Semiconductor: Incorporating Nonlinear Phenomena in Semiconductor Supply Chain Planning Models

该基金支持由NSF和半导体研究公司（SRC）共同发起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。联合研究将研究一系列改进和扩展研究者先前使用非线性清空函数（CFs）的生产计划模型的工作，CFs将资源的预期吞吐量表示为预期在制品库存（WIP）的凹函数。大量的计算实验表明，该模型能够捕获制造环境中资源利用率和交货时间之间的相互作用，同时保留大规模使用的可追溯性。新的研究将解决如何在没有模拟负担的情况下将CFs应用于各种工作中心，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，其中的每一个都已被证明会显著影响拥塞、吞吐量和交货时间。这项新研究将尝试利用cf公式的灵活性，推导出一个综合的多时期规划模型，将这三者结合起来。在高科技、资本密集型行业，如半导体制造业、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程序已多次显示出显著的效益。然而，大多数适合大规模应用的方法都无法模拟实际操作的拥塞和前置时间动态。这项研究的成功将使已经很有前途的CF方法更容易对大型和复杂的操作进行建模，并结合目前外部处理的其他问题。结果可能是关键制造业的生产率和服务水平的显著提高。

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.