Abstract
Due to the rapid change of the market and decision flexibilities of intelligent manufacturing, TFT-LCD industries are facing the challenges of a huge number of customers and different kinds of products. Therefore, it is important to enhance productivity as well as remain product quality. Because photolithography stage is the bottleneck, this study focuses on photolithography scheduling which considers job arrivals. To deal with the uncertainty of arrival time, this study develops Two-phase Decoding Genetic Algorithm (TDGA) combined with rolling strategy for dynamic scheduling in photolithography stage under complex restrictions. TDGA can also avoid the reworked problem and load unbalancing through the design of chromosome. For validation, TDGA is also compared with GA which has the left-shift mechanism through empirical data from a leading TFT-LCD industry in Taiwan. The experimental result shows that TDGA can shorten the idle time between jobs. It can obtain a high quality solution with 99% machine utilization. Thus, TDGA performances better than GA in all scenarios.