An integrated product modularity method based on transfer network of failure mode‐recycling decision for remanufacturing

Abstract

The product modularity has an important influence on the whole product life cycle. In order to improve product recovery of a used product at the end‐of‐life stage, it is imperative to develop modular product architecture with remanufacturing strategies consideration. In this paper, an integrated modular design method for green remanufacturing considering hierarchical structure of the product and fuzzy logic is proposed, and the modularity of the architecture from the viewpoint of product remanufacturing is assessed. The transfer network of failure mode‐recycling decision using BP neural network optimized by adaptive genetic algorithm is built. Design structure matrix is employed to represent the relationships between components, and the hierarchical structure of product modularity with functionality, physical connection as well as geometric position is constructed. The failure modes of used components are analyzed, and four modular drivers with remanufacturing strategies consideration, namely, recycling mode, component lifetime, material compatibility, and remanufacturing processability, are introduced to reconstruct the modular product architecture for remanufacturing. Finally, an example on the grab is provided to illustrate the proposed method for product modularity taking into account function, structure as well as remanufacturing characteristics.

Study on Recycling Decisions of Recycling Dismantlers of Used Power Batteries Under the Influence of Recycling Efforts

“…In the current research on recycling decision-making Parsaeifar [1] et al study and discuss how it makes ordering and pricing decisions on the basis of profit optimization by constructing a closed-loop supply chain involving a manufacturer and multiple suppliers and retailers.Cheng [2] et al establish a recycling decision-making for improving the recycling rate of end-of-life products by using BP neural network optimized by adaptive genetic algorithm. Zhao [3] and others constructed a closed-loop supply chain model consisting of different remanufacturing entities and thirdparty recyclers, and studied the recycling decision-making of their different remanufacturing modes.Yi et al [4] similarly added a third-party recycler to the supply chain members, and constructed a closed-loop supply chain model with a dual recycling channel in which the third-party recycler recycles with the retailer to discuss the optimal recycling decisionmaking based on profit maximization.…”