Semiconductor manufacturing is wildly considered as a highly complex process. Its operation management and optimization are challenging for both researchers and practitioners. To address its modelling and scheduling issue, this chapter presents the applications of Petri nets (PNs) to complex system scheduling. After the introduction to basic concepts and extensions of PNs, a hierarchical coloured timed PN (HCTPN) is proposed. To address its scheduling issue, genetic algorithms (GAs) are extended and then embedded into the constructed HCTPN to find optimal/suboptimal schedules. Simulation results based on real-factory scenarios and data are presented. The comparisons 554among different scheduling strategies are made. It is proved that the PN models and GAs can be well combined to solve the complex scheduling problems of semiconductor manufacturing and outperform such policies as empirical rule (E-Rule) and first in first out (FIFO).
|Original language||English (US)|
|Title of host publication||Formal Methods in Manufacturing|
|Number of pages||18|
|State||Published - Jan 1 2014|
All Science Journal Classification (ASJC) codes