Scheduling problems have been studied extensively over the years. Broad ranges of focus areas exist, from optimization to heuristics, production planning to production sequencing, customized algorithms to general-purpose algorithms, simple machines to complex environments, etc.
In this research, a heuristic approach has been proposed to overcome the scheduling problem on a complex flexible job shop (called T-Line) found at a manufacturer of commercial building products (called LLC). The job shop environment consists of single and parallel machines with and without sequence-dependent setup times, parallel batching machines with incompatible job families and p-batching, precedence constraints, non-zero release dates, and due dates. The research is aimed at sequencing production orders in near-real-time, primarily to minimize total tardiness, but also to reduce total setup time. A layered Shifting Bottleneck Procedure (SBP) is employed, with the top layer determining release dates and due dates for individual jobs, and the bottom layer applying algorithms to individual work centers. Each bottom-layer algorithm is drawn from literature, revised from an existing method, or inspired by existing methods.
The outcome of this research is a better T-Line production schedule than current methods with minimal computation cost. The SBP framework performs well, and could be applied to other production areas in LLC. The individual algorithms are modular, allowing them to be added to or removed from the framework with minimal effect to other algorithms in the framework. Future endeavors will involve building this heuristic into LLC’s ERP system and possibly expanding it to other production areas.
|Commitee:||Chen, Xin, Cho, Sohyung|
|School:||Southern Illinois University at Edwardsville|
|Department:||Mechanical and Industrial Engineering|
|School Location:||United States -- Illinois|
|Source:||MAI 56/06M(E), Masters Abstracts International|
|Keywords:||Bottleneck, Manufacturing, Shifting|
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