A Formal Analytical Framework for IoT-Based Plug-And Play Manufacturing System Considering Product Life-Cycle Design Cost

Technological advances in the Internet of Things (IoTs) and the evolution of manufacturing models applied in industrial environments increase the use of concepts, such as plug-and-play in intelligent manufacturing systems for customized products. However, plug-and-play manufacturing modes are subjected to dynamic changes in both products and resources during the runtime phase. Hence, traditional model-based formal verification methods cannot guarantee system dependability before and after the reconfiguration. In addition, customized manufacturing is a product-driven process, which requires product- and equipment-based modeling and analysis to be considered during the product life-cycle management. In this article, a model-data-driven (DD) framework for the formal analysis of production resources is proposed. An IoT-based DD technology is combined with a model-driven approach to ensure dependability verification of formal models in the operational production line phase through real-time resource status feedback. The proposed method is verified experimentally, using a smart factory experimental platform. The results show that the proposed method reduces the time-cost of the formal modeling phase by at least 75%.