Towards Data-Driven Reliability Modeling for Cyber-Physical Production Systems

Jonas Friederich, Sanja Lazarova-Molnar
2021 Procedia Computer Science  
Reliability is one of the most important performance indicators in contemporary production facilities. Increasing reliability of manufacturing systems results in their prolonged lifetimes, and reduced maintenance and repair costs. Reliability modeling is a common technique for deriving reliability measurements and illustrating relevant fault-dependencies. There is a significant body of research focusing on hardware-and software reliability models, such as Fault Trees, Petri Nets and Markov
more » ... s. Up until now, development of reliability models has been a labor-intensive and expert-knowledge-driven process. To remedy that, through the prevalence of data stemming from the new and technologically advanced manufacturing systems, we propose that data generated in modern manufacturing lines could be used to either automate or at least to support development of reliability models. In this paper, we elaborate on the details of our proposed framework for data-driven reliability assessment of cyberphysical production systems. We, furthermore, introduce a case study that will aid the development and testing of the proposed novel data-driven approach. Abstract Reliability is one of the most important performance indicators in contemporary production facilities. Increasing reliability of manufacturing systems results in their prolonged lifetimes, and reduced maintenance and repair costs. Reliability modeling is a common technique for deriving reliability measurements and illustrating relevant fault-dependencies. There is a significant body of research focusing on hardware-and software reliability models, such as Fault Trees, Petri Nets and Markov Chains. Up until now, development of reliability models has been a labor-intensive and expert-knowledge-driven process. To remedy that, through the prevalence of data stemming from the new and technologically advanced manufacturing systems, we propose that data generated in modern manufacturing lines could be used to either automate or at least to support development of reliability models. In this paper, we elaborate on the details of our proposed framework for data-driven reliability assessment of cyberphysical production systems. We, furthermore, introduce a case study that will aid the development and testing of the proposed novel data-driven approach.
doi:10.1016/j.procs.2021.03.073 fatcat:vbxw4gsogfajdaffbms5s63sxi