Detection of bottlenecks for multiple products and mitigation using alternative process plans
In a manufacturing environment, productivity and quality of the system can be improved by focusing on production constraints (bottlenecks). As a result, the bottleneck detection methods have gained more importance in enhancing the performance of the system. There are several short-term and long-term bottleneck detection methods. This research focuses on inactive state duration bottleneck detection for multiple product flow as high complexity arises in material flow due to several products and different processing sequences. The efficiency of the proposed methodology is validated by case studies using discrete event simulation models. The integration of simulation tool to detect bottlenecks in the manufacturing system has been useful in real-time case studies. An automatic bottleneck detection method was proposed to identify the bottleneck time and bottleneck machines in an easier manner. Previous research focuses on additional capacity and buffers to machines to mitigate the bottleneck. This approach spotlights the selection of alternative process plan in the presence of bottlenecks with a objective of minimized bottleneck time and minimized machining cost of the products in the given process plan. A mathematical model was presented with these objectives. Case studies were conducted for initially selected process plan and alternative process plan to show the improvements in system performance.
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering.