SIMATIC IT Reporting Framework v2.1 SIMATIC IT ... · The term Manufacturing Execution Systems...

SIMATIC IT Reporting Framework v2.1 – SIMATIC IT Intelligence Suite v2.1 issued by: Siemens. © Siemens AG 2013. All rights reserved.

www.siemens.com

March 2013

SIMATIC IT Reporting Framework v2.1SIMATIC IT Intelligence Suite v2.1

Functional Overview

Siemens. © Siemens AG 2013. All rights reserved.

Functional Overview | SIMATIC IT Intelligence Suite v2.1 | March2013 2

Contents

1 ........................................................................................ Introduction 5

1.1 ........................................................... MES and Production Modeling 5

1.2 ................................................................ Standards and Compliance 5

1.2.1 ......................................................................... ISA-95 Compliance 5

1.2.2 ............................................................. 21 CFR Part 11 Compliance 6

2 ........................................ Why focus on MES and Production Modeling? 7

2.1 ................................................................................. Business issues 7

2.2 .............................................................................. Production issues 8

2.3 ........................................................................................... IT issues 9

3 ........................................................................... How you can succeed 10

3.1 ........................................................................ The SIMATIC IT model 10

3.2 .............................................................................. Business Benefits 10

3.3 ........................................................................... Production Benefits 11

3.4 ........................................................................................ IT Benefits 11

3.5 ............................................................................... Total Integration 11

4 ............................ SIMATIC IT Reporting Framework and Intelligent Suite 12

4.1 ...................................................... What is the Business Intelligence? 12

4.2 ............................................. What is the Manufacturing Intelligence? 12

4.3 ............................................................ SIMATIC IT for Manufactoring 13

4.4 .............................................. Data Integration and Contextualization 14

4.5 ............................................................................... What is supplied 14

4.6 ........................................................SIMATIC IT Reporting Framework 14

4.7 .............................................................. SIMATIC IT Intelligence Suite 15

4.8 ................................................................................. Different layers 15

4.8.1 ............................................................................ Production Layer 15



4.8.2 ............................................................................. Reporting Layer 16

4.8.3 ................................................................................ Analysis Layer 17

4.8.4 ......................................................................... Connectivity Layer 18

4.9 ...................................................... What is Manufactoring Data Store 18

4.10 ............................................. Multiplant and MultiLanguage support 19

4.11 ........................... Handling SIMATIC IT MES Database Customizations 19

4.12 .................................... Handling SIMATIC IT MES Database Deletions 19

4.13 ....................................................... Manufacturing Data Warehouse 19

4.14 ................................................................ Manufacturing Data Mart 19

4.15 ....................................................................... Manufacturing Cube 20

4.15.1 .......................................................... Online Analytical Processing 20

4.15.2 ................................................................................ Data Storage 21

4.15.3 ........................................................ Multidimensional Expressions 22

4.15.4 .................................................. Key Performance Indicators (KPIs) 22

4.16 ................................................................................................ ETL 22

4.16.1 ............................................................................. Scheduling ETL 23

4.16.2 .................................................................................. Custom ETL 23

4.16.3 ...................................................................................... Recovery 23

4.17 ................................................................................... User Models 24

4.17.1 .................................................................................. Data Model 24

4.17.2 ............................................................................. Business Model 24

4.17.3 ........................................................................... Analytical Model 25

4.18 ................................................................ Engineering Environment 25

4.18.1 ............................Main Functionalities of Engineering Environment 25

5 ................................................................ Major features in version 2.1 26

5.1 ........................................................................................... Usability 26

5.1.1 ................................................................. CAB Reporting Manager 26



5.1.2 ........................................................................... Smart navigation 26

5.1.3 ....................................................................... Smart configuration 26

5.1.4 ............................. Scorecard “Excel like” line hierarchical expansion 26

5.1.5 ................ Import export of Reporting Framework CO Configurations 26

5.2 ........................................................................... New functionalities 27

5.2.1 ........ Multilanguage data read from SIT databases and stored in MDS 27

5.2.2 ................... Historian Custom Objects available in MDS for reporting 27

5.2.3 ....................... Compliance Services Custom Data Structures support 27

5.2.4 ............................................................... OEE Custom field support 27

5.2.5 .................................. New SHC / OEE feature for fiscal year support 27

5.2.6 .......................... Report printing with counters and callback support 27



1 Introduction

1.1 MES and Production Modeling In the early Nineties, industries acknowledged the need for a layer to integrate and link Business Systems with Control Systems. The term Manufacturing Execution Systems (MES) has been used from the start to specify all those functions and products that satisfy this need. Initially, MES indicated a “gray” area that was a hodgepodge of almost every application or product that could not be clearly assigned to either the Business System or the Control System layer. Most of these products were spinoffs of applications developed by a System Integrator for a particular Customer and were generally focused on a very specific area (i.e. scheduling, laboratory, quality, tracking…). After some time, international organizations addressed the need for a clearer definition of MES: MESA (Manu-facturing Enterprise Solutions Association) and, as a consequence, ISA (Instrumentation System and Automa-tion Society) later developed models that describe these levels and seek to standardize them.

