Optimization of reconditioning scheme for remanufacturing of used parts based on failure characteristics

•A new framework for optimization of reconditioning scheme for used parts, based on failure features, is established, and Fault Tree Analysis (FTA) is applied to extract failure features of used parts.•An optimization model of reconditioning scheme is then established, which considers the remanufacturing cost and time as the optimization objectives, and a Genetic Algorithms (GA) is applied to solve the optimization problem.•The approach is demonstrated through the remanufacturing of used worm gear and its effectiveness is compared against two cases. The multiple failure characteristics of used parts make the remanufacturing process very complex. This leads to undecisive reconditioning schemes. In order to determine the optimal reconditioning scheme for used parts, a failure characteristic modelling-based method for remanufacturing of used parts is presented. In this method, Fault Tree Analysis (FTA) is adopted to extract and analyze the failure characteristics of used parts and its causes; and then the generic failure characteristics of used parts are summarised and characterized through the mathematic modelling. The matter-element analysis is utilized to characterize the failure characteristics information. In accordance with the characteristics information, rule-based reasoning and an improved AND/OR as well as network diagram are used to generate reconditioning scheme alternatives. A multi-objective optimization model considering reconditioning cost and time is established, whilst the Generic Algorithm (GA) is applied for the model solution comparing with a non-algorithm method. Finally, a worm gear is taken as an example to verify the effectiveness of the proposed method and the results indicate that the proposed method is valid and practical.