Semiconductor: Incorporating Nonlinear Phenomena in Semiconductor Supply Chain Planning Models

这笔赠款支持由NSF和半导体研究公司(SRC)共同赞助的一个联合项目的科学和数学方面，数据收集、验证和测试由SRC单独支持。这项联合工作将调查对调查人员先前使用非线性结算函数(CFS)在生产计划模型上所做的一系列改进和扩展，CFS将资源的预期生产能力表示为预期在制品库存(WIP)的凹函数。大量的计算实验表明，该模型能够捕捉制造环境中资源利用率和提前期之间的相互作用，同时保持了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CFS适应于不同的工作中心，并增强模型，以包含影响复杂生产操作动态的三个新元素：批量/设置、安全库存和动态/促销定价。单独来看，这其中的每一个都被证明对拥塞、吞吐量和交货期有显著影响。这项新的研究将试图利用CF配方的灵活性来得出一个整合了这三个因素的综合多阶段计划模型。在高科技行业，半导体制造、全球供应链、较短的产品周期和快速变化的市场状况等资本密集型行业使得有效的供应链协调成为成功的必要条件。支持这种协调的全公司生产计划模型的应用已多次被证明产生了显著的好处。尽管如此，大多数适合大规模应用的方法无法对实际操作的拥塞和提前期动态进行建模。这项研究的成功将使已经很有前途的CF方法更好地为大型和复杂的操作建模，以及纳入目前由外部处理的其他问题。其结果可能是关键制造业的生产率和服务水平显著提高。

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.