This document discusses a project focused on utilizing digital twin technology to enhance decision-making throughout the product lifecycle, involving multiple partners and twelve use cases. It explores how digital twins represent physical objects and facilitate improved decision support by formalizing knowledge across various lifecycle phases. Recommendations for better understanding the complexities of digital twin usage as decision support tools are also presented.

1. Digital Twin based services for decision
support over the product lifecycle
Industrie 2025, F&E Konferenz zur Industrie 4.0
5 February 2020
Dr. Shaun West (HSLU) and Dr. Jürg Meierhofer (ZHAW)

2. Industrie 2025, F&E Konferenz zur Industrie 4.0 |Jürg Meierhofer & Dr Shaun West
Introduction
Digital Twin based services for decision support over the product lifecycle
This presentation is based
on an Innosuisse funded
project with ten partners to
demonstrate how the digital
twin can support decision
making over the product life
cycle
Introduction to the IMPULSE project
The context of the decision making
Review of use cases
Demonstrate with one use case linking of the lifecycle phases

3. Industrie 2025, F&E Konferenz zur Industrie 4.0 |Jürg Meierhofer & Dr Shaun West
Digital Twin

4. Industrie 2025, F&E Konferenz zur Industrie 4.0 |Jürg Meierhofer & Dr Shaun West
Supply chain
Factories
Manufacturing
and Design
Products
and
assets
OwnersPartners Suppliers
Source: SAMSUNG CES Event 2018
PLM
ERP CRM
MES
MMS
“a dynamic virtual
representation of a
physical object or
system across its
lifecycle, using real-time
data to enable
understanding, learning
and reasoning”
(Bolton et al., 2018).
Product lifecycle
Many actors
Many perspectives
Beginning
of life
Middle
of life
End
of life
Many processes/data producers
Operational
Minutes
Tactical
Hours/weeks
Strategic
Months/years
Many timeframes
Digital Twin

5. Industrie 2025, F&E Konferenz zur Industrie 4.0 |Jürg Meierhofer & Dr Shaun West
Framework
Decision making process
Transformation of data to wisdom and in doing so codifying the business processes
D I UK W
Past Future
Doing things right Doing the right
things
Information
(what)
Knowledge
(how to)
Understanding
(why)
Wisdom
(what is best)
(La Longa et al., 2012)
Data

6. Industrie 2025, F&E Konferenz zur Industrie 4.0 |Jürg Meierhofer & Dr Shaun West
Case based research
Examples where the digital twins can provide support based on +12 use cases
Question Actors (primary) Layer Phase Level Time frame
How did the component actually function
compared with the design?
Operations,
Maintenance, Design
Component
(aggregated)
BOL/MOL Strategic Annually
What could I do to improve factory output Asset mgr, operations Equipment, line MOL Tactical,
strategic
Annually
What happens if I delay the next planned
maintenance on the machine?
Asset mgr, operations,
maintenance
Assembly,
equipment, line
MOL Tactical,
strategic
Monthly,
annually
How can I improve my spares holding? Asset mgr Line/Lines MOL
What options do I have now that machine is
broken?
Operations,
maintenance
Line/Lines MOL Operational Live/daily
A competitor is opening a new factory what are
the implications?
CEO, CFO Business
ecosystem
MOL Strategic Annually
I have a new mix of products, what is the
optimal production plan?
Production, sales Lines MOL Tactical Daily, weekly,
monthly
I need to replace a machine in a line, what is the
best option for me?
Asset mgr, production,
maintenance,
procurement
Equipment/ lines MOL Strategic Annually
We need to make the next product generation;
how do firms operate the machines today and
how do they perform?
Design, NPD, service Equipment
(assembly,
components)
MOL/BOL Strategic Annually
Questions provide a good way to define the use cases and where we need advice

7. Industrie 2025, F&E Konferenz zur Industrie 4.0 |Jürg Meierhofer & Dr Shaun West
Lifecycle analysis
Beginning of Life
Design
Product
design
Process
design
Plant
design
Manufacture
Produc-
tion
Internal
logistics
Middle of Life
Distrib-
ution
External
logistic
Use/
operate
Optimize
Support
Train Maintain Repair
End of Life
Upgrade
MOL2
Retire
Reverse
logistics
Recycle Resell
Case based research
The project has use cases linking many parts from the lifecycle
Beneficiaries include: the OEM; the asset manager; the operator; and, the maintener

8. Industrie 2025, F&E Konferenz zur Industrie 4.0 |Jürg Meierhofer & Dr Shaun West
Closing
Conclusions
The digital twin helps us to
make better decisions by
formalizing the knowhow
that is created over the
whole lifecycle
The digital twin is a representation of a machine or a business
The digital twin can link different lifecycle phases
The digital Twin should contain the current and past states
The digital twin helps us capture and formalize knowhow

9. Industrie 2025, F&E Konferenz zur Industrie 4.0 |Jürg Meierhofer & Dr Shaun West
Closing
Recommendations
The use of the digital twin as
a decision support tool over
the lifecycle needs to be
better understood given the
complexities of the system
We need to understand how to deal with the ‘gaps’
We need to support value cocreation through decision making
We need to understand actors over the lifecycle
We need identify the beneficiaries over the lifecycle

