Yield management with downward substitution and uncertainty demand in semiconductor manufacturing
Yield management with downward substitution and uncertainty demand in semiconductor manufacturing
复制标题
半导体制造中向下替代和不确定性需求的良率管理
DOI：
10.1080/00207543.2010.543942
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发表时间：
2012-02
影响因子：
9.2
通讯作者：
韩广华
中科院分区：
文献类型：
--
作者：
董明;邵晓峰;韩广华
由于半导体行业的高产量可变性，最终产品的质量是不确定的，并且在发货前根据性能分为几个质量级别之一。本文研究了某半导体制造企业所面临的两阶段生产到库存系统的动态多周期产量管理问题。在第一阶段，在任何实际需求已知之前，公司投资原材料，并生产多种类型的产品，其收益率随机，因为过程中存在随机性。在第二阶段，根据质量将产品划分为不同的类别，并分配到若干连续的时期。需求也是随机的，可以根据产品级别分为多个类别。当一种产品耗尽时，需求可以升级。本文提出了一个多周期、多产品、向下替代模型，以确定满足需求的最优生产投入和不同产品的配置。生产和分配问题被建模为一个随机动态规划，其目标是使企业利润最大化。我们证明了简单的一步升级替代策略是最优的，目标函数在生产投入上是凹的。设计了一种寻找最优生产投入的迭代算法，并通过数值实验验证了算法的有效性。
Motivated by the high yield variability in the semiconductor industry where the quality of the end products is uncertain and is graded into one of several quality levels according to performance before being shipped. We consider a dynamic multi-period yield management problem of a two-stage make-to-stock system faced by a semiconductor manufacturing firm. In the first stage, the firm invests in raw material before any actual demand is known, and produces multiple types of products with random yield rates because of the presence of randomness in the process. In the second stage, products are classified into different classes by quality, and allocated in a number of sequential periods. Demand is also random and can be classified into multiple classes corresponding to product levels. Demands can be upgraded when one type of product has been depleted. This paper presents a multi-period, multi-product, downward substitution model to determine the optimal production input and allocation of the different products to satisfy demands. The production and allocation problem is modelled as a stochastic dynamic program in which the objective is to maximise the profit of the firm. We show that the simple one step upgrade substitution policy is optimal, and the objective function is concave in production input. An iterative algorithm is designed to find the optimal production input and numerical experiments are used to illustrate its effectiveness.
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DOI：
10.1137/0304018
发表时间：
1966-02
期刊：
Siam Journal on Control
影响因子：
--
作者：
R. V. Slyke;R. Wets
通讯作者：
R. V. Slyke;R. Wets
DOI：
10.1287/msom.4.4.313.5728
发表时间：
2002-10
期刊：
INSEAD Working Paper Series
影响因子：
--
作者：
J. V. Mieghem;N. Rudi
通讯作者：
J. V. Mieghem;N. Rudi
影响因子：
9.2
作者：
Naveen Kumar;Kathryn Kennedy;K. Gildersleeve;Richard Abelson;Christina M. Mastrangelo;Douglas C. Montgomery
通讯作者：
Naveen Kumar;Kathryn Kennedy;K. Gildersleeve;Richard Abelson;Christina M. Mastrangelo;Douglas C. Montgomery
影响因子：
2.3
作者：
Albert Y. Ha
通讯作者：
Albert Y. Ha
影响因子：
2.3
作者：
H. Block;V. Bueno;T. H. Savits;M. Shaked
通讯作者：
H. Block;V. Bueno;T. H. Savits;M. Shaked