Under the pressure of new business-driving forces that have been emerging in recent decades, Manufacturing Plants continue to play a major role. The globalization of both companies and production processes makes it necessary to create new models. Manufacturing is not a process that can be completed by a single self-enclosed entity, but extends beyond the bounds of the Plant, the Country and the Enterprise. Therefore, MES cannot act simply as an interface between Business and Process layers, but requires a substan-tial number of functions that are crucial to a Company’s success. Rather than remaining distinct from one an-other, connected solely by a data exchange layer, these functions need to be coordinated, in adherence to the Business and Production strategy. ISA-95 documents point this out very clearly, describing the MES process in terms of both data and interaction between functions (e.g. Order Dispatching, Resource Management). The result is a new approach to MES, based on an architecture that allows describing Business Processes that orchestrate functionalities provided by a set of specialized and affordable Components. At the same time, this orchestration must also involve the Automation and Control level, thereby making both MES and Control part of the same Collaborative Production Management system.

1.2 Standards and Compliance

1.2.1 ISA-95 Compliance ISA-95 is acknowledged as the most authoritative standard for MES applications. Not only Market Analysts such as AMR (www.amrresearch.com) and ARC (www.arcweb.com) confirm this, but also several major vendors adopt this standard. In addition to Siemens, we can find, for example, SAP and Microsoft. Siemens works in close conjunction with ISA and was the very first MES vendor to offer a comprehensive prod-uct implementing the ISA-95 standard. This translates into standardized terminology, concepts and models for integrating manufacturing operations functions with enterprise functions. Such standardization is achieved



with ISA-95, which defines the functional view of an enterprise, allowing a simple generic model of work activi-ties to be applied to the main areas of manufacturing. As a member of the ISA-95 Committee, Siemens actively contributes to the further development of this standard.

Complying with ISA-95 makes it possible to reap some important benefits: in particular, for what concerns de-fining the hierarchical model of the MES solution, which simplifies developing solutions that are both standard yet flexible, while still satisfying customer requirements in full.

1.2.2. 21 CFR Part 11 Compliance

In order to address regulated industries (such as Pharma), SIMATIC IT provides a built-in service (the instal-lation of which is optional) depending on the requirements. This service (SIMATIC IT Compliance Service) provides support for the 21 CFR Part 11 requirements for Audit Trail and Electronic Signature. Several in-stallations in regulated industries successfully proved SIMATIC IT support in certifying a solution.



2 Why focus on MES and Production Modeling? On a daily basis, a variety of figures in charge of different activities face problems that involve manufactur-ing systems. Implementing MES and deploying the right production model can provide a solution to many of these issues. In broad outline, the problems encountered concern: S

Business

Production

IT

2.1 Business issues

Do you want to increase the overall efficiency of your supply chain?

Supply-chain efficiency is strongly affected by how the Business level (ERP) and the Shop Floor (Control) interact. MES represents the go-between, which, when streamlined and efficient, contributes to a better Supply Chain.

Is your system able to react quickly to new conditions and new market requirements?

In today’s world of manufacturing, the ability to adapt to new operational requirements (i.e. changes in product specifications, quality procedures…) and environmental conditions (i.e. introduction of new standards…) is paramount to success. If your system is ready to meet these challenges, the reward may be a significant increase in your competitiveness, as well as impressive savings in terms of costs.

Is your production process standardized across all plants?

Guaranteeing uniform, consistent production procedures is a key issue in today's business. If this is lacking, then the result may be uneven quality of your product from one facility to another. Control System and Business System cannot solve the problem, as a structured and modeled environment is required in order to seamlessly coordinate the production process, also in different contexts (e.g. different hardware and software installation bases).

Are you ready for new regulations?

Some established standards and regulations, such as FDA, already exist to guarantee high-quality prod-ucts. However, new regulations, as well as the need for exhaustive material traceability, are affecting manufacturing procedures substantially. MES can help you achieve compliancy with these regulations and maintain full accountability of materials.

Would you like your business to be more customer-oriented?

Standard monolithic applications often represent a barrier to implementing an efficient system that can adapt and satisfy ever-changing requirements from both the customer and the market. In view of the growing demands posed by Customers, MES can make your system much more flexible and adaptable.



2.2 Production issues

Do you handle reworks and scraps properly? Do you track how your materials are used with preci-sion?

Typically, reworks and scraps cannot be handled by control systems. Without appropriate management, excessive waste or uncontrolled material tracking can also affect the quality of your final product. In addi-tion, overall material tracking throughout the production process is now a crucial factor for both account-ing and the correct evaluation of production costs. S

Do you need to increase visibility of your production process? Is your system able to provide Produc-tion-related KPIs and advanced reporting?

To fully comprehend how your plant is performing, you need a system that can generate production re-porting correlating process-control specific data with production-related data (i.e. order number, lots, personnel, materials…) to facilitate troubleshooting and analyzing performance problems. MES can heighten visibility in the production process, creating the right conditions to promote improvement and increase your manufacturing system’s efficiency.

Do you need to raise your level of quality? Are you able to pinpoint contaminated lots or out-of-spec finished-goods lots? Are you able to backtrack your production with accuracy?

If not, you might be unable to address specific issues regarding the quality of your product. You may also be unable to respond to customer complaints appropriately or organize product recalls promptly. An effi-cient MES system can provide complete genealogy, being able to track materials throughout the entire production process. It also follows all material transformations with precision until the final product is produced and delivered to the final customer.

