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Sequencing production orders is crucial in high-mix, low-volume job shop manufacturing environments. This study aims to identify the best sequencing rule to enhance manufacturing performance in a company with three CNC milling machines. Five sequencing rules—Earliest Due Date (EDD), Shortest Processing Time (SPT), Shortest Processing and Setup Time (SPST), Geometric Mean of Processing Time and Due Date (GMPD) and Harmonic Mean of Processing Time and Due Date (HMPD)—were evaluated. Stochastic machine breakdown and setup times were modelled using EasyFit software. Ten production orders with varied products and quantities were simulated using WITNESS software. Performance was measured by total completion time, average work-in-progress and machine busyness. The results were compared to the current system without sequencing rules to determine the optimal approach.

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Sequencing and Simulation of Production Orders in a Job Shop Manufacturing Company with Stochastic Machine Breakdown Time and Setup Time

  • 会议论文

  • 发表日期：

    2025年

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  • Che Ying Lee,
  • Kuan Yew Wong

摘要

Sequencing production orders is crucial in high-mix, low-volume job shop manufacturing environments. This study aims to identify the best sequencing rule to enhance manufacturing performance in a company with three CNC milling machines. Five sequencing rules—Earliest Due Date (EDD), Shortest Processing Time (SPT), Shortest Processing and Setup Time (SPST), Geometric Mean of Processing Time and Due Date (GMPD) and Harmonic Mean of Processing Time and Due Date (HMPD)—were evaluated. Stochastic machine breakdown and setup times were modelled using EasyFit software. Ten production orders with varied products and quantities were simulated using WITNESS software. Performance was measured by total completion time, average work-in-progress and machine busyness. The results were compared to the current system without sequencing rules to determine the optimal approach.