10. Industrie 2025, F&E Konferenz zur Industrie 4.0 |Jürg Meierhofer & Dr Shaun West
For more information please visit slideshare.net/ShaunWest
Who we are…
Collaboration is key with the development of digital twin enabled services
2
Projekt4 2.8.2007 19:17 Uhr Seite 1
Senior Lecturer
Industry 4.0
Coordinator Platform
Executive MBA
Dr. sc. techn. ETH (PhD)
Jürg Meierhofer
8401 Winterthur, Switzerland
Rosenstrasse 3, P.O. Box
www.zhaw.ch/idp
www.zhaw.ch/=meeo
juerg.meierhofer@zhaw.ch
Phone direct: +41 58 934 40 52
School of
Engineering
IDP Institute of Data Analysis
and Process Design
Zurich University
of Applied Sciences
Jürg Meierhofer
Expert Smart Service Engineering

11. Industrie 2025, F&E Konferenz zur Industrie 4.0 |Jürg Meierhofer & Dr Shaun West
Thanks for your time!
Questions over coffee at the poster… Slides posted on SlideShare.com
Expert Group Smart Services
Our mission is to identify and apply best practice methodologies for
designing data-intensive services that create personal and business
value of data for users in their specific context

12. Projekt4 2.8.2007 19:17 Uhr Seite 1
Senior Lecturer
Industry 4.0
Coordinator Platform
Executive MBA
Dr. sc. techn. ETH (PhD)
Jürg Meierhofer
8401 Winterthur, Switzerland
Rosenstrasse 3, P.O. Box
www.zhaw.ch/idp
www.zhaw.ch/=meeo
juerg.meierhofer@zhaw.ch
Phone direct: +41 58 934 40 52
School of
Engineering
IDP Institute of Data Analysis
and Process Design
Zurich University
of Applied Sciences
Jürg Meierhofer
Expert Smart Service Engineering
Digital Twin based services for decision support over the
product lifecycle
The project has been designed to understand how the
digital twin can support decision making. The partners have
taken over twelve use cases to create decisions support
services over the product lifecycle, considering many
perspectives, many actors, timeframes and processes.
Lifecycle analysis
Beginning of Life
Design
Product
design
Process
design
Plant
design
Manufacture
Produc-
tion
Internal
logistics
Middle of Life
Distrib-
ution
External
logistic
Use/
operate
Optimize
Support
Train Maintain Repair
End of Life
Upgrade
MOL2
Retire
Reverse
logistics
Recycle Resell
D I UK W
Past Future
Doing things right Doing the right
things
Information
(what)
Knowledge
(how to)
Understanding
(why)
Wisdom
(what is best)
Data
Transformation of data to knowledge codifies the system allowing us
to understand the past and to better consider the future options
We need identify
the beneficiaries
over the lifecycle
We need to
understand how to
deal with the ‘gaps’
We need to support
value cocreation
through decision
making
We need to
understand actors
over the lifecycle
The use of the digital twin as a decision support
tool over the lifecycle needs to be better
understood given the complexities of the system.
The digital twin helps us to make better decisions by
formalizing the knowhow that is created over the
whole lifecycle and tailoring for the actor’s needs.
Question Actors (primary) Layer Phase Level Time frame
How did the component actually function
compared with the design?
Operations,
Maintenance, Design
Component
(aggregated)
BOL/MOL Strategic Annually
What could I do to improve factory output Asset mgr, operations Equipment, line MOL Tactical,
strategic
Annually
What happens if I delay the next planned
maintenance on the machine?
Asset mgr, operations,
maintenance
Assembly,
equipment, line
MOL Tactical,
strategic
Monthly,
annually
How can I improve my spares holding? Asset mgr Line/Lines MOL
What options do I have now that machine is
broken?
Operations,
maintenance
Line/Lines MOL Operational Live/daily
A competitor is opening a new factory what are
the implications?
CEO, CFO Business
ecosystem
MOL Strategic Annually
I have a new mix of products, what is the
optimal production plan?
Production, sales Lines MOL Tactical Daily, weekly,
monthly
I need to replace a machine in a line, what is the
best option for me?
Asset mgr, production,
maintenance,
procurement
Equipment/ lines MOL Strategic Annually
We need to make the next product generation;
how do firms operate the machines today and
how do they perform?
Design, NPD, service Equipment
(assembly,
components)
MOL/BOL Strategic Annually
(La Longa et al., 2012)
Questions provide a good way to define the use cases and where we
need advice. They also help us to understand the context and build
user stories around the problem. The digital twin helps to codify the
understanding so that in the future it is easier to do the right things. It
is not without its challenges…
A single example linking of the lifecycle phases shows the complexity
that the designer of the digital twin faces: Who are the beneficiaries?
When are they active? What is their perspective? Decision timeframe?
What data is missing? How are decisions made?
shaun.west@hslu.ch