Does your system react efficiently to production problems? Do you re-schedule your plant activities properly?

What if something goes wrong on the shop floor? Efficient management of failures and downtimes is a must. Often, several systems need to be involved in order to solve the problem (maintenance must be informed, rescheduling is necessary, certain people must be notified as soon as possible…). Poor coordina-tion leads to using resources in an ineffective manner, ultimately raising your production costs.

Is your ERP System working with the Manufacturing Operations System efficiently?

To optimize Supply Chain efficiency, the Business Logistic System must be informed in real-time as to what is happening on the Shop Floor, especially in terms of Production Performance. This is especially useful in terms of planning, as well as both material and warehouse management.

Is your manufacturing system totally integrated?

Total integration between Process Control, MES and ERP is essential in today's business. The manufacturing system consists in the joint efforts of a variety of functions. Good integration can make a difference for attaining top-level efficiency: on the contrary, poor integration can hinder your efforts to improve plant performance.



2.3 IT issues

Is your System properly integrated and synchronized? Are there so many links between applications that communication is difficult? Are your IT maintenance costs too high?

A myriad of links between your Software Packages greatly increases the complexity of the manufacturing system. In turn, costs for IT maintenance and program modification become staggering. This is mainly due to the lack of coordination and flexibility of the majority of manufacturing applications. The modeling approach can effectively simplify integration and actively coordinate the interaction and the flow of infor-mation between different applications on site.

Is implementation too expensive? Do you frequently assess projects as falling in the "high-risk" cate-gory?

Being able to employ reusable solutions creates the conditions for streamlining and speeding up project implementations. Total ownership costs can be cut dramatically, thanks to efficient software reusability.

Does sharing your know-how represent an obstacle? Would you like to re-use your expertise and your software effortlessly?

Efficient reusability of software is key to effective cost saving. Being able to "code" the expertise permits the rapid transfer of know-how between users, which is usually not feasible with standard applications. Without a modeling environment to help you define business procedures, focusing on the production pro-cess rather than specific IT issues, the understanding of complex manufacturing applications is rather difficult, making it virtually impossible to modify or reutilize code.

Do you need a more streamlined environment for monitoring and troubleshooting?

Typically, a production system is a complex integration of software applications and physical devices. Pin-pointing problems and debugging are serious issues that require a great deal of effort and ultimately cost money. If you are able to model and run programs and business procedures from a single environment involving several systems, then extended monitoring and troubleshooting become more than just a possi-bility.

Is it difficult for you to maintain your team’s technological skills at top level? Are the costs to train your staff in line with state-of-the-art technology excessive?

Applications are very often numerous and customized to satisfy specific needs. As a result, frequently, the person with the most know-how is used to develop and maintain these applications. Such competence is very difficult to maintain, as well as very expensive. By adopting SIMATIC IT, which covers all functionali-ties in an integrated and homogenous environment, complex manufacturing systems can be implemented with ease, making the tasks involved viable even for those users who possess normal skills.



3 How you can succeed

3.1 The SIMATIC IT model

Today, increasing competitiveness is mandatory for manufacturing companies.

MES is crucial to guaranteeing overall component integration, ensuring maximum quality and production efficiency across all global facilities. Siemens was one of the first to understand the challenges facing manufacturing industries, offering SIMATIC IT as a solution.

SIMATIC IT is a collection of highly-integrated components, designed to integrate the systems within each factory, standardize production across the entire enterprise and keep manufacturing processes aligned with supply-chain activity.

SIMATIC IT provides a high-level environment that enables the definition of the manufacturing processes and operating procedures, synchronizing and coordinating the functions provided by its single compo-nents. These functions will carry out what is required to manage production, such as order management, material management, KPI calculation and so on.

SIMATIC IT Production Suite has been developed to provide cross-industry functions. Through layered li-braries, objects defined in SIMATIC IT Production Suite can be more and more specialized in order to ad-dress specific industry segments.

A dedicated team at Siemens provides pre-built objects and examples ready for use in actual projects. They can be used either “as is”, or slightly modified to fit the context where they will be employed. These pre-built objects are part of SIMATIC IT Cross Industry Libraries.

3.2 Business Benefits

SIMATIC IT Production Suite fills the gap between Business Logistic Systems (typically, ERPs) and Control Systems, providing the conditions for increasing overall supply-chain efficiency. The unique approach of



SIMATIC IT allows manufacturing systems to have a native flexibility that gives users the possibility to easi-ly adapt and modify the business process to new requirements and business drivers. SIMATIC IT Production Suite allows manufacturers to model their own business to be much more cus-

tomer-oriented and ready to satisfy any on-the-fly requirements from the market. SIMATIC IT Production Suite has also been designed to facilitate application roll-out to several plants,

thus being extremely cost-effective in multi-site contexts. SIMATIC IT Production Suite effectively helps users to comply with existing regulations.

3.3 Production Benefits

SIMATIC IT Production Suite offers a set of modules able to cover the MES core requirements in any manu-facturing context. By modeling and defining production procedures, SIMATIC IT Production Suite effective-ly increases visibility on the entire production process. Tracking and tracing of materials can be configured in order to match the actual process with preci-

sion. Having a clear view of material usage makes it possible to reduce stock, analyze production costs in

greater detail and manage scraps and reworks in an efficient manner. SIMATIC IT Production Suite can rebuild the complete material genealogy (both backward and for-

ward). SIMATIC IT coordinates and integrates a variety of systems, each with its own scope, thereby providing

true added value to the production system as a whole.

