Money-back guarantee warranty policy with preventive maintenance strategy for sensor-embedded remanufactured products


1 Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, 22254, Saudi Arabia

2 Department of Mechanical and Industrial Engineering, Northeastern University, 334 Snell Engineering Center, 360 Huntington Avenue, Boston, MA, 02115, USA


In today’s global environment, technology is constantly evolving. Being able to stay up-to-date with the very latest technological advances can be extremely hard to accomplish. As a result of these changes and developments in technology, which often come unexpectedly, consumers are frequently tempted to update their devices to the very latest model. The result is that the life cycle of a product is becoming shorter and shorter than before. Manufacturers attempt to respond to consumers’ concerns involving environmental issues as well as the more governmentally stringent environmental legislations by establishing facilities which include the minimization of the totality of waste relocated to landfills by recovering materials and components from returned, or End-Of-Life products and reuse them to build a remanufactured product, and/or novel components. With the rapid growth of interest in remanufactured products’ market, offering warranty for remanufactured products and components is becoming a necessity for remanufacturer in order to meet customers’ requirement and as a marketing mechanism. During that process, maintenance policies are of great importance in order to reduce the warranty cost on the remanufacturer. In this paper, an optimization simulation model for remanufactured items sold with one-dimensional non-renewing money-back guarantee (MBG) warranty policy is proposed from the view of remanufacturer, in which, an End-Of-Life product is subjected to upgrade action at the end of its past life and during the warranty period, preventive maintenance actions are carried out when the remaining life of the product reaches a pre-specified value so that the remanufacturer’s expected profit can be maximized. Finally, a numerical example and design of experiment analysis are provided to demonstrate the proposed approach.