GOALI: Process Control Approaches to Supply Chain Management in Semiconductor Manufacturing

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A vibrant manufacturing sector is vital to the economic health of the United States, and efficient management of supply chains plays a critical role in this regard. This grant provides funding to explore how Model Predictive Control (MPC), an advanced control paradigm originating from the process industries, can be utilized as a novel approach for tactical decision-making in supply chain management problems associated with semiconductor manufacturing. The project involves the unique collaboration of investigators from chemical engineering, mathematics, and computer science at Arizona State University with a technical leader from Intel Corporation. The principal topic of research is the formulation and initial proof-of-concept of Model Predictive Control algorithms for a novel class of supply chain problems associated with semiconductor manufacturing that extend beyond chemical process applications and traditional MPC. To this end, the use of state-of-the-art optimization techniques that efficiently solve the optimization problems associated with Model Predictive Control, and the development of a software architecture that can satisfy the unique computational needs of this class of supply chain problems, will be examined.It is expected that the Model Predictive Control-based formulations developed as part of this research will ultimately serve as integral components in hierarchical, enterprise-wide planning tools that function on real-time data, support varying levels of information sharing and centralization, and employ combined feedback-feedforward control action. Broader impacts of this research include efforts towards developing a body of theory and technology meaningful not only to semiconductor manufacturing, but to a wide range of discrete-part manufacturing industries of importance to the national economy. Ongoing efforts by the PIs to involve minority and undergraduate students in integrative research and educational activities, as well as the dissemination of research outcomes to the engineering community at large, will be further stimulated as a result of this grant.