3.4 IT Benefits

The basic approach of SIMATIC IT makes it possible to model business rules in a graphical way so as to represent the interactions and the expected flow of information among different software components (including those that are not part of SIMATIC IT Production Suite). SIMATIC IT Libraries, classes and inher-itance mechanisms create the conditions for an effortless rollout and reutilization of SIMATIC IT Production Suite applications. SIMATIC IT Production Suite permits users to focus on process issues, rather than IT issues. In SIMATIC IT Production Suite, technological aspects are transparent to the user, who, as a result, requires

fewer skills than what is normally required to develop standard MES implementations. Costs for maintenance and application modification are pared to the bone. Siemens partners can create their own SIMATIC IT Libraries, coding their own expertise and making it easi-

ly reusable, thus dramatically reducing the average development time for MES projects.

3.5 Total Integration

Siemens is committed to providing complete solutions to their customers, from field devices to MES.

This is part of the TIA concept (Total Integrated Automation). What Siemens offers can satisfy a full range of requirements for automation in the manufacturing market. Its native integration provides considerable advantages.

Such an ample range of totally integrated products leads to faster implementation and effective engineer-ing, creating the conditions to attain greater productivity in the company’s workflow.

In the Siemens TIA strategy, SIMATIC IT is the MES player. While maintaining its capability of integrating third-party software and components, SIMATIC IT has an active role in the TIA concept.

In this way, SIMATIC IT benefits from the integration with the rest of Siemens’s products, supplying a vast range of pre-configured objects ready to be instantiated and used without requiring any additional engi-neering effort. As a result, both rapid project implementation and native integration throughout the man-ufacturing system are ensured.



4 SIMATIC IT Reporting Framework and Intelligent Suite

4.1 What is the Business Intelligence?

Managers need to make quick and effective decisions, and to do this they need the right information at the right time, but they are often overwhelmed by data, which is scattered across different sources. For quick and effective decision-making, data must be:

• integrated into one place (a data warehouse).

• turned into clear and actionable information.

Business Intelligence systems typically supply dedicated client-side tools, which make easier the navigation between data and make OLAP analysis easy for non-technical users. The main features of a BI system are:

• Dashboards, providing an at-a-glance overview of key business data.

• Scorecards, comparing results against a target simply and effectively.

4.2 What is the Manufacturing Intelligence?

In today’s economic environment manufacturers are under constant pressure to optimize plant perfor-mance and consequently to reduce operating costs.

To accomplish this objective many manufacturers have installed Manufacturing Execution Systems (MES) that have proven to streamline production processes and facilitate the flow of information between the shop-floor and the rest of the enterprise.

In today’s economic environment manufacturers are under constant pressure to optimize plant perfor-mance and consequently to reduce operating costs.

To accomplish this objective many manufacturers have installed Manufacturing Execution Systems (MES) that have proven to streamline production processes and facilitate the flow of information between the shop-floor and the rest of the enterprise.

As a result, every day Manufacturing Execution Systems process a very large amount of data. But, typically, this data is difficult to interpret, and must be accessed and transformed thus becoming understandable and actionable to users in a format they can use to optimize operations.

Manufacturing Intelligence transforms plant floor data into key performance indicators and metrics that managers use to monitor and improve the manufacturing operations performance.

In this way, Manufacturing Intelligence enables manufacturers to close the performance loop by gaining visibility across the production, inventory, assets and quality management aspects of manufacturing oper-ations.

An Enterprise Manufacturing Intelligence system enables close-loop performance management by:

• Aggregating data gathered from many sources.

• Contextualizing the data through a data model that will help users find what they need.

• Providing appropriate analytics that enable users to analyze data across sources and especially across production sites.

• Providing tools to create visual summaries of the data to alert decision makers and call attention to the most important information of the moment.

• Automating the transfer of the collected data from the plant-floor up to business systems such as SAP.



The main benefits of Manufacturing Intelligence are:

• More Intelligence; Integration of analytical and visualization tools makes possible to monitor data in real time and inform appropriate decision-makers in case of non-conforming incident.

• Less Variability; Using EMI systems, manufacturers can better understand sources of variability in their production process and operate to improve process stability, plant capacity, and quality compliance.

• Less Costs; Reducing variability in the production process manufacturers can decrease operating costs.

4.3 SIMATIC IT for Manufacturing

SIMATIC IT includes a set of products designed to give manufacturing operators, management, and execu-tives increased visibility into plant information. This enables them to make informed decisions, thereby improving performance throughout the plant.

Reporting Framework and Intelligence Suite are complementary to the Production and R&D Suites. Through data extraction, transformation, and contextualization with data from the SIMATIC IT suites (as well as third party data), these products turn data produced by these suites into information. In turn, they allow this information to be visualized and analyzed through the use of dashboards, reports, and analytic tools.

Generally speaking, the Intelligence Suite is about turning data into information and knowledge, allowing for better decision-making in a near real-time environment. Currently, data (such as orders, inventory, production, and so forth) is collected and analyzed for the purpose of investigating historical conditions. The results of such an investigation is then used to improve productivity, assess the current situation, and predict future needs.

