Job shop bottleneck detection based on orthogonal experiment

  • Authors:

  • Yingni Zhai;Shudong Sun;Junqiang Wang;Ganggang Niu

  • Affiliations:

  • Institute of System Integration and Engineering Management, Northwestern Polytechnical University, Xi'an 710072, China and Key Lab. of Contemporary Design and Integrated Manufacturing Technology, ...;Institute of System Integration and Engineering Management, Northwestern Polytechnical University, Xi'an 710072, China and Key Lab. of Contemporary Design and Integrated Manufacturing Technology, ...;Institute of System Integration and Engineering Management, Northwestern Polytechnical University, Xi'an 710072, China and Key Lab. of Contemporary Design and Integrated Manufacturing Technology, ...;Institute of System Integration and Engineering Management, Northwestern Polytechnical University, Xi'an 710072, China and Key Lab. of Contemporary Design and Integrated Manufacturing Technology, ...

  • Venue:
  • Computers and Industrial Engineering
  • Year:
  • 2011

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Abstract

A new prior-to-run bottleneck detection method based on orthogonal experiment (BD-OE) is proposed for job shop from the perspective of scheduling. It is built according to a new bottleneck definition which is proposed based on the principle of ''Bottlenecks determine the performance of manufacturing systems'' in TOC. The method takes the scheduling objective as estimated index, and constructs orthogonal trials by orthogonal array and dispatching rules to detect the bottleneck machine which has the greatest effect on the estimated index. It can detect the bottleneck machine before manufacturing systems run, and guide the following production process for the improvement of the performance of manufacturing systems. In order to evaluate the performance of the proposed method, different scales of job shop scheduling instances and two existing bottleneck detection methods are selected for simulation. The results show that the prior-to-run bottleneck detection method is feasible, efficient and easily implemented.