Research On Product Mix Decision And Production Mode In Manufacturing Enterprises

In order to meet diversified market demands, spread risks, expand sales, and increase profit, the enterprise would like to produce multiple types of products. So how to make good product mix decision(PMD) is very important. Since it can help the enterprise to get initiative station in the fierce market competition. According to the difference of market demands, the enterprise may use mixed production modes, just like allocating different production modes for different processes of products, so as to make full use of production resource, reduce costs, and improve equipment utilization. In mass production, special tooling, fixture or automation equipments are always used to improve production efficiency, while in single and small batch production, the universal tooling, fixture or equipments are always used to reduce costs. Equilibrium point of production modes should be considered in manufacturing enterprises. The main innovative contributions of the dissertation are as follows:Firstly, based on Activity Based Costing(ABC) theory, a multi-stage absorption method of costs is put forward, the mathematical model of absorption is built. Dalian reducer plant is used as an example to make production cost accounting.Secondly, the capacity accounting method is discussed, and the designed capacity, planned capacity and actual capacity of Dalian reducer plant are analyzed.Thirdly, the definition of equilibrium point of production modes is given, the mathematical model is built to help the enterprise to choose proper production modes.Fourthly, a mixed-product proposal from qualitative analysis is provided. A solution of increasing the products width, strengthening the correlation between products is advanced to enhance market position of the enterprise.Finally, the traditional PMD mathematic model using ABC theory is improved. A model considering mixed production modes is given. The paper provides a global optimal solution within a reasonable time, using the LINGO software. And then this paper gives a comparison of the optimization results with the traditional TOC algorithm, to prove the effectiveness and practicality of this method.