A Multi-Objective Optimization of Secure Pull Manufacturing Systems

This paper aims to optimize the losses of the current manufacturing systems to perform the Just in Time (JIT) system and minimize the time, labor, and material in the manufacturing process. Pull systems, which have a famous name of the Smart Kanban system, are one of the methodologies to implement the JIT system. The setting of manufacturing system frameworks offers intriguing capabilities to improve the performance of pull-controlled creation frameworks. Smart Kanban can be utilized, rather than actual cards, and the data conversion about the manufacturing settings, is accessible through sensors. Since a Just-in-Time system does not include a buffer, any interruption to the system can cause the process to stop quite quickly, so security is necessary for the JIT improvement. However, those systems have recently been unguarded to security threats as they introduce general-purpose technologies. From the viewpoint of the system, a security measure is implemented for pull system methods to check for potential threats and analyze vulnerabilities of the pull system. The Flower Pollination Algorithm (FPA) is used as a novel multiobjective technique to optimize different types of cost and time. The experimental results show that the proposed algorithm has robust security efficiency, as well as reduces cost and time consumption.