Discrete lot sizing and scheduling problem under batch processing constraints in the semiconductor manufacturing
Discrete lot sizing and scheduling problem under batch processing constraints in the semiconductor manufacturing
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DOI：
10.1007/s00170-013-5028-4
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发表时间：
2013-05
期刊：
影响因子：
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通讯作者：
Jun-Ho Lee;Sun Hoon Kim;Young Hoon Lee
中科院分区：
文献类型：
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作者：
Jun-Ho Lee;Sun Hoon Kim;Young Hoon Lee
在具有各种特性和要求的系列设备上制造高技术产品。例如，有机发光二极管的沉积工艺在腔室中进行长的制造时间，而属于同一系列的各种产品器件可以在预防性维护计划或所需化学气体的再填充之前依次处理。沉积工艺是一个瓶颈，其生产效率对上游低温多晶硅工艺以及下游封装和组件工艺至关重要。在考虑产品系列设置、批量大小、补充掩模工具要求和材料耗尽要求的情况下，使用混合整数规划（MIP）来制定批量产品系列调度问题。结果表明，计划和调度决策可以同时在一个集成的模型，它可以在实际的生产线上实施。通过优化模型分析，在不损失吞吐量和需求满足的情况下，可以将容量提高20 ~ 30%。
Highly advanced technology products are manufactured on the series of equipment having various characteristics and requirements. The deposition process of organic light emitting diode, for example, is performed in chambers for a long manufacturing time, while various product devices belonging to the same family can be processed in sequence before the preventive maintenance schedule or the refill of chemical gas required. The deposition process plays as a bottleneck, and its productivity of the schedule is critical to the upstream low-temperature poly silicon process and the downstream encapsulation and module processes as well. The batch family scheduling problem is formulated using the mixed-integer programming (MIP) in consideration of the family setups, lot sizing, supplementary mask tools requirements, and material exhaustion requirements. It is shown that the planning and scheduling decisions can be made simultaneously in an integrated model, and that it can be implemented in the actual manufacturing line. Through the optimized model analysis, the capacity can be enhanced by 20∼30 % without losing the throughput and demand satisfaction as well.