Reporting Framework and Intelligence Suite help users in creating knowledge from a vast quantity of in-formation, getting the right data, and putting it in the hands of the right user at the right time with the aim to support the decision-making process.



The main goals of these products are separated into three main areas:

• Providing data integration and contextualization.

• Helping in using information to make as real-time as possible decision.

• Analyzing information.

4.4 Data Integration and Contextualization

Reporting Framework and Intelligence Suite allow the integration and contextualization of data, which is gathered from the SIMATIC IT components as well as the third party data sources that are scattered throughout the plant. All MES production data is collected with a low-to-medium latency, which can differ according to the specific context (such as discrete, process, batch and so forth). This provides information, through the use of reports, dashboards, and analytic tools, that allows the user to react to situations with-in the manufacturing cycle in a timely manner.

This data is then put into the context of business or enterprise data, supply chain, and production events using 3 main repositories:

• Manufacturing Data Store (MDS) – a staging area, where data is collected, denormalized and related to context.

Manufacturing Data Mart (MDM) – a set of entities as dimensions; linked with specific fact tables that allow different types of data analysis.

• Manufacturing Data Warehouse (MDW) - a set of strictly connected entities which are useful to create rapid prototyping reports.

All these repositories are able to capture, transform, unify, and contextualize data for use in reporting, decision support, and analysis.

4.5 What is supplied

The Intelligence Suite provides a rich set of information to perform advanced analytics, such as Online Analytical Processing. Pre-canned dimensions help to gain the knowledge by which decisions can be made to help optimize productivity throughout the plant.

Data contained in databases can be queried in different ways according to the user needs. For a manager for example, can be useful to view data either by plant or by product in order to better analyze data.

This approach to data is typical of data structures called OLAP Cubes, which typically contain the results of all possible combinations of aggregations. Each of these result is called a measure. The categories used for the aggregations (in our example, product and plant) are called dimensions, and each item in the dimen-sion is called a member.

Cubes and dimensions are managed by multi-dimensional databases.

4.6 SIMATIC IT Reporting Framework

SIMATIC IT Reporting Framework is based on Microsoft SQL Server platform, with its data management, reporting and analysis technologies. It extends the functionalities of SIMATIC IT Production Suite providing a data management infrastructure and a range of tools to build reporting solutions on SIMATIC IT.

MES relevant information is first collected into a Staging Area to:



• maintain the historical information.

• consolidate and cleanse data.

Consequently information is exposed for reporting purposes.

A complete set of out-of-the-box connectors is provided to collect and refresh data from SIMATIC IT pro-duction databases. The user can then configure when data in the Staging Area shall be refreshed using the Reporting Framework ETL scheduling environment.

4.7 SIMATIC IT Intelligence Suite

SIMATIC IT Intelligence Suite is based on Microsoft SQL Server and Analysis Services platform, and it ex-tends the functionalities of SIMATIC IT Reporting Framework by providing Manufacturing Intelligence func-tionalities through a data infrastructure and a range of tools that allow the user to perform analysis on KPI indicators.

MES relevant information are collected and stored in a dedicated data structure – generally called OLAP Cube – that is optimized for analysis activities.

The product can be extended with a set of User Interfaces that can be set-up by users of any type, allowing them to easily analyze KPIs related to their domain of responsibility: the Manufacturing Scorecard compo-nent.

4.8 Different layers

The whole package can be divided into different functional layers:

1) Production Layer 2) Reporting Layer 3) Analysis Layer 4) Connectivity Layer

4.8.1 Production Layer

The Production Layer includes the possible data sources for SIMATIC IT Reporting Framework and SIMATIC IT Intelligence Suite.

SIMATIC IT Production Suite is the main data source, which provides the following MES relevant infor-mation:

• ISA 95 entities (for example Equipment model, Orders, Materials, PPRs, Shift Calendars, Personnel)

• Historical tags

• OEE and SPC data

• Compliance Services data

Additional data sources are:

• Third-Party MES systems

• SIMATIC IT Libraries



4.8.2 Reporting Layer

The Reporting Layer provides a data management infrastructure to support reporting functionalities:

• Staging Area, a temporary location where data from Production Layer is collected and stored. It is mainly required to: - Harmonize, consolidate and cleanse data

- Maintain the historical information for LTA (Long Term Archiving)

In SIMATIC IT Reporting Framework the Staging Area is called MDS (Manufacturing Data Store).

• Data Model, an abstraction layer that hides the complexity of data provding the user with a set of well known entities.

In SIMATIC IT Reporting Framework the Data Model consists of a set of views implemented on top of both SIMATIC IT databases and MDS.

• Business Model, exposes the ISA 95 business entities that can be used to create business reports: - In-formation is exposed using a Business Oriented Data Model

- Production data that does not add a value to the analysis is discarded

Reports are executed using the Business Model as the data source.

In SIMATIC IT Reporting Framework the Business Model is called MDW (Manufacturing Data Warehouse).

• Long Term Archiving, provides the capability to archive “old data” in separate repositories: - Maintains data available for long term archiving purposes

- Controls the Staging Area size and performances

The Reports are developed using MS SQL Server Reporting Services:

• Reports are accessed via SIMATIC IT CAB Portal and rendered as Web pages.

• Reports can be exported in common file formats (e.g. pdf, excel, csv, etc.).

• Report execution can be scheduled.



