Abstract
A Flexible Manufacturing Cell (FMC) is a system that consists of computer-integrated machines, automatic material handling systems, and robots. It produces different part types with minimal worker involvement. Many different methods, such as queuing systems and simulation models, have been applied in FMC modeling in the literature. This study aims to use Petri Nets (PN) in modelling complex FMCs. The study is carried out in the FMC located in the Advanced Manufacturing Systems Laboratory of Baskent University. The FMC consists of a CNC machining center, a material handling robot and a pallet, which has three work-piece carriage capacities. Processing times of FMC elements may vary due to reasons (the power usage performance, air supply efficiency, electrical power efficiency, etc.) arising from the mechanical structure of the system. This uncertainty needs to be taken into account when modeling the system. In this study, the uncertain (fuzzy) processing times associated with the transitions were caused by the mechanical structure of the system. In order to compare with the newly developed fuzzy models, the system was first modeled using Transition Time Petri Nets (TTPN), in which the running times associated with the transition times take precise values. On the other hand, for handling fuzzy values of the actual operating times in the FMC, two models namely, Partial-Fuzzy Transition Time Petri Nets (Partial-FTTPN) and Fuzzy Transition Time Petri Nets (FTTPN) are developed. The results of the three models are compared to analyze the benefits of combining “time uncertainties” resulting from the natural behavior of FMCs.
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Bulca, F.B., Ic, Y.T., Yurdakul, M. (2022). The Use of Petri Nets in Performance Analysis of Flexible Manufacturing Cell. In: Xu, J., Altiparmak, F., Hassan, M.H.A., García Márquez, F.P., Hajiyev, A. (eds) Proceedings of the Sixteenth International Conference on Management Science and Engineering Management – Volume 1. ICMSEM 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 144. Springer, Cham. https://doi.org/10.1007/978-3-031-10388-9_50
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