Semiconductor: Incorporating Nonlinear Phenomena in Semiconductor Supply Chain Planning Models

半导体：将非线性现象纳入半导体供应链规划模型

• 批准号: 0432440
• 负责人: Reha Uzsoy
• 金额: --
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0432440&HistoricalAwards=false
• 关键词: Semiconductor; Incorporating; Nonlinear; Phenomena; Supply

The grant supports scientific and mathematical aspects of a joint project co-sponsored by NSF and the Semiconductor Research Corporation (SRC), with data-gathering, validation and testing supported separately by SRC. The combined effort will investigate a series of refinements and extensions to the investigators prior work on production planning models using nonlinear Clearing Functions (CFs), which express the expected throughput of a resource as a concave function of the expected work in process inventory (WIP). Extensive computational experiments have shown that this model is capable of capturing the interaction between resource utilization and lead times in manufacturing environments while retaining the tractability for large-scale use. New research will address how CFs can be fitted to various workcenters without the burden of simulations and enhance the models to encompass three new elements impacting the dynamic of complexity production operations: lot-sizing/setups, safety stock, and dynamic/promotional pricing. Taken separately, each of these has been shown to significantly impact congestion, throughput, and lead times. The new research will attempt to exploit the flexibility of CF-formulations to derive an integrated multiperiod planning model incorporating all three.In high-technology, capital-intensive industries such as semiconductor manufacturing, global supply chains, short product cycles and rapidly changing market conditions render effective supply chain coordination a requirement for success. Applications of company-wide production planning models that support this coordination have been repeatedly shown to yield significant benefits. Still, most methods tractable enough for large-scale application are unable to model the congestion and lead-time dynamics of real operations. Success in this research will make the already promising CF approaches more ready to model large and complex operations, as well as incorporating other issues now handled externally. The result could be a significant improvement in productivity and service levels of critical manufacturing industries.

该赠款支持由NSF和半导体研究公司（SRC）共同赞助的联合项目的科学和数学方面，SRC分别支持数据收集，验证和测试。 联合的努力将调查一系列的改进和扩展的调查人员以前的工作，生产计划模型使用非线性结算功能（CF），表示的预期吞吐量的资源作为一个凹函数的预期工作在过程中的库存（CFs）。大量的计算实验表明，该模型能够捕捉资源利用率和交货期之间的相互作用，在制造环境中，同时保持大规模使用的易处理性。 新的研究将解决如何在没有模拟负担的情况下将CF安装到各种工作中心，并增强模型，以包含影响复杂生产运营动态的三个新元素：批量/设置，安全库存和动态/促销定价。 单独来看，这些因素中的每一个都被证明会显着影响拥塞，吞吐量和交货时间。新的研究将试图利用CF公式的灵活性，以得出一个综合的多周期规划模型，将所有三个。在高科技，资本密集型产业，如半导体制造，全球供应链，短产品周期和快速变化的市场条件，使有效的供应链协调的成功的要求。 支持这种协调的全公司范围的生产计划模型的应用已多次被证明产生显着的好处。 尽管如此，大多数易于处理的大规模应用的方法是无法建模的拥塞和提前期动态的真实的操作。 这项研究的成功将使已经很有前途的CF方法更容易建模大型和复杂的操作，以及纳入其他问题，现在外部处理。 结果可能会显着提高关键制造业的生产力和服务水平。