4.8.3 Analysis Layer

The Analysis Layer provides a data management infrastructure to support analysis functionalities:

• Enterprise Data Warehouse, a repository where data from multiple sites is collected and stored. It is nec-essary only in multi site scenarios.

• Manufacturing Data Mart (MDM), a multi-dimensional repository that collects, organizes, and makes data available for analysis. The purpose of this repository is to facilitate the aggregation of values against several contexts, which enables KPI analysis and advanced analytical functions.

• OLAP Cube, a data structure that allows fast analysis of data. It can also be defined as the capability of manipulating and analyzing data from multiple perspectives.

Scorecards are highly summarized views with Key Performance Indicators (KPIs) measured and scored against predefined targets, which are used to measure operational performances.



4.8.4 Connectivity Layer

Connectors are available to collect data from one layer and store them into the upper layer. They are based on Extract, Transform, and Load (ETL) packages that:

• Extract data from the SIMATIC IT S95 components and external data sources;

• Transform and validate it to fit business needs (which can include quality levels);

• Load it into the MDS, MDW or the MDM.

4.9 What is Manufactoring Data Store

From a functional perspective, the Manufacturing Data Store (MDS) is an Operational Data Store (ODS). An ODS is a type of database designed for high-performance queries on transactional data and for integrating data from multiple sources to simplify analysis and reporting.

The MDS is a relational repository that serves as the single contextual data source largely based on ISA 95 data/object models within SIMATIC IT MES and extensions to address the needs of other vertical markets such as discrete manufacturing.

This repository lifts the burden of reporting, read-only dashboards, and analytic processing from the Online Transactional Processing (OLTP) database, and allows for further contextualization and integration from external data sources. The MDS also serves as a “staging” area for data that is then loaded into the Manufacturing Data Mart.

The MDS structure is designed with the purpose of storing data retrieved from the following Production Suite Components:

• Material Manager

• Production Order Manager

• Business Process Modeler

• Product Definition Manager

• Personnel Manager

• Shift Calendar



• Plant Performance Analyzer: - Historical Tags

- EBR

• Compliance Services

• At Line Testing

• Logbook

4.10 Multiplant and MultiLanguage support

One of the most important Intelligence Suite goals is providing support for multi-plant and multi-language. This is achieved by using:

• The SITE_KEY as part of the primary key in the MDS tables and part of the alternate key in the MDM ta-bles.

• The language code as part of the primary key in MDS language tables

4.11 Handling SIMATIC IT MES Database Customizations

The SIMATIC IT databases are extensible through custom objects and custom fields or properties. Custom objects are structures that can be associated to tables; custom fields or properties are taken in the form of name/value pairs in the SIMATIC IT DBs. These structures are managed within the MDS by using the Report-ing Framework Engineering Environment1, which helps the user to extend the MDS data structure.

4.12 Handling SIMATIC IT MES Database Deletions

Because deletions are managed in the SIMATIC IT DBs, the MDS is also able to manage them. Every time a record is deleted in the SIMATIC IT DBs, information (such as the primary key and the deletion date) is stored in dedicated tables

4.13 Manufacturing Data Warehouse

The Manufacturing Data Warehouse (MDW) is a repository characterized by a ISA 95 structure, that collects most relevant business data from the Data Model.

Unlike the MDS it stores business information instead of detailed production data, thus allowing the per-sonnel responsible for plant and line operations to easily access business reports, providing constantly updated information.

Also data provided by third-party systems can be stored in MDW, using the standard ETLs provided with the Reporting Framework setup, and updating the Data Model implementation to fit the data model of new data.

4.14 Manufacturing Data Mart



The Manufacturing Data Mart (MDM) is a multi-dimensional repository that collects, organizes, and makes data available. The purpose of this repository is to facilitate the aggregation of values against several con-texts, which enables KPI reporting and advanced analytical functions such as Online Analytical Processing (OLAP).

The Manufacturing Data Mart (MDM) has the same characteristics of a Data Warehouse, but it is usually smaller and is focused on a portion of the enterprise data. In short, the Data Mart is a subset of a Data Warehouse.

The MDM is a subject-oriented, integrated, time-variant, non-volatile collection of data used to support the strategic decision-making process for the manufacturing environment.

• Subject-oriented The data in the database is organized so that all the data elements relating to the same real-world event or object are linked together. These events are usually clustered around the calculation necessary to compute KPIs.

• Integrated The database contains data from most or all of an organization's manufacturing applications, and this data is made consistent.

• Time-variant The changes to the data in the database are tracked and recorded so that reports can be produced showing changes over time.

• Non-volatile Data in the database is rarely, if ever, never over-written or deleted. Once committed, the data remains static and is read-only. It is retained for future reporting.

4.15 Manufacturing Cube

The Intelligence Suite provides the necessary information to perform sophisticated data analysis opera-tions, such as Online Analytical Processing (OLAP).

4.15.1 Online Analytical Processing

Online Analytical Processing is a category of decision support software which enables users to analyze the data that has been summarized into multidimensional views and hierarchies. The core of any OLAP system is the paradigm of cube.

A star schema, as described in the previous paragraphs, is typically the information source for the OLAP cubes. A star schema can have one or more cubes associated with it.

The most important mechanism in OLAP is the use of aggregations. Aggregations are built from the fact table by aggregating the data along the dimensions. The number of possible aggregations is determined by every possible combination of dimension granularities.

