An Intelligent Design Method for Remanufacturing Considering Remanufacturability and Carbon Emissions

Abstract

Design for remanufacturing (DfRem) is to consider the remanufacturability of the product at the design stage, which can improve the remanufacturability of the product. Moreover, the DfRem solution has a significant impact on the carbon emissions of manufacturing processes. Unreasonable design solutions can significantly increase carbon emissions from manufacturing processes. However, there is no direct link between DfRem solutions and remanufacturability as well as manufacturing carbon emissions, which makes it difficult to quickly generate a rational DfRem solution that can enhance product remanufacturability and reduce carbon emissions simultaneously. To this end, this paper proposes an intelligent design method for remanufacturing that considers remanufacturability and manufacturing carbon emissions. First, an intelligent DfRem framework is constructed, which includes information acquisition, virtual model construction of the DfRem solution, and multi-objective optimization of the design solution. Then, the design matrix and sensitivity analysis are used to construct the mapping models between remanufacturability, carbon emissions, and DfRem parameters. Meanwhile, a multi-objective optimization model of DfRem with remanufacturability requirements and carbon emissions as design objectives is constructed, and an adaptive teaching and learning optimization algorithm is applied to solve the optimization model to obtain a DfRem solution that satisfies the objective information. Finally, the feasibility of the method is verified by DfRem of the injection mold as an example.