Enhancement of Computational Efficiency in Seeking Liveness-Enforcing Supervisors for Advanced Flexible Manufacturing Systems with Deadlock States

• Published in: Applied sciences 2020-04, Vol.10 (7), p.2620
• Main Authors: Pan, Yen-Liang, Tai, Chun-Wang, Tseng, Ching-Yun, Huang, Jong-Ching
• Format: Article
• Language: English
• Subjects: Computer applications; Computing time; Deadlock Prevention; Discrete event dynamic systems; Efficiency; Flexible manufacturing system; Flexible manufacturing systems; Industrial applications; Iterative methods; Liveness-Enforcing Supervisors; Manufacturing industry; Petri nets; Prevention; Production capacity; Supervisors
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app10072620

In industry 4.0, all kinds of intelligent workstations are designed for use in manufacturing industries. Among them, flexible manufacturing systems (FMSs) use smart robots to achieve their production capacity under the condition of a high degree of resources sharing. As a result, deadlock states usually appear unexpectedly. For solving the damage deadlock problem, many pioneers have proposed new policies. However, it is very difficult to make systems maximally permissive even if their policies can solve the deadlock problem of FMSs. According to our survey, the Maximal number of Forbidding First Bad Marking (FBM) Problems (MFFP) seems to be the best technology to obtain systems’ maximally permissive states in the existing literature. More importantly, the number of added control places (CP) is the smallest among the existing research works. However, when the complexity of a flexible manufacturing system increases, the computational burden rises rapidly. To reduce computational cost, we define a new concept named Pre Idle Places (PIP) to enhance the computational efficiency in Seeking Liveness-Enforcing Supervisors. We can bypass all PIP once they can be identified from a deadlock system under the process of solving MFFP. According to the data showed in three classical examples, our proposed Improved MFFP is better than conventional MFFP in terms of computational efficiency with the same controllers.