In order to help manufacturing companies quantify and reduce product carbon footprints in a mixed model manufacturing system, a product carbon footprint-oriented multi-objective flexible job-shop scheduling optimization model is proposed. The production portion of the product carbon footprint, based on the mapping relations between products and the carbon emissions within the manufacturing system, is proposed to calculate the product carbon footprint in the mixed model manufacturing system. Nondominated sorting genetic algorithm-II (NSGA-II) is adopted to solve the proposed model. In order to help decision makers to choose the most suitable solution from the Pareto set as its execution solution, a method based on grades of product carbon footprints is proposed. Finally, the efficacy of the proposed model and algorithm are examined via a case study.

Issue Section:
Research Papers
Keywords:
flexible job-shop scheduling, carbon footprint, carbon emission, nondominated sorting genetic algorithm
Topics:
Carbon, Emissions, Machine shops, Manufacturing, Machinery, Machine tools

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