Optimization decomposition of manufacturing tasks and equipment cycle ordering based on cost control

Abstract

In the manufacturing process, there are a large number of complex tasks, and refining them into smaller subtasks can better handle and schedule them. By dividing tasks into smaller units and understanding the characteristics and requirements of each subtask, targeted control and optimization can be carried out. Reasonably arranging the procurement and usage cycle of equipment based on changes in demand and production capacity can avoid waste caused by idle and excessive use of equipment, and maximize the utilization of equipment resources to reduce production costs. The aim of this study is to explore the method of manufacturing task optimization decomposition and equipment cycle ordering based on cost control, in order to optimize the cost-effectiveness of the manufacturing process. The task decomposition and equipment cycle ordering process are abstracted into mathematical models, and corresponding optimization objectives and constraints are formulated based on the characteristics of the models. Then, optimization algorithms are used to solve the model and find the optimal task decomposition and equipment cycle ordering strategy. The experimental results show that the use of cost control based manufacturing task optimization decomposition and equipment cycle ordering methods has achieved significant improvements in cost-effectiveness.