Abstract
Design for remanufacturing process (DFRP) plays a key role in implementing remanufacturing because it directly affects the performance recovery of the End-of-Life (EoL) product. Since the used parts have various failure forms and defects, these make it hard to rapidly generate the remanufacturing process scheme for satisfying the performance demand of the used product. Moreover, remanufacturing process parameters are prone to conflicts during the process of implementing remanufacturing, this leads to the failure of the remanufacturing process. For accurately generating remanufacturing scheme and solving the conflicts, an integrated design method for remanufacturing process based on performance demand is proposed, which can reuse the historical remanufacturing process data for generating the remanufacturing process scheme. Firstly, for accurately describing the performance demand, the Kansei Engineering (KE) and Quality Functional Development (QFD) are applied to analyze the performance demand data and map the demand to the engineering features. Then, Back Propagation Neural Network (BPNN) is applied to inversely generate the remanufacturing process scheme rapidly for satisfying the performance demand by reusing the historical remanufacturing process data. Meanwhile, Theory of Constraint (TOC) and TRIZ are used to identify the conflicts of the remanufacturing process and resolve the conflicts for optimizing the remanufacturing process scheme. Finally, DFRP of the saddle guideway is taken as an example to demonstrate the effectiveness of the proposed method, the result shows the design method can quickly and efficiently generate the remanufacturing process for the EoL guide rail.
An integrated design method for remanufacturing process based on performance demand