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Efficient Due-Date Quoting and Production Scheduling for Integrated Circuit Packaging With Reentrant Processes

机译:具有折返工艺的集成电路封装的有效到期日报价和生产计划

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摘要

The advances in packaging technology in the past decade have overcome a few engineering limitations in integrated circuit (IC) manufacturing. This has greatly complicated the manufacturing process and created a huge challenge in the operations management of the semiconductor back-end production. In particular, the modern demand of lighter and smaller products expedites the multichip packaging technology, which requires reentrant processes and hence makes resource scheduling more difficult. Apart from the fact that IC packaging shares many key features with the semiconductor front-end production, the cycle time of back-end production is significantly shorter than that of the front-end production. Therefore, there is an urgent need of a rapid solution procedure to generate a reliable production schedule for IC packaging. To respond to customer requests efficiently, this paper models the production scheduling of IC packaging as an optimization model and formulates a hybrid genetic algorithm (GA) to solve the problem efficiently. The embedded structure of our model enables the decomposition of the original problems into many small-sized subproblems, which can be solved by available optimization solvers. These subproblems communicate via a master problem, which is solved by a GA to determine the due dates assigned to subproblems. The master and the subproblems are iteratively solved in turn to obtain a satisfactory solution. Computational experiments and an empirical study are performed to validate the efficiency and the feasibility of the proposed approach.
机译:过去十年中,封装技术的进步克服了集成电路(IC)制造中的一些工程限制。这极大地使制造过程复杂化,并且在半导体后端生产的运营管理中提出了巨大的挑战。特别地,对更轻和更小产品的现代需求加速了多芯片封装技术,该技术需要可重入的工艺,因此使资源调度更加困难。除了IC封装与半导体前端生产具有许多关键特性这一事实外,后端生产的周期时间明显比前端生产的周期时间短。因此,迫切需要一种快速的解决方案以生成可靠的IC封装生产计划。为了有效地响应客户需求,本文将IC封装的生产计划建模为一个优化模型,并制定了一种混合遗传算法(GA)以有效地解决该问题。我们模型的嵌入式结构可以将原始问题分解为许多小子问题,这些问题可以通过可用的优化求解器来解决。这些子问题通过主问题进行沟通,而主问题由GA解决,以确定分配给子问题的到期日。依次解决主问题和子问题以获得满意的解决方案。计算实验和实证研究进行以验证该方法的效率和可行性。

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