In Figure 2-11 a hypothetical cube structure is described. In particular, a cube with three dimensions and one measure is described:

• Each dimension represents a specific master data in the production process (equipment, materials, and time), and it represents a specific view.

• In an OLAP cube each cell summarizes a specific aggregated value of one or more measures. In this ex-ample only one measure is taken into account: the Production Quantity.

• The time dimension is structured as a hierarchy having two levels: the year and each quarter. In general, each dimension is represented by a hierarchical level – each dimension represents data that is hierarchical in nature.



SQL Server 2005 Analysis Services provides tools and features for OLAP which helps in designing, deploy-ing, and maintaining cubes.

An OLAP analysis, as already stated, allows to fast analyzing a huge amount of data by modeling the data following the multidimensional paradigm. This target is achieved thanks to slicing and dicing, and drill down and drill up capabilities.

The OLAP technology allows slicing and dicing the data according to the cube’s dimensions as described in Figure 2-12. This means that the data inside a cube can be analyzed using specific partial views.

The objective of slicing is to extract a slice of the original cube corresponding to a single value of a given dimension. We can analyze produced quantity by equipment, or production quantity by time or by materi-al, and so on.

The OLAP technology allows slicing and dicing the data according to the cube’s dimensions as described in Figure 2-12. This means that the data inside a cube can be analyzed using specific partial views.

The objective of slicing is to extract a slice of the original cube corresponding to a single value of a given dimension. We can analyze produced quantity by equipment, or production quantity by time or by materi-al, and so on.

4.15.2 Data Storage

An OLAP Cube can be stored in three ways:

• MOLAP – Multidimensional Online Analytical Processing

• ROLAP – Relational Online Analytical Processing

• HOLAP – Hybrid Online Analytical Processing



MOLAP is the classic storage option and it is used by SIMATIC IT Intelligence Suite. The base data, the di-mensions, and the aggregations are stored in a multidimensional Microsoft proprietary format. Aggrega-tions are pre-calculated summaries of data that improve query response time. The number of possible aggregations is determined by every possible combination of dimension granularities.

4.15.3 Multidimensional Expressions

Multidimensional Expressions, also known as MDXs, allow querying a multidimensional structure as cubes returning cell sets that contain the cube’s data.

Even if the MDX is similar to SQL syntax, it is not an extension of the SQL language and it is different in many ways. A full explanation of MDX language is out of the scope of this document

4.15.4 Key Performance Indicators (KPIs)

KPIs (Key Performance Indicators) are defined as quantifiable and strategic measurements that reflect the critical success factors of each organization. They are calculated comparing a measure against a target.

The main concepts relative to KPIs are the following:

• Key Operating Parameter (KOP), a parameter which can be used to define dynamic goals for KPIs, instead of static formulas.

• Measure, the result of possible combinations of aggregations within the OLAP Cube.

• Dimension, a category used for the aggregation within the OLAP Cube.

4.16 ETL

KPIs (Key Performance Indicators) are defined as quantifiable and strategic measurements that reflect the critical success factors of each organization. They are calculated comparing a measure against a target.

The main concepts relative to KPIs are the following:

• Key Operating Parameter (KOP), a parameter which can be used to define dynamic goals for KPIs, instead of static formulas.

• Measure, the result of possible combinations of aggregations within the OLAP Cube.

• Dimension, a category used for the aggregation within the OLAP Cube.

Reporting Framework and Intelligence Suite provide a set of canned ETL packages which are able to:

• Retrieve data from standard SIMATIC entities2 and load it in the MDS.

• Retrieve data from standard MDS entities and load it in the MDW.

• Retrieve data from standard MDS entities and load it in the MDM.

The ETL packages can be mainly divided in two main classes:

• Initial load, the first run of the ETLs load all the data available in the data source

• Incremental load, every following run of the ETLs gets only the differences from the previous run



The initial load must be run one time when the target database is empty.

The incremental load is run periodically in order to get all the changes which occur in the source database.

An incremental ETL package can be either executed on event by the Production Modeler, cyclically as a SQL Server job, or even as a one-shot process.

The frequency varies for each project and is strictly related to the frequency of data updates and the data type used by the reports.

It is strongly suggested to avoid performing incremental loads with a frequency lower that 15 minutes and greater than 24 hours.

4.16.1 Scheduling ETL

As previously stated, an ETL process can be either Initial or Incremental. Even if incremental processes can be run as one-shot events, it would make more sense to schedule the process. An incremental ETL can be scheduled by:

• Event - ETL is executed from the Production Modeler.

• Time - ETL is scheduled periodically by using the SQL Server Agent or other job scheduling tool (such as the Engineering Environment).

4.16.2 Custom ETL

Each ETL package is basically constituted of two workflows:

• Control flow

• Data flow

As the name suggests, the Control Flow is the primary area for dictating the flow of processing within a package. It contains a set of tasks used as containers which hold other tasks, for example, the For Loop Container or Execute Package Task. One of the most important tasks used in the Control Flow area is the Data Flow Task. This task is used to perform a majority of the data acquisition, transformation, and date writing operations.

4.16.3 Recovery

If a failure occurs during an incremental load (e.g. the network connection goes down) and the incremen-tal load is interrupted, it is possible to run it again starting from a certain point of time prior to the failure time.



