An optimal policy for a lean supply chain control problem considering forecast accuracy

Since the automotive sector is a particularly powerful driver of growth for the semiconductor industry, some semiconductor companies are focusing on the automotive industry as a key market. This research gives an introduction to semiconductor products and their production. The current business conditions and challenges in a company at the time of research are presented, and the causes and effects on the semiconductor supply chain in terms of semiconductor inventory management are examined. This research focuses on problem formulation and solution procedures for inventory planning using Markov decision process models to recommend the decisions regarding finished goods inventory in a supply chain with stochastic demand. We first identify a Markov decision problem for an inventory model considering the chain's state space, transition probabilities and cost structure, and then obtain the optimal control policy that minimizes the expected cost under stochastic variability.