Automated Generation of Hybrid Probabilistic Risk Models From SysML V2 Models of Software-Defined Manufacturing Systems

Abstract The concepts of Software-Defined Manufacturing (SDM) and Digital Twins emphasize the current trend in production system development. These systems are characterized by frequent software updates to address adjustable production processes and higher system flexibility. These software-intensive systems are safety-critical and require a thorough reliability analysis. This implies the necessity to automatically re-evaluate the reliability before each software update. In this paper, we introduce a new Model-to-Model (M2M) transformation method that enables the automatic generation of hybrid reliability models from the Digital Twin formalism based on SysML v2. The models of the Digital Twin are extended with reliability data. The method includes (i) transformation of behavioral models to Markov chains, (ii) transformation of structural models to fault trees, and (iii) the generation of hybrid reliability models based on the software and system structure. Besides, this paper describes an SDM-system, based on a robotic manipulator, that fulfills two different tasks depending on the uploaded software. This case study shows that our M2M transformation method enables continuous reliability assessment of SDM-systems.