Digital Twins for future industrial competitiveness

Digital Twins for future industrial competitiveness - DOUBLED research center

With the support of a research team that has its roots in computer aided engineering design research back in 1990’s merging research from Luleå University of Technology, Blekinge Institute of Technology and Stanford Unviersity we are now embarking on the the design of circular business solutions and systems through digital twins – DOUBLED.

Please contact us (Marco Bertoni & Tobias Larsson) if you want to know more on how you may join our research center creation!

DOUBLED wants to be an internationally leading research environment and the first- hand choice for partners who want to develop the necessary engineering and simulation capabilities to realise the vision of digital-driven product development.

DOUBLED is based on a clear vision on model- and data-driven design, building on the achievements of the Model Driven Development and Decision Support (MD3S) profile. MD3S is internationally recognised as leading research environment in this domain and features continuous collaborations with a number of industrial partners.

DOUBLED will deepen MD3S research to understand how Digital Twins can be used to bring together diverse disciplines (engineering, sustainability, economics etc.) to inform engineering designers in an early stage, so to enable the creation of value- adding, sustainable life-cycle solutions and systems.

The main objective of DOUBLED is to create new theories, methodologies and support tools to improve designers’ ability of simulating the economic and society-wide benefits of sustainable circular solutions and Product-Service System through the use of Digital Twins. Its objective is also to increase international collaboration, impact educational programmes and disseminate new knowledge in top-ranked forums.

Key features

  • A process to guide DT` development to support the design of circular solutions.
  • Methods and tools for DT realisation and implementation in industrial contexts.
  • Case-based twinned models and demo.
  • Educational/training material, frameworks and implementation guidelines.

WHAT ARE DIGITAL TWINS?

Digital Twins consist of a physical entity, a virtual representation of that entity, and a bi-directional data connection that feeds data between them  in both directions. 

Developing a digital twin is first and foremost a matter of ensuring a physical-to-virtual connection that captures the states of a physical entity (e.g., through sensors) and transfer it to the digital model. This allows the digital model to be always in sync with its physical counterpart, replicating it exactly.

A virtual-to-physical connection describes the flow of information and processes from the digital model to the physical object, so that – after having simulated a number of possible scenarios to determine the optimal set of parameters value for the physical entity – the latter is adjusted based on what’s best according to the simulation.

WHY A STRONGHOLD ON DIGITAL TWINS?

Digital Twins (DT) are listed by Gartner, Inc. as one of the most hyped technologies of the 2020s. This hype is driven by recent advances in Industry 4.0, data management and data processing technologies, as well as by the strong academic and industrial interest towards data-driven and digital manufacturing initiatives.

A 2019 survey among 599 organisations in 6 countries – having an annual revenue greater than $50 million- shows that 75% percent of the sample already used or were in the process of developing DT in conjunction with Internet of Things (IoT) projects.

DT are becoming a hotspot in the European research agenda, with several projects

exploring how virtual models can digitally reproduce with maximum accuracy the behaviour and performances of the real life counterpart to which they are twinned.

THE TRACKS OF DOUBLED

DOUBLED will be structured in 3 research tracks, each one focusing on a specific set of research questions related to the development and application of the DT in the early stages of circular solutions and systems design.

PRODUCT TWINNING TRACK

This track will focus on how virtual products shall be developed, twinned, controlled and used in a distributed environment to support early stage design decision making. The defining research questions for this track are:

  • How shall hardware models be developed/populated for prognostic purposes in an early design stage?
  • How shall twinning be realised between physical and digital objects?
  • How shall data analytics be used to predict the behaviour of products in circular systems?
  • How can the product twins support early stage design decision making?

PROCESS TWINNING TRACK

This track will focus on the development of behavioural models for the DT, with the objective to realistically replicate manufacturing, usage and end-of-life operations of complex systems. This track will be focused on the following research questions:

  • How shall process models be developed to simulate the lifecycle behaviour of circular
    solutions?
  • How shall process data be gathered from Cyber Physical Systems?
  • How shall the data from the system lifecycle be analysed to provide useful input to
    feed lifecycle simulation models?
  • How shall the results of process simulation activities be displayed to the distributed
    cross-functional team?

