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In the dynamic manufacturing landscape, efficient scheduling of parallel plastic injection machines is critical for optimizing production efficiency, minimizing resource wastage, and enhancing sustainability. This study addresses inefficiencies in manual job scheduling at a leading electrical components manufacturer, with a focus on extended setup times and significant raw material losses during frequent color changes. The proposed solution uses Goal Programming techniques—specifically Weighted Goal Programming, Tchebychev Goal Programming, and Lexicographic Goal Programming—to develop an optimal scheduling model. The focus is on minimizing raw material loss and total setup time. All instances of the problem were solved using IBM ILOG CPLEX Version 22.1, ensuring robust and efficient solutions. This study aims to establish a benchmark for sustainable manufacturing practices by comparing these different Goal Programming approaches in terms of efficiency and effectiveness in real-world scheduling problems.

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Scheduling for Parallel Plastic Injection Machines: A Sustainable Approach Using Goal Programming

  • 会议论文

  • 发表日期：

    2025年

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  • Beril Durmaz,
  • Ferit Doğruel,
  • Beste Atasolmaz,
  • Doruk Dumlu,
  • Seray Tütüncü,
  • Mert Paldrak,
  • Efthymia Staiou

摘要

In the dynamic manufacturing landscape, efficient scheduling of parallel plastic injection machines is critical for optimizing production efficiency, minimizing resource wastage, and enhancing sustainability. This study addresses inefficiencies in manual job scheduling at a leading electrical components manufacturer, with a focus on extended setup times and significant raw material losses during frequent color changes. The proposed solution uses Goal Programming techniques—specifically Weighted Goal Programming, Tchebychev Goal Programming, and Lexicographic Goal Programming—to develop an optimal scheduling model. The focus is on minimizing raw material loss and total setup time. All instances of the problem were solved using IBM ILOG CPLEX Version 22.1, ensuring robust and efficient solutions. This study aims to establish a benchmark for sustainable manufacturing practices by comparing these different Goal Programming approaches in terms of efficiency and effectiveness in real-world scheduling problems.