Reliability Modeling and Assessment of Internet-of-Things in Smart Manufacturing Systems: A Modular Petri Net Approach

The Internet of Things (IoT) represents a transformative convergence of traditional manufacturing systems with advanced information technologies, collectively referred to as smart manufacturing. The interconnected nature of IoT facilitates real-time data collection and analysis, optimizing production processes and improving operational efficiency. However, the increased complexity and interdependence of IoT systems pose significant challenges in reliability modeling and assessment. This article introduces a novel reliability model that comprehensively integrates factors such as degradation of physical systems and information networks, along with their interactive impacts on system performance and reliability. A modular Petri net approach is developed to efficiently assess reliability of IoT systems by leveraging a structured framework to model the intricate interdependencies within IoT. The modular nature of the proposed approach enables targeted analysis and scalability enhancements, addressing the critical need for models that can adapt to the evolving landscape of IoT in smart manufacturing systems. A vehicle manufacturing system example is introduced to demonstrate the proposed approach. The results reveal the distinct impact pathways of the physical system and information network on overall system reliability. Statistical analysis across various system configurations shows that modifying the architecture of the information network can lead to an average improvement of 20.67% in system reliability.