The DeFacto project, supported by the European Commission via a Marie Skłodowska-Curie Global Individual Fellowship, tackles the complexity arising from the transformation of industrial manufacturing systems into intricate cyber-physical systems. This evolution offers unprecedented opportunities but also poses intellectual and engineering challenges. DeFacto aims to advance the design automation of cyber-physical production systems by developing innovative modeling paradigms, scalable algorithms, software architectures, and tools. In the DeFacto approach, production systems are managed through service-oriented manufacturing software architectures. System-level models capture the features and the requirements of production systems, representing both production and computational processes as services provided by the infrastructure. Methodologies for system analysis and optimization rely on compositional abstractions of system behaviors grounded in assume-guarantee contracts. This paper outlines key research endeavors, findings, and lessons learned from the DeFacto project.

Design Automation for Cyber-Physical Production Systems: Lessons Learned from the DeFacto Project

Lora, Michele;Gaiardelli, Sebastiano;Spellini, Stefano;Nuzzo, Pierluigi;Fummi, Franco
2024-01-01

Abstract

The DeFacto project, supported by the European Commission via a Marie Skłodowska-Curie Global Individual Fellowship, tackles the complexity arising from the transformation of industrial manufacturing systems into intricate cyber-physical systems. This evolution offers unprecedented opportunities but also poses intellectual and engineering challenges. DeFacto aims to advance the design automation of cyber-physical production systems by developing innovative modeling paradigms, scalable algorithms, software architectures, and tools. In the DeFacto approach, production systems are managed through service-oriented manufacturing software architectures. System-level models capture the features and the requirements of production systems, representing both production and computational processes as services provided by the infrastructure. Methodologies for system analysis and optimization rely on compositional abstractions of system behaviors grounded in assume-guarantee contracts. This paper outlines key research endeavors, findings, and lessons learned from the DeFacto project.
2024
Smart manufacturing, system-level design, design automation, software architecture, system modeling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1133847
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