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Weighted least-square estimation of demand product mix and its applications to semiconductor demand

机译:需求产品组合的加权最小二乘估计及其在半导体需求中的应用

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Estimation of demand product mix is important for effective production plans. Unlike most research in the literature where the product mix is either given or treated as a decision variable in optimization of the production efficiency, this paper focuses on the product mix itself and how to estimate it from the market demand. With more accurate information on the demand product mix, aggregate production plans for product families can be disaggregated into quality detailed plans for individual product items. In this paper, least-square estimates of demand product-mix proportions are first derived. To take into account the effect of the product life cycle, dynamic weighting schemes are then developed to improve the accuracy of the product-mix estimates. For applications, we concentrate particularly on semiconductor demand where new generations of semiconductor products emerge at the pace of every six months, as manifested by the celebrated Moore's laws. The proposed methodologies will be tested with simulated DRAM demands and actual semiconductor demands of different technology generations.
机译:需求产品组合的估算对于有效的生产计划很重要。与文献中大多数将产品组合作为优化生产效率的决定变量来提供或视为决策变量的研究不同,本文重点关注产品组合本身以及如何根据市场需求进行估算。利用有关需求产品组合的更准确信息,可以将产品系列的总体生产计划分解为单个产品的质量详细计划。在本文中,首先得出需求产品混合比例的最小二乘估计。考虑到产品生命周期的影响,然后开发了动态加权方案以提高产品组合估算的准确性。对于应用而言,我们特别关注半导体需求,在这种需求下,每隔六个月就会出现新一代的半导体产品,这就是著名的摩尔定律所证明的。拟议的方法将在模拟的DRAM需求和不同技术一代的实际半导体需求下进行测试。

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