4.17 User Models

4.17.1 Data Model

The Data Model is an abstraction layer based on database views implemented on top of both the SIMATIC IT DBs and MDS, which contains a relational, and highly denormalized structures based on the entities of the SIMATIC IT databases.

The Data Model defines SIMATIC IT entities and relationships among them using a SIMATIC IT terminology, thus allowing the end-user to interact with data without the necessity to understand the complexity of the database logic or to be familiar with where the physical data is stored.

It exposes data contained in different databases, thus allowing SIMATIC IT expert users to create specific types of operational reports providing constantly updated information. In detail the user, according to his project needs, can choose its data source among the following:

• SIMATIC IT DBs only, for real-time reports.

• MDS only, for historical reports.

• Both SIMATIC IT DBs and MDS, for mixed reports.

The MDS is used only in scenarios that require a Data Store.

All operational reports are used by personnel responsible for plant and line operations.

4.17.2 Business Model

The Business Model consists of a set of views implemented on top of the MDW database which allows users with limited SIMATIC IT knowledge to create business reports using SIMATIC IT consolidated data.

It is built around the standard business terminology of ISA 95 and provides the end-user the ability to au-tonomously query and retrieve information using common business terminology.

Data exposed by the Business Model are used to create business reports which support managers and executives to make business decisions.



4.17.3 Analytical Model

The model used for the MDM adheres to the Kimball design philosophy in that it stores data in a dimen-sional schema. As such, it yields predictable, understandable designs that users can use. In addition, it can be queried with high performance. This particular model is also known as a dimensional model since it provides a multi-dimensional view of the data based on specific data structures such as star schemas (which may contain snowflaked dimensions). Each is modeled with a central table, known as the fact ta-ble, surrounded by a set of dimension tables3.

The Intelligence Suite provides a set of pre-packaged dimensions along with star and snowflake schemas that can be created and modified using the KPI Editor tool which is integrated in the Engineering Environ-ment.

4.18 Engineering Environment

Both SIMATIC IT Reporting Framework and SIMATIC IT Intelligence Suite contains a Graphical User Interface (GUI), the Engineering Environment, which allows the user to set-up and manage the project.

4.18.1 Main Functionalities of Engineering Environment

Setting up a project Setting up the database connections Creating the MDS, MDW and MDM Tables Creating custom tables and ETL packages Running and Scheduling ETL packages Managing PPA tags Generating the OLAP Cube



5 Major features in version 2.1

5.1 Usability

5.1.1 CAB Reporting Manager

It is now possible to integrate Reports directly inside CAB Web Pages.

With simple configurations reports can be associated with specific CAB user groups, in order to allow dis-playing the reports only to these users. It is also possible to pre-fill report parameters and give the CAB administrator the right to lock parameters preventing the users from modifying them.

5.1.2 Smart navigation

This functionality allows the user to set the report parameters directly from the CAB Portal.

In this way the operator has the possibility to display reports immediately without configuring report pa-rameters.

5.1.3 Smart configuration

It is possible to configure Reporting Framework, Intelligent Suite and the related connections to DBs (both sources and destination, like MDS and MDM), using a centralized environment that through APIs can inter-act directly with the Engineering Environment, creating or updating databases and configuring connection strings.

5.1.4 Scorecard “Excel like” line hierarchical expansion

Now Intelligent Suite Scorecards can display KPIs and measures using trees that, once expanded, indent automatically each sub-level, thus improving the readability.

5.1.5 Import export of Reporting Framework CO Configurations

A new possibility has been offered for importing / exporting CO configurations.



5.2 New functionalities

5.2.1 Multilanguage data read from SIT databases and stored in MDS

Now it is possible to define several languages and import Multilanguage data from different SIMATIC IT databases.

Data is located inside MDS and can be used to generate reports and cubes, and to manage different sites with different languages.

5.2.2 Historian Custom Objects available in MDS for reporting

Now Reporting Framework can create MDS databases ready to host Custom Object data directly imported from SIMATIC IT Historian using ETLs.

5.2.3 Compliance Services Custom Data Structures support

Reporting Framework and Intelligent Suite support Compliance Services data structures, allowing the user to create dedicated MDS structures and to fill them with data coming from SIMATIC IT Compliance Services Databases. The same custom structures can be also used in Intelligent Suite.

5.2.4 OEE Custom field support

If Reporting Framework OEE Plug-In is installed, there is the possibility to add new custom structures to MDS and create ETLs to import data.

The import process requires selecting Custom fields and corresponding custom properties.

The same custom structures can be also used in Intelligent Suite.

5.2.5 New SHC / OEE feature for fiscal year support

If Reporting Framework OEE Plug-In is installed, there is the possibility to import OEE calculated data clus-tered by Fiscal Year, having previously set the Fiscal Year start date into SIMATIC IT SHC and created in SIMATIC IT OEE the Calculated Algorithms clustered by Fiscal Year.

5.2.6 Report printing with counters and callback support

With this functionality it is possible to print reports in a pdf format either on a local or on a network print-er, using a custom system, instead of the native printing capabilities offered by Microsoft SQL Server Re-porting Services. This system can add on each page a customized header and footer (for example it can include the printing ID of the report copy). This could be useful especially in pharmaceutical industry sce-narios.

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