Resiliency in Semiconductor-Based Supply Chains: A Computational Approach to Preventing Supply Shortages

Abstract

This thesis uses a convex optimization model to evaluate the microchip supply chain and manufacturing processes within a closed system. Microchips have become crucial components for the vast majority of electronic products. As such, microchip production has become crucial to a host of other industries, and therefore to economies around the world. Despite microchips’ vital role in the global economy, the demand and supply-side shocks that occurred in 2020 exposed fissures in the microchip supply chain and caused demand bottlenecks. Inadequate production and inventory levels has led to huge economic losses due to the inability to satisfy demand from chip-utilizing goods. Manufacturers’ inability to accurately predict levels of output and demand highlight the intricate nature of the semiconductor-based supply chain. In this paper, we formalize a microchip supply chain on which we apply an optimization model seeking to minimize final production given a desired service level. By running the model with high service levels, this thesis shows how production across the manufacturing process should react in order to cover the total demand and prevent supply shortages for consumers, regardless of uncertainty levels within other aspects of the system.