The Process-based Modeling Method For Cost Analysis And Control In Mechanical Manufacturing Enterprises

Nowadays, the mechanical manufacturing enterprises are facing a more fierce competition and their pressure on cost control is intensified. The need for enhancing cost analysis and cost control has increased to improve their competitiveness. In this research, a process-based modeling method for cost analysis and control in mechanical manufacturing enterprises is presented and then studied. This work is supported by the National Natural Science Foundation of China under Grant No.61074136.First, a process-based approach for cost calculation based on material flow tracing is presented. On the basis of activity tracing, a material flow tracing model is established. Then, the costs of products consumed in their manufacturing process are classified and a hierarchical model for cost allocation is set up. Thus, the production state is timely captured and the traceability of cost is improved. This approach has a higher accuracy in cost calculation than the traditional non-process-based approaches, and it can provide more reliable cost information for product profit analysis.Second, a process-based model for product cost estimation is set up. The complexity of cost consumption relationships in a manufacturing environment is discussed. Through utilizing the input-output analysis method, the complex consumption relationships are expressed, and then the consumption characteristics of all production activities (mainly presented by the activity rates) are extracted by solving these relationships. Subsequently, the mapping relationship from product design parameters to processing parameters for cost estimation is established. Thus, the detailed cost consumption of a new product in its manufacturing process can be directly estimated from its design feature parameters.Third, a process-based standard cost control model is established. Through utilizing the data envelopment analysis (DEA) method, the cost efficiency of each production activity is evaluated. The process data with low efficiency are found and excluded, thus a feasible and stimulating process-based cost standard is determined. Then, comparing the actual data with the standard data, a mathematical model for analyzing the cost variances and its variability is established. The cost variances in manufacturing process are decomposed, and the variability of cost consumption in manufacturing process is also analyzed for enhancing the cost control. Forth, a process-based cost optimization model is presented and its solution method is discussed. In a manufacturing environment of a job shop, a mathematical model for resource configuration adjustment and cost optimization is established, and the goal is to minimize its total manufacturing and tardiness cost. A manufacturing process simulation model is constructed to evaluate the performance of each resource configuration adjustment properly. Then by combining the production simulation method and improved simulated annealing algorithm, a heuristic algorithm for solving the problem is designed. In the proposed algorithm, the search and selection of neighbor configuration alternatives is guided by the critical production path analysis. It can gain better solution quality and efficiency than the traditional random search method, thus is more suitable for modeling and solving the relatively large-scale problem in practice.Finally, a cost information management system is developed with the above models. The system has been applied in Dalian Refrigeration Co. Ltd. of China, which is a typical large mechanical manufacturing company. The effectiveness of the models is verified. The work of this research builds a theoretical foundation for the process-based cost calculation, estimation and control in the manufacturing environment. It can provide supports to manufacturing enterprises for enhancing their cost management and cost control.