VALUE DISCOVERY TRACK

This track will focus on how the value of circular solutions – looking at how the solution affect people, planet and profit in the ecosystem – shall be captured and simulated through the use of digital twin/thread solutions. This track will pivot on the following research questions:

  • How shall qualitative and quantitative value-related dimensions for circular solutions be modelled in the Digital Twin?
  • How shall customer satisfaction and value-related data be gathered from the physical word and transferred to the virtual one?
  • How shall value-related data be analysed to predict future customer behaviour and value generation in circular businesses?
  • How shall Augmented and Virtual Reality applications be used to create ‘virtual experiences’ and communicate the value of circular product/service solutions?

Technologies explored in DOUBLED

Defining

CAD, Discrete Event Simulation and other CAE approaches for digital model building

Twinning

Cyber Physical Systems etc

Predicting

Machine Learning etc

Deciding

Virtuap Prototyping etc

Contacts

Marco Bertoni (PhD)
Professor
Main responsible for development of DOUBLED
Tobias Larsson (PhD)
Professor
Research Director and project leader MD3S

Features from research etablishing DOUBLED

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Industry 4.0 Cyber Physical Factory!

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Reserach publications

Investigating effects of group model building on sustainable design decision-making 

Investigating effects of group model building on sustainable design decision-making 

Abstract This research seeks to investigate the effects of a Group Model Building approach on the sustainability knowledge base prior to the…

Sustainability awareness in engineering design through serious gaming

Sustainability awareness in engineering design through serious gaming

Abstract Sustainability considerations are traditionally difficult to trade-off with technical and business requirements in an early design phase. Hence, design…

Codesign in resource-limited societies: theoretical perspectives, inputs, outputs and influencing factors

Codesign in resource-limited societies: theoretical perspectives, inputs, outputs and influencing factors

Abstract Codesign with resource-constrained people living in developing countries is crucial for sustained adoption and use of designed solutions. Several…

Designing solutions with the product-service systems digital twin: What is now and what is next?

Designing solutions with the product-service systems digital twin: What is now and what is next?

Abstract The emergence of IoT has propelled the traditionally known Product-Service System (PSS) to be Digital Twins (DT) are of…

Data-driven value creation in Smart Product-Service System design: State-of-the-art and research directions

Data-driven value creation in Smart Product-Service System design: State-of-the-art and research directions

Abstract The emergence of IoT has propelled the traditionally known Product-Service System (PSS) to be characterized by smarter technologies, enabling…

Can Design Be Non-paternalistic? Conceptualizing Paternalism in the Design Profession

Can Design Be Non-paternalistic? Conceptualizing Paternalism in the Design Profession

Abstract Paternalism is an instance of someone making a decision on behalf of someone else. A professional designer can exhibit…

A global capstone project course in the age of coronavirus pandemic: Learning from the ME310 ReGlove case

A global capstone project course in the age of coronavirus pandemic: Learning from the ME310 ReGlove case

Abstract Engineering educations deploy capstone courses as a way of supporting students’ transition into the engineering profession. This paper presents…

Physical Prototypes to Foster Value Co-creation in Product-Service Systems Conceptual Design: A Case Study in Construction Equipment

Physical Prototypes to Foster Value Co-creation in Product-Service Systems Conceptual Design: A Case Study in Construction Equipment

Abstract The paper presents the experience collected in a case study in the construction equipment concerning the use of physical…

Data-Driven Design Automation for Product-Service Systems Design: Framework and Lessons Learned from Empirical Studies

Data-Driven Design Automation for Product-Service Systems Design: Framework and Lessons Learned from Empirical Studies

Abstract The digitalization era has brought about unprecedented challenges for the manufacturing industries, pushing them to deliver solutions that encompass…

Find full list of research publications from MD3S here.