Research On Production Scheduling Method For Flexible Assembly Process Of Mechanical Product

In recent years, production manufacturing enterprises are changing gradually from the production of traditional single-species and large batch to multi-species and low batch. Due to the changes of species and batch, various problems are fond in the process of carrying out the flexible assembly, including the changeover time in the assembling process, the increasing production cost and the extension of delivery time caused by the increasing preparation time. In order to improve the ability that the production manufacturing enterprises response to the demand of the customers and improve customer loyalty, the concept of customer satisfaction widely used in service industry is introduced into the research on production scheduling method for flexible assembling process of mechanical product. Customer satisfaction is always the research focus of the scholars in retail/service industry, and this is decided by the nature of the industry. Similarly, orders obtained by the manufacturing enterprises are understood as service and the customer satisfaction is taken as the breakthrough. By the research of customer satisfaction and its evaluation model, several kinds of indices applied to customer satisfaction evaluation are summarized. Combined with the characteristics of the relationship between manufacturing enterprise and customer, delivery time, price and quality are selected as the evaluation indices. On this basis, a scheduling multi-objective optimization model based on customer satisfaction is constructed. Multi-objective simulated annealing algorithm is applied to solve the model. And aimed at the lack that the stop criterion of the simulated annealing algorithm, the improvement of the two simulated annealing algorithm is summarized. At last, with the help of Visual studio.NET a product-assisted system with the functions of production planning and scheduling is developed. And the system not only improves the execution efficiency of the production planning, but also provides an effective reference for the practical application of the model.