Research On Calculation And Optimization Of Product Carbon Footprint In Manufacturing Process

Environmental problems have caused worldwide attention. The product carbonfootprint will be an important basis for product to pay its carbon tax in a low-carboneconomy market and also one of the important factors affecting the marketcompetitiveness of product. Therefore, research about the quantification and optimizationof the product carbon footprint has an important help and practical significance to improvethe competitiveness of companies in the low-carbon market and be response to nationalenvironmental policy.Research on the calculation of product carbon footprint exist some problems such asthe lack of basic data and the system boundary is not clear, while all of these are importantfactors affecting the accuracy of calculation results of product carbon footprint. In order tosolve problem that the calculation of product carbon footprint is not accuracy, and alsoprovide accuracy basic data of product carbon footprint in manufacturing process todownstream enterprises, a calculating method of product carbon footprint inmanufacturing processes which is based on distribution relations between carbonemissions in manufacturing processes and products manufactured is proposedIn the actual manufacturing process, the processing path of product and the order ofproduct processed on a machine will be changed when the scheduling is changed, theresult will not only affect the completion time, but also affect the product carbon footprintin manufacturing process. In order to optimize the product carbon footprint inmanufacturing processes under the premise of ensuring the completion time, amulti-objective flexible job-shop scheduling model aiming at minimizing the total productcarbon footprint in manufacturing processes, minimizing complete time and maximizingequipment utilization is proposed by combining the calculation model of product carbon footprint in manufacturing process with the traditional shop scheduling optimizationmodel. NSGA-II(Non-Dominated Sorting Genetic Algorithm-II) is designed to solve themodel. In order to ensure most of the product carbon footprint could be optimized by thefinal solution, a product carbon footprint rank based method is proposed to choose theexecuting solution. The effectiveness of the processing efficiency and reducing theproduct carbon footprint has been verified by applying the optimization model to a shaftparts machining workshop.Finally, the summary is presented and the future research direction is outlined.