列车维修人员班次安排:个案研究
Muhammed Abdullah Gençer1, Tamer Eren1, Hacı Mehmet Alakaş1
1Department of Industrial Engineering, Faculty of Engineering and Architecture, Kırıkkale University, 71451 Kirikkale, Turkey.
概括
这项研究通过将故障预测与人员资格相结合,优化了安卡拉地铁列车维护时间表. 新模式确保了公平的班次分配和平衡的工作负载,提高了整体运营效率.
科学领域:
- 运营研究 运营研究
- 铁路工程 铁路工程是指铁路工程.
- 预测性维护是指预测性维护.
背景情况:
- 安卡拉地铁在安排324列列车的维护人员方面面临挑战,影响每月大约1000万乘客.
- 目前的调度没有充分考虑故障预测或人员资格,导致潜在的低效率.
研究的目的:
- 为安卡拉地铁维修人员开发一个优化的班次安排模型.
- 整合日常人员需求,资格和故障预测,以改善调度.
主要方法:
- 在181天内分析了1721个故障数据点,以评估8种预测方法.
- 为30天的故障预测选择了表现最好的预测方法.
- 利用目标编程来确定日常人员需求,并对员工进行分类 (电子,电机械,机械) 以实现平衡的班次分配.
主要成果:
- 优化的日程表显示了每月总工作时间的均分布.
- 班次在员工之间分配得更公平.
- 在有关人员资格的轮班中实现了必要的平衡.
结论:
- 将故障预测与人员资格相结合,大大改善了铁路维护人员的安排.
- 目标编程模型为公共交通运输维护中的多目标调度问题提供了灵活的方法.
- 这项研究为优化铁路维护操作的文献提供了宝贵的见解.
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