mathematics-driven advice, while at the same time preventing him from developing a tunnel vision when it comes to the generation of alternatives. In these ways, the tool can act as a platform that serves as a bridging intermediary between the planner’s world view and planning approach, and hard mathematics-driven decision support.

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Annex 4E. Training games developed earlier at TU Delft

At TU Delft, several training games have already been developed for topics that are close to the SALOMO project. This means we can build upon the experience that has already been gathered, and the complex issue of ‘serious game’ development can be tackled in an more effective way. Three examples of games will be briefly introduced below. More information about these, and other, games that have been researched in TU Delft’s serious gaming projects, can be found at http://cps.tbm.tudelft.nl/

1. The Supervisor safety training game

Supervisor is a serious game which allows you to play the role of a supervisor on a drilling site. You are expected to handle hazardous situations, watch you personnel and take care of health safety and environment requirements. This demonstrator shows the potential of simulations combined with gaming technology. You fulfill tasks which lead to “good” or “bad” supervision.

The enabled site is modeled after the Simwell training facility in Schoonebeek, The Netherlands. Supervisor is a proof-of-concept built in close cooperation by Shell and Delft University of Technology. In the past few years Shell learning organization was confronted with companies who could provide serious gaming solutions. Serious gaming involves the use of concepts and technologies derived from (computer) entertainment games for non-entertainment purposes such as for learning, policy and decision-making.

The purpose of this proof-of-concept is to demonstrate and enhance the feasibility and credibility of serious gaming technology and concepts for Shell learning, training and management activities. Supervisor has been developed by the in-house production team, the Gamingstreet. The game uses the Unreal 3 engine, normally used in blockbuster entertainment games, providing the possibility to create a near realistic experience.It was developed with a modular approach in mind, meaning that it should be able to create new scenarios in an easy way.

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In one scenario, the supervisor trainee should know how to recognize defects, protocol violation and know how to react in hazardous situations. During the game session, player actions are being logged on a webserver. After completing the scenario all logging results can be used by the game facilitator to have an evaluation with the trainee.

2. Global Supply Chain Game

The Global Supply Chain Game (S.P.A. van Houten, A suite for developing and using business games: supporting supply chain business games in a distributed context, PhD Thesis, TU Delft, 2007), provides a realistic setting in which students and managers can experience global supply chain management. The web-based system allows distributed, real-time gaming with a large number of participants playing from different locations anywhere in the world.

The game content and settings can easily be adapted by the instructor-trainer for different Supply Chain conditions and teaching objectives.

The Global Supply Chain system has been developed jointly by TU-Delft (faculty of TPM, dept. of systems engineering) and the University of Maryland (R.H. Smith School of Business, Supply Chain Management Center). For more information visit the Global Supply Chain game website: http://www.gscg.org.

3. Simport MV2

SimPort-MV2 is a computer-supported multi-player simulation game that mimics the real processes involved in planning, equipping and exploiting the Second Maasvlakte (MV2) in the Port of Rotterdam, the Netherlands. It is described in detail in Bekebrede (2010).

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See (Bekebrede, G., Experiencing Complexity: A gaming approach for understanding infrastructure systems. PhD Thesis, TU Delft, 2010) for more details.

SimPort-MV2 is a game about the extension of the Port of Rotterdam with a new, reclaimed area, the Second Maasvlakte. The game mimics the real processes involved in planning, equipping and exploiting the Second Maasvlakte and is based on real-life data.

SimPort-MV2 is a multiplayer simulation game in which participants gain insight in the consequences and effects of choices within long-term strategies. Participants tackle different aspects of managing a complex project as they are confronted by time pressure and seemingly conflicting interests. Whether the participants will be able to stick to their chosen strategies throughout the game is a decisive factor for eventual success. Pictures below show teams from the Port of Rotterdam play the SimPort-MV2 game as a training tool for future decision making.

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Annex 4F. Example Automatically Generated 3D-model of a Container Terminal

The research of Michele Fumarola (Multiple Worlds - A multi-actor simulation-based design method for logistics systems, PhD Thesis, 2011, to appear) describes the automatic generation of 3D-environments of container terminal simulation models from CAD drawings, and a repository of equipment parameters and external data. Below, two screenshots are shown of the resulting models, that can be used for situational awareness, training, and collaborative decision support. All software and knowledge from Fumarola’s project is available to the SALOMO team.

