Energy Consumption Optimization And Exergy Loss Assessment Method For CNC Machining Process

Energy and resource are consumed with increasingly serious environment pollution when the materials are processed and used. At present, low energy utilization efficiency of machinery manufacturing enterprise in our country is a serious problem, and environmental pollution caused by resources consumption is also a serious problem. Energy problem has become a strategic issue for economic development of China. Energy-saving and optimization of manufacturing process is the basis of sustainable manufacturing, and is the embodiment of sustainable development strategy in the manufacturing industry. Therefore, improving energy utilization efficiency and reducing resources waste of machinery manufacturing enterprises have great significance.The two dimensional relationship between cutting parameters and energy consumption of machine tools is established considering energy consumption of spindle rotation. Based on the establishment of cutting energy monitoring platform, the change rule of cutting power of machine tools under different processing states and cutting parameters is studied. The energy consumption model is established using the combination of theoretical analysis and empirical modeling. The coefficients of energy consumption model are obtained through cutting experiment and energy data fitting. The values of the model coefficients are clearly defined, which will be easy to obtained and used in practice. Finally, milling experiment is performed for verification of energy consumption model. Experimental results show that the proposed model is able to provide a reliable prediction of energy consumption for given process parameters with a high accuracy. This study will provide basic knowledge for energy-efficient optimization, environmental impact assessment, energy consumption dynamic simulation of manufacturing process.With cutting energy consumption as one objective of cutting parameters optimization, a multi-objective optimization method is proposed based on the trade-offs between cutting energy, productivity and machining quality. The weighted grey relation analysis theory is used to solve the multi-objective optimization problem. A weight distribution method is proposed according to the influence degree of cutting parameters’ variations on optimization objectives. Finally, the proposed optimization method is validated through the orthogonal experiment to increase production rate and cutting quality combined with the decrease of cutting energy consumption in a given cutting parameters range. Meanwhile, cutting parameters of each machine are allowed to vary to affect the processing time and energy consumption. A bi-level optimization method for energy-efficient hybrid flow shop(HFS) scheduling is proposed, which incorporates the established energy model of single machine and cutting parameters optimization into the energy-efficient scheduling problem. The case study for a HFS is presented to demonstrate the applicability of the proposed bi-level optimization method. The scheduling results show that the bi-level optimization method is effective in assisting schemes selection to provide theoretical and technical support for sustainability oriented optimization of machine tools and workshop.Based on the established energy model, the exergy loss assessment method of machining process is proposed considering both energy and material flows. In view that few studies have addressed energy and material flows using a common perspective, the exergy losses of cutting activities, compressed gas loss, tool wear, cutting fluid consumption and metal scraps produced are analyzed. The quantitative relationship between exergy loss and cutting parameters is established. Energy and material flows are viewed using the same metric in this relationship. Specific exergy loss is used as index of environmental impact to solve the trade-off problem of different factors, such as electricity consumption, tool wear, cutting fluid consumption etc. To demonstrate the applicability and effectiveness of the method, a case study is considered in which a milling tool path is selected to minimize exergy loss. Another milling experiment with different cutting parameters shows that the larger feed rate and lower spindle speed can effectively reduce the specific exergy loss. This work provides an important theoretical support for the target to improve the efficiency of energy utilization and reduce resource consumption for CNC machining process.A dynamic cutting simulation system for energy consumption prediction is developed based on the above mentioned energy consumption model, which can assist manufacturers to make quick and efficient decisions before the workpiece is processing.The function modules of the dynamic simulation system are designed, and the relationship between the various modules is analyzed to show the working process of the simulation system. Finally, the applicability of the simulation system is verified through the experiment of designed energy consumption test workpiece to provide an accurate evaluation of energy consumption effectively.