Integrated Optimization Of Process Planning And Shop Scheduling For Reducing Manufacturing Carbon Emissions

With global warming, environmental problems have been worldwide attention, and low carbon manufacturing, as a kind of new sustainable manufacturing mode, can effectively reduce the emissions of greenhouse gasses and mitigate climate change. Process planning and shop scheduling are two important parts of which affect the carbon emissions of manufacturing process. Therefore, the research on process planning and shop scheduling optimization for low carbon is of great significance for reducing the carbon emissions of manufacturing process. In the traditional study on low carbon, usually process planning and shop scheduling are regarded as independent subsystems which are studied separately. Shop scheduling is always performed after Process planning has been schemed, lacking handle of the mechanism of mutual influence and conflict between process planning and shop scheduling coordinately. So this article will integrate process planning and shop scheduling aimed at reducing the carbon emissions of manufacturing process.First the composition of carbon emissions in manufacturing process is analyzed in detail, and the different influence of process planning and shop scheduling on the different carbon emissions of manufacturing process is also analyzed, and the influence mechanism of process planning and shop scheduling for each carbon source is explored. Based on this, in order to further reduce carbon emissions in manufacturing processes, make up for the defect that the influence of processing methods and process route of each workpiece in process planning on machine allocation, handling distance and processing sequence in scheduling are ignored when process planning and shop scheduling are optimized separately, a multi-objective integrated optimization model of process planning and shop scheduling are proposed aiming at minimizing carbon emissions of manufacturing process and makespan to optimize process method of each machining characteristic, process route of each workpiece, processing sequence and machine allocation of each process at the same time.Then, because there are many parameters to be optimized in the proposed multi-objective integrated process planning and shop scheduling optimization model, such as workpiece machining method, process route and order the workpiece and the distribution process of machine tool, and they are interactional, can't exist independently, a four-segment encoding method is designed to code the related parameters. A Non-Dominated Sorting Genetic Algorithm-II(NSGA-II) algorithm is designed to solve the proposed model.Afterwards, according to the proposed multi-objective integrated process planning and shop scheduling low-carbon optimization model, three workpieces are selected to specific analysis, and the four-segment encoding NSGA-II algorithm is designed to solve this problem. Combining with the actual experimental data, by comparing with results of current separated optimization method of process planning and scheduling, and some others related analysis, the effectiveness of proposed integrated optimization model on reducing carbon emissions in manufacturing processes is validated.Finally, the work of the whole paper is summarized. The deficiency of the study and which aspects can be improved the future research direction is analyzed and put forward.