Research On Multi-objective Optimal Scheduling For Energy-saving On Mechanical Machining Permutation Flow Line

Green manufacturing, which includes some significant research contents such as reducing energy consumption and improving energy efficiency, is the new requirement of development strategy for manufacturing industry. The mechanical machining manufacturing industry, as an important component for manufacturing industry, has a large number of machine tools and consumes enormous energy. In this field, permutation flow line is a typical production mode. It consists of many machine tools according to a certain process procedure, and a set of workpieces which have the same machining order on each machine tool successively pass through the permutation flow line. Energy-saving production scheduling, as a procedure optimization technology for green manufacturing, can effectively reduce energy consumption of mechanical machining system on the production management level. At present, there are a lot of literatures focused on the energy-saving scheduling issues. However, the study about the energy-saving scheduling for mechanical machining permutation flow line is relatively lacked. Therefore, this paper carries out research on the energy-saving scheduling problem for mechanical machining permutation flow line.Firstly, the structure and the constitution of energy consumption for mechanical machining permutation flow line are analyzed, and the energy-saving principle is revealed, which can effectively reduce total energy consumption of the flow line by using production scheduling to decrease the standby energy consumption of machine tool of the flow line. Based on the above analysis, the architecture of multi-objective scheduling for energy-saving on mechanical machining permutation flow line is established, which includes production planning layer, scheduling layer and worksite information collection layer. It can support the holistic approach study of energy-saving scheduling.Secondly, this paper presents a method of multi-objective scheduling for energy-saving on mechanical machining permutation flow line. A model of multi-objective scheduling for energy-saving is established first, and the optimization objective of this model is to simultaneously minimize the total flowtime of workpieces machining and the total standby energy consumption of machine tools. Since the scheduling of permutation flow line is a well-known NP-hard problem, the non-dominated genetic algorithm 2(NSGA-2) is adopted to solve this problem. Furthermore, the effectiveness of this method is verified by numerical illustration.And then, considering the uncertainty of new workpieces arrival, this paper proposes a method of multi-objective rescheduling for energy-saving on mechanical machining permutation flow line. In this method, a model of multi-objective rescheduling for energy-saving is developed. The optimized multiple objectives of this model are simultaneously minimizing the total flowtime of machined workpieces, the total standby energy consumption of machine tools and the instability influence of rescheduling. Based on it, the NSGA-2 algorithm and the predictive-reactive strategy are introduced to solve this model. The effectiveness of this method of multi-objective rescheduling for energy-saving is verified by simulation experiments.Targeted to the machining mode of mixed-category workpieces, a method for the acquisition of real-time machining task progress is proposed. The method is based on both the power feature of workpiece machining and the incremental learning Lagrangian support vector machine. By analyzing the characteristics of power change during the machining process, the power feature vector, which reflects the characteristics of workpiece machining, is designed. Then, the initial classifier of each category of workpieces is obtained by training a few samples of power feature vector which are from the test machining of workpieces. During the subsequent machining process, the classifiers are updated by incremental learning method, and the workpiece classification and the acquisition of machining task progress are achieved by Lagrangian support vector machine. The effectiveness of this method is empirically tested by application to a case study.Finally, the application system for energy-saving scheduling is detailedly designed. It includes framework, function architecture, running process and data tables etc. Moreover, the phased implementation mode for energy-saving scheduling is presented, which is the integration of production worksite information system and energy-saving scheduling function system. On this basis, combining the sub task of the national science and technology major special project “the network worksite management and intelligent monitoring system for the gear machining automatic production line”, the production worksite information system is developed, which is regarded as the information system for application case. Furthermore, the integration scheme between this information system and energy-saving scheduling function system is designed in order to make preparations for eventually achieving practical application of the energy-saving scheduling.