A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future

Adrien Bécue,Philipp Borchers,Linda Feeken,Eva Maia,Isabel Praça

doi:10.3390/app10134482

Adrien Bécue, Philipp Borchers + Show 3 more

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https://doi.org/10.3390/app10134482

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Abstract

In the context of Industry 4.0, a growing use is being made of simulation-based decision-support tools commonly named Digital Twins. Digital Twins are replicas of the physical manufacturing assets, providing means for the monitoring and control of individual assets. Although extensive research on Digital Twins and their applications has been carried out, the majority of existing approaches are asset specific. Little consideration is made of human factors and interdependencies between different production assets are commonly ignored. In this paper, we address those limitations and propose innovations for cognitive modeling and co-simulation which may unleash novel uses of Digital Twins in Factories of the Future. We introduce a holistic Digital Twin approach, in which the factory is not represented by a set of separated Digital Twins but by a comprehensive modeling and simulation capacity embracing the full manufacturing process including external network dependencies. Furthermore, we introduce novel approaches for integrating models of human behavior and capacities for security testing with Digital Twins and show how the holistic Digital Twin can enable new services for the optimization and resilience of Factories of the Future. To illustrate this approach, we introduce a specific use-case implemented in field of Aerospace System Manufacturing.

Highlights

The recent cyber-attacks on Renault [1], Saint-Gobain [2] Rosnef and Merck [3], among others, have spotlighted cyber-security-related threats towards industry, as well as their unexpected financial and business impacts
We provide the baseline of a comprehensive Factory of the Future (FoF) modeling and simulation capacity
Building on state-of-the-art Digital Twins (DTs) and CRs, we identify and address some important limitations of the technology, which essentially relate with the lack of adapted human behavior modeling techniques and the need for co-simulation

Summary

Introduction

The recent cyber-attacks on Renault [1], Saint-Gobain [2] Rosnef and Merck [3], among others, have spotlighted cyber-security-related threats towards industry, as well as their unexpected financial and business impacts. Unlike risks affecting regular Information Technology (IT) systems, attacks targeting Operational Technology (OT), which supports industrial processes, can cause physical damages and casualties [4]. When it comes to the manufacturing sector, business impacts add up. In 2011, a German governmental project coined the term Industry 4.0 with the ambition to “drive digital manufacturing forward by increasing digitization and the interconnection of products, value chains and business models” [5]. The electrification of factories progressively enabled replacing single-speed central steam engines by task-specific power groups, allowing greater flexibility, reduced power loss and improved working conditions [8]

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