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Annex 4G. TBA’s CONTROLS for testing operations in dynamic situations

CONTROLS Emulation ToolTBA has developed a methodology using advanced simulation models to test a TOS (Terminal Operating System) before it is actually deployed. This approach is called “emulation”. TBA’s CONTROLS (CONtainer TeRminal Optimised Logistics Simulation) is an innovative emulation tool. It is designed for the testing and tuning of control software, such as Terminal Operating Systems, as well as for training TOS operators. Emulation is realised by linking the physical computer hosting the TOS to another computer. The second computer runs a simulation model of the real terminal that comprises all relevant terminal processes. Using the identical protocols used for communicating between the control software and the vehicles that this software is controlling, the TOS thinks it controls the real system rather than a mere model of it. The TOS operator, i.e. the yard planner, the dispatcher, or the vessel planner, operates the normal user interface of the TOS, and can perform work as if controlling an actual operation. In this way, tests are as realistic as possible. The simulation model of terminal operations is comprehensive and includes regular as well as special operations such as reefer handling, empty handling, traffic to customs inspection or the CFS, and so on.

CONTROLS has three different objectives: Testing and validating the TOS functionality. It ensures error-free operations by

extensively assessing complex conditions before going live. Tuning the TOS parameter settings (yard and equipment control settings) in order

to achieve the best possible performance. Training TOS operators without hindering live operations and preparing them for

all kinds of atypical situations.

The gained experience for the last two objectives is especially important for the SALOMO project, as we look at improving performance under uncertainty in controlled environments, and to provide training tools that are based on simulations, and provide an experience that is as realistic as possible.

The architecture of the CONTROLS tool will prove to be very useful to apply in the SALOMO project. TBA will make CONTROLS available, so universities and partners can build on the knowledge gained, and use it in the decision support and training challenges.

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Annex 4H. Background on learning theory from Open University CELSTEC

The SALOMO project will base its data input and visualization strategies for the decision support tools and training games on recent theories from computer-human interaction (CHI) and learning. Below, three key areas are briefly introduced: awareness, augmented reality, and contextual learning support.

Awareness

For mobile and ubiquitous learning, adaptivity and awareness are considered as key concepts especially for informal learning support [1]. Awareness is a concept that can also be utilized to acquire relevant information for the design of Ambient Learning Displays within ubiquitous learning environments. In doing so learners can be kept continuously aware about the environment he is proactive in as well as the available resources matching the learning activity. Based on current CSCW and CSCL research social, task, concept, and workspace awareness have been identified for ubiquitous learning environments [2, 3]; completed by knowledge awareness “for inducing collaboration in a shared knowledge space” and context awareness as crucial “to provide the right information to the right person at the right time and the right place with the right form” [4].

In order to present the acquired information in context an appropriate model is needed that can be used to process and transfer this information in the next step. The Ambient Information Channels model allows the description of contextual learning support patterns [5]. The model is based on four infrastructure layers encapsulating the sensor functionality, the informational aggregation, the instructional logic, as well as the visualization and interaction of a context-aware system. The sensor layer collects and handles all sensor information while the aggregation layer combines this information in a meaningful way, which is then used by the control layer to enrich the entities involved in the learning process. The indicator layer finally describes the user interface providing feedback to the user and enabling the interaction with the system.

Permanency, accessibility, immediacy, interactivity, situatedness, and adaptability have been identified as the main characteristics for ubiquitous learning embedded in our daily life (Ogata & Yano, 2004).

Permanency: Learners never lose their work unless it is purposefully deleted. In addition, all the learning processes are recorded continuously every day.

Accessibility: Learners have access to their documents, data, or videos from anywhere. That information is provided based on their requests. Therefore, the learning involved is selfdirected.

Immediacy: Wherever learners are, they can get any information immediately. Thus, learners can solve problems quickly. Otherwise, the learner can record the question and look for the answer later.

Interactivity: Learners can interact with experts, teachers, or peers in the form of synchronous or asynchronous communication. Hence, the experts are more reachable and knowledge becomes more available.

Situatedness: The learning could be embedded in our daily life. The problems encountered as well as the knowledge required are all presented in their natural and authentic forms. This helps learners notice the features of problem situations that make particular actions relevant.

Adaptability: Learners can get the right information at the right place in the right way.

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References

[1] Syvanen, A., Beale, R., Sharples, M., Ahonen, M., & Lonsdale, P. (2005). Supporting Pervasive Learning Environments: Adaptability and Context Awareness in Mobile Learning. In IEEE International Workshop on Wireless and Mobile Technologies in Education, 251-253. IEEE.

[2] Goldman, S. (1992). Computer Resources for Supporting Student Conversations about Science Concepts. ACM SIGCUE Outlook, 21(3), 4-7.

[3] Gutwin, C., & Greenberg, S. (2002). A Descriptive Framework of Workspace Awareness for Real-Time Groupware. Computer Supported Cooperative Work, 11(3).

