Optimization Problem For The Assembly Line Subject To Workers With Different Skills

Discrete manufacturing industry plays an important role in China, which is regarded the world factory. The development of discrete manufacturing industry has a great direct effect on our national economy. Driven by the severe competition in the market, quality, cost, delivery date has become the major factor influencing core competitiveness of discrete manufacturing industry. However, whether the assembly line of the discrete manufacturing industry is optimal, directly affects these three major factors. Because the orders accepted by these discrete manufacturing enterprises have such distinguishing features as small batch size, early delivery date, and random arrival, resulting in frequent production replacement; While most assembly lines are designed simply by experience, giving rise to generally low rate of output in these discrete manufacturing enterprises. This phenomenon hinders these enterprises from reducing cost, improving delivery accuracy and efficiency. Therefore, it is essential to find a method to optimize assembly line considering the personnel capacity variance suitable for discrete manufacturing enterprises.Taking a package manufacturing enterprise in Guangdong province as the background, this paper concludes and applies diverse theories and methods, and proposes a method to optimize assembly line considering the personnel capacity variance suitable for discrete manufacturing enterprises.In this research, Firstly, Based on the investigation of that enterprise, fully analyze the factors influencing the balance of assembly line, taking the minimization of Tact in assembly line as the optimizing target, build a mathematical model to optimize assembly line considering the personnel capacity variance; Secondly, propose optimizing algorithm for problems of in large and small scale respectively, that is an overall optimizing algorithm which can work out an accurate solution for the small scale problem, while a divisional heuristic algorithm which can work out an approximate solution for big scale problem; Thirdly, in order to assess the optimizing results, propose a measure for find optimal upper and lower bounds, and make analysis of the measure with calculation example both in large and small scale; Finally, based on the actual production situation of that enterprise and the algorithms stated above, develop and design a system to optimize the assembly line suitable to the enterprise, and validate the practicability of the system with application examples.