Research on Enterprise Spare Parts Production Decision System Based on Decision Tree

Most enterprises in the market need to purchase spare parts for assembly. The qualification of the finished products depends on the quality of the spare parts. The unqualified quality of any single spare part will lead to the disqualification of the finished product. However, even if all the spare parts are qualified, the finished product may still be unqualified due to other factors. Therefore, how to select spare parts has become a decision-making dilemma for enterprises. This paper will establish a multiple linear regression model to predict the cost of spare parts. On this basis, the decision tree algorithm is used to efficiently determine the quality status of spare parts, enabling enterprises to make more scientific and accurate production decisions for spare parts. This helps enterprises achieve strategic goals of cost reduction, quality improvement, and benefit maximization in the fierce market competition, laying a solid foundation for the sustainable development of enterprises.