In this research, we model a semiconductor wafer fabrication process as a complex job shop, and adapt a Modified Shifting Bottleneck Heuristic (MSBH) to facilitate the multi-criteria optimization of makespan, cycle time, and total weighted tardiness using a desirability function. The desirability function is implemented at two different levels of the MSBH: the subproblem solution procedure level (SSP level) and the machine criticality measure level (MCM level). In addition, we suggest two different methods of choosing the critical toolgroup at the MCM level: (1) the Local MCM approach, which chooses the critical toolgroup based on local desirability values from the SSP level and (2) the Global MCM approach, which chooses the critical toolgroup based on its impact on the desirability of the entire disjunctive graph. Results demonstrate the desirability-based approaches' ability to simultaneously minimize all three objectives.
- Complex job shop
- Shifting bottleneck
ASJC Scopus subject areas
- Management Science and Operations Research
- Artificial Intelligence