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

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.The present work was developed under the EUREKA–ITEA3 Project CyberFactory#1 (ITEA-17032), co-funded by Project CyberFactory#1PT (ANI|P2020 40124), from FEDER Funds through NORTE2020 program and from National Funds through FCT under the project UID/EEA/00760/2019 and by the Federal Ministry of Education and Research (BMBF, Germany, funding No. 01IS18061C).info:eu-repo/semantics/publishedVersio

Supporting Industry 4.0 Implementation with Modeling and Simulation - two SME Cases

This article investigates the modelling and simulation that supports the implementation of Industry 4.0 through two industrial SME case studies. Our findings suggest that the importance of modelling and simulation is increasing significantly also in the SME context as the use of smart manufacturing technologies proliferate in every industry. Rather than applying all-embracing modelling and simulation tools, SMEs need lighter task-focused tools, which they can nimbly utilize and avoid big investments in modelling tools as well as competence development. Larger companies are leading the Industry 4.0 development, but to take full advantage of the benefits it promises, they need to engage their supply chains that often include SMEs. Further research on the changes Industry 4.0 brings about is needed to support the different stakeholders in the value chains better. Research is also needed in order to take advantage of the opportunities, and to respond to the challenges of this transformation

Detecting and Processing Anomalies in a Factory of the Future

Production systems are changing in many aspects on the way to a Factory of the Future, including the level of automation and communication between components. Besides all benefits, this evolution raises the amount, effect and type of anomalies and unforeseen behavior to a new level of complexity. Thus, new detection and mitigation concepts are required. Based on a use-case dealing with a distributed transportation system for production environments, this paper describes the different sources of possible anomalies with the same effect, anomaly detection methods and related mitigation techniques. Depending on the identified anomaly, the FoF should react accordingly, such as fleet or AGV reconfiguration, strong authentication and access control or a deletion of adversarial noises. In this paper, different types of mitigation actions are described that support the fleet in overcoming the effect of the anomaly or preventing them in the future. A concept to select the most appreciate mitigation method is presented, where the detection of the correct source of the anomaly is key. This paper shows how various techniques can work together to gain a holistic view on anomalies in the Factory of the Future for selecting the most appropriate mitigation technique

Developing and Using a Digital Twin of a Decentralized Robot Fleet. Talk at the Finnish Industrial Internet Forum

The CyberFactory#1 (2018-2022) project aims at designing, developing, integrating and demonstrating a set of key enabling capabilities to foster optimization and resilience of the Factories of the Future (FoF). The project includes 29 partners from seven countries and addresses the needs of pilots from Transportation, Automotive, Electronics and Machine manufacturing industries around use cases such as statistical process control, real time asset tracking, distributed manufacturing, and collaborative robotics. The talk will give a short overview about the CyberFactory#1 modeling and simulation activities and present the development and application of a digital twin for a fleet of automated robots as part of the work done by the German partners

Challenges in Achieving Explainability for Cooperative Transportation Systems

The anticipated presence of highly automated vehicles and intelligent infrastructure systems in urban traffic will yield new types of demand-driven mobility and value-added services. To provide these services, future transportation systems will consist of large-scale, cooperative ensembles of highly automated and connected systems that operate in mixed traffic and have to interact with human drivers and vulnerable road users while coordinately ensuring traffic efficiency and safety. We posit that the ability to explain processes and decisions is essential for such systems. Adequately addressing the needs of the involved actors will require that explainability and trust-worthiness are handled as core properties in the development of highly automated systems. To support explainability-driven design approaches, we identify a set of explainability challenges in the context of a large-scale ongoing endeavor on cooperative transportation and present approaches to target these challenges