REPRESENTATION, SIMULATION AND CONTROL OF MANUFACTURING PROCESS WITH DIFFERENT FORMS OF UNCERTAINTIES

This paper suggests a new methodology for effectively describing and analyzing manufacturing processes with uncertainties. Uncertain information in the form of variance and vagueness are captured using probability distribution and fuzzy logic. The captured uncertainties are incorporated into a new Petri Net model referred to as Fuzzy colored Petri Net with stochastic time delay (FCPN-std). Through FCPN-std, general manufacturing uncertainties such as unclear operation rules, unfixed re-source plan and processing time variances can be incorporated. This paper focuses on how FCPN-std model is generated and simulated for analyzing system performances. The procedure is illustrated using an example process. The main advantages of FCPN-std model are in the ability to capture and analyze manufacturing uncertainties, and provide an opportunity to im-prove process performance in the presence of uncertainties. These characteristics help modelers design exactly manufactur-ing process without approximations/ignorance and guide how manufacturing process can be improved through incorporated information.