[4] Ogata, H. (2009). Assisting Awareness in Ubiquitous Learning. In Proceedings of the IADIS Mobile Learning 2009, 21-27. IADIS.

[5] Specht, M. (2009). Learning in a Technology Enhanced World. Maastricht, The Netherlands: OCÉ.

Augmented reality and human perception

Specht (2009) describes a generic model for ubiquitous learning and synchronizing real-world environments with augmentation media and media channels. In the Ambient Information Channel Enrichment (AICHE) model, five parameters of context are used to synchronize and augment the user’s context with information and services. These five high-level categories of contextual parameters are location, time, environment, relations, and ID. Furthermore, the role of sensors and sensor information is defined as essential to connect media and real world objects for situated learning experiences and the support for reflection in action and about action (Schön, 1983). Mobile devices today typically come with a range of basic sensors. Through processing and aggregation of the raw sensor data, higher-level sensors and semantic classification of raw sensor data can be implemented. The AICHE model defines four processes by which sensor data can be a) aggregated; and b) used for enrichment of physical artifacts and metadata for media channels; c) media channels, artifacts, and users with contextual metadata are synchronized, and d) synchronized information channels are framed for metacognitive learning processes.

Human perception, awareness, knowledge acquisition, and learning can be enhanced by such augmentations in several ways.

a) Augmented Perception: Sensor systems can measure phenomena outside the human perception scope and these can be visualized for humans. The display of this sensor data can be done in a variety of ways as sensor audification, visualisation, or all other components of multimodal human-computer interfaces.

b) Augmented Simulation of not perceiveable complex phenomena: Real-time data from different sources can be aggregated and integrated in the HCI for understanding complex phenomena based on observation and simulation data.

c) Augmented Reflection: Sensor systems can record real time data and provide it for later analysis and reflection to the individual.

(Mobile) Augmented Reality can be applied in various educational domains. It can help learners to gain a deeper understanding, experience embedded learning content in real world overlays, or explore content driven by their current situation or environmental context. Most prominent examples support exploration of the physical environment with different topics of interest, e.g. history, arts, technology, biology, astronomy, and others, or by enriching artifacts in the physical environment with AR techniques.

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References

Hamilton, K. (2010) Augmented Reality in Education. Retrieved online at http://wik.ed.uiuc.edu/index.php/Augmented_Reality_in_Education

Ternier, S., Specht, M., De Vries, F., De Jong, T., & Börner, D. (2010). ‘Mobile Augmented Reality’ voor het Onderwijs. Surfnet & Kennisnet, Innovatieprogramma.http://hdl.handle.net/1820/2431

Contextual Learning Support

New technologies off a variety of possibilities to contextualise learning experiences and on the one hand adapt them to individual situations and learning needs as also make them more authentic and relevant learning experiences. Mobile learning support and embedding learning activities in authentic contexts becomes more and more important and has proven in the last years as an efficient method for supporting sustainable and enriched learning experiences in a variety of educational sectors ranging from school field trips to life-long learning support. Social software as a tool for creating content in context has established even in the corporate information landscape as a new mean of knowledge management and bottom up integration of the “wisdom of crowds”.

Ubiquitous and contextualized access to information and services enable the integration of informal and formal learning support: Mobile and ubiquitous learning technology gives new possibilities to support distributed learning networks with activities ranging from notification for awareness, content creation in context and content exchange as also reflection in and about action (Schoen, 1998). Furthermore the previous support for e-learning on a desktop computer de-contextualizing the learner from the actual community, practice environment, or working activities becomes dissolved when computers and through them learning services can be integrated in daily living and working environments. Through these technologies not only the information and services become available on-demand in a situation of practice but also the social networks and informal learning activities are integrated in a life long learning experience.

Relevant publications

de Jong, T., Specht, M., & Koper, R. (2010). A Study of Contextualised Mobile Information Delivery for Language Learning. Educational Technology & Society, 13 (3), 110–125.

Specht, M. (2009). Towards Contextualized Learning Services. In Koper, R. (Ed.). Learning Network Services for Professional Development. Springer 2009. pp 241-254

De Jong, T., Specht, M., & Koper, R. (2008). A Reference Model for Mobile Social Software for Learning. International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL). 18(1), 118-138.

De Jong, T., Specht, M., & Koper, R. (2008). Contextualised Media for Learning. Journal of Educational Technology & Society, 11(2), 41-53.

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Annex 4J. Overall project plan

WP0Project Management 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12


WP1SSA Theory Development 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12


WP2SSA Tool Development 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12


WP3SSA Tool Evaluation with Partners 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12


WP4SSA Tool Evaluation with User Group 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12


WP5Training Tool Development & Test 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12


WP6Dissemination 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12









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