SERVICE ENGINEERING FOR THE DIGITALIZATION IN ......Copenhagen, May 31th, 2017 Service Engineering...

SERVICE ENGINEERING

FOR THE

DIGITALIZATION IN FUTURE SEAPORTS

M.Sc. Aaron Heuermann

BIBA – Bremer Institut für Produktion und Logistik GmbH

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Copenhagen, May 31th, 2017 Service Engineering for the Digitalization in Future Seaports, M.Sc. Aaron Heuermann

Maritime Supply Chains

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ISO intermodal containers

standardization

Container ships with cargo

capacities up to 20,000 TEU

repetitive processes

Standardization and repetitive

processes enable a

high automation

Container Logistics

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Partial automation and

manual process steps

along entire supply chain

Disruptions in information

flows

Digitalization in Container Logistics

Internal automation in

terminals using automatic

guided vehicles

Internal digital information

flows

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Project Logistics

Main frames, towers,

blades etc. with varying

sizes

individual components

Varying conditions and

individual processes

low automation

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Iterative Process and Requirements Assessment

Logistic

Systems

Logistic

Processes

Stakeholders

Greenfield

What if …

Critical

Incidents

Change the system boundaries

Process modeling (BPMN 2.0)

Varied views and interfaces

Planning from scratch and variance comparison

… the container ship is delayed

Weather, delays etc.

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Decentralized and nontransparent availability of ship

schedules and cargo closing deadlines

Automatic identification and fleet management

systems allow localization of ships and trucks

Initial Situation in Container Logistics

Ship

ScheduleShip

ScheduleShip

Schedule

Ship

ScheduleShip

ScheduleShip

Schedule

Ship

ScheduleShip

ScheduleShip

Schedule

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Collect and integrate ship

schedules and cargo closing

deadlines from various sources

Intelligent tracking data

processing and comparison

with schedules

Centralized and transparent

distribution to all stakeholders

Service Ideation for Container Logistics

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Long handling operations at

distributed locations

Experts and certifiers are

required at each location

Expert knowledge and

experience is only available at

one location at the same time

Individual and no collective

knowledge and experiences

Initial Situation in Project Logistics

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Centralized supervision and

controlling of complex handling

operations in a virtual control

center

Intelligent processing of video

and sensor data streams

Collection and distribution of

experiences and expert

knowledge

Service Ideation for Project Logistics

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Portfolio for Evaluation and Selection

Make data available

(2)

Implement

(1)

Do not implement

(4)

Wait until data become relevant

(3)

Data

rele

van

ce

Data availability

low

hig

h

low high

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System Architecture (I)

Local data selection and

preprocessing is required

Data encryption and

protection is required

Microsoft Azure Cloud

Services enable

high service availability

and scaleability

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System Architecture (II)

PresentationProcessingTransportData sources

Storage

Devices(IP)

Devices(IoT)

Devices(Low Power)

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Iterative Implementation and Evaluation

Plan

DoCheck

Act

Plan

DoCheck

Act

Initial situation „Smart Vision“

Service

maturity

Other capability levels

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Collect and integrate ship

schedules and cargo closing

deadlines from various sources

Collect automatic identification

system and tracking data

Compare schedules and actual

data to identify conflicts

Capability Level A in Container Logistics

Ship

ScheduleShip

ScheduleShip

Schedule

Ship

ScheduleShip

ScheduleShip

Schedule

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Saved time

DelayScheduled shipping time Unloading time Loading time

Wasted t.

ATD PTA ETA Beginn of loading PTD

Cargo Closing

Intelligent calculation of dynamic cargo closing deadlines

Capability Level B in Container Logistics

Scheduled shipping time Unloading time Loading time

Req. storage time

ATD PTA/ETA Beginn of loading PTD

Cargo Closing

Req. storage time

DelayScheduled shipping time Unloading time Loading time

Req. storage time

ATD PTA ETA Beginn of loading PTD

Dynamic Cargo Closing

ATD = Actual time of departure, PTA = Planned time of arrival, ETA = Estimated time of arrival, PTD = Planned time of departure

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Nowadays, cargo closing

is confirmed when a

container is at the terminal

Location and state

tracking allow cargo

closing confirmations

when containers are

closed and in a defined

area

Capability Level C in Container Logistics (I)

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Savings

Nowadays, one cargo closing deadline for documents and

containers

Separating the information and material flows leads to

multiple cargo closing deadlines and savings

Capability Level C in Container Logistics (II)

Req. storage time


Processing and storage time

Cargo Closing


Documents processing time

Informational Cargo Closing

Material Cargo Closing

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Smart Containers interact and

with other containers, vehicles

and parties autonomously

Container2X communication

Containers autonomously

agree individual processes

with other parties according to

destination and content

„Smart Vision“ in Container Logistics

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Remote supervision of

handling operations using

modern communication and

video systems

Parallel streaming in a virtual

control center

Capability Level A in Project Logistics (I)

Body Cam

Web Cam

Drone

Video Wall

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Nowadays, experts and certifiers are required at each

location

Remote supervision allows parallel handling operations

Capability Level A in Project Logistics (II)

Travel time and cost Operation time and cost

Travel time and cost Operation time and cost

Handling Operation A

Handling Operation B

Operation time and cost

Savings

Further handling operations possible

Handling Operation A

Operation time and cost

Handling Operation C

Handling Operation B

Add. handling operation

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Intelligent personal

assistants provide state

dependent decision

support and operation

guidelines

Additional information via

Augmented Reality

Combining video and

sensor stream analytics

with experiences and

expert knowledge

„Smart Vision“ in Project Logistics

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Service

ideation

Service

requirements

Service

design

Service

implementation

Service

test

Market

introduction

Conclusion – The Service Engineering Process

Continual

improvement

IT test

Collection of

ideas

Evaluation of

ideas

Process

assessment

Requirements

assessment

Product model

Process model

Business Model

implementation

Organisational

measures

Product test

Process test

Marketing

activities

Roll out

Resource model

IT architecture

Human resources

measuresResource test User feedback

IT implementation

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Page 25Copenhagen, May 31th, 2017 Service Engineering for the Digitalization in Future Seaports, M.Sc. Aaron Heuermann

BIBA – Bremer Institut für Produktion und Logistik GmbH

Postanschrift: Postfach P.O.B. 33 05 60 · D-28335 Bremen / Germany

Geschäftssitz: Hochschulring 20 · D-28359 Bremen / Germany

USt-ID: DE814890109 Amtsgericht Bremen HRB 24505 HB

Tel: +49 (0) 421/218-02 Fax: +49(0)421/218 - 50031

E-Mail: [email protected] · Internet: www.biba.uni-bremen.de

Geschäftsführer: Prof. Dr.-Ing. habil. Klaus-Dieter Thoben, Olaf Simon

M. Sc. Aaron Heuermann

Research Scientist

[email protected]

+49 (0) 421 218 - 50 172

Contact

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SERVICE ENGINEERING FOR THE DIGITALIZATION IN ......Copenhagen, May 31th, 2017 Service Engineering...

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