Aftermarket survey on end-of-life vehicle recovery in Malaysia: Key findings. (20th February 2019) - Mohamad-Ali, Nurhasyimah; Raja Ghazilla, Raja Ariffin; Abdul-Rashid, Salwa Hanim; Ahmad-Yazid, Aznijar
Abstract: The National Automotive Policy was introduced in Malaysia in 2006, which includes end-of-life vehicle (ELV) recovery policies. However, there is limited information on the current state of ELV recovery in Malaysia, which hinders the fulfillment of these new requirements. For manufacturers, the lack of information will lead to difficulties in making strategic decisions in order to fulfill the ELV policies. In order to support design strategies for ELV recovery, it is crucial to identify the issues and factors of ELV recovery, which forms the objective of this study. A survey was carried out among the key stakeholders in the aftermarket chain and the results revealed that special tooling is needed to handle ELV components as well as design that will facilitate the separation of parts according to materials. These are among the main factors that contribute toward the effectiveness of ELV recovery. The following 5 factors (pre-production, health and environment, policy and worker, manufacturing process, and end-of-life value) are the factors that will enhance ELV recovery in Malaysia and it is believed that these factors are subject to dynamic changes in the aftermarket chain. It is believed that the results presented in this paper will be useful to academics and researchers in order to establish design strategies for ELV recovery in Malaysia. Moreover, stochastic techniques are required to cater the dynamic and complex behavior of the actual ELV recovery system in Malaysia. Highlights: ELV recovery issues and factors in the automotive industry are investigated. Special tooling is a critical issues faced by aftermarket stakeholders. Pre-production, manufacturing process, and EOL value are among the important factors. Fragility of components is the most important sub-factor. The proposed factors serve as a guideline to create a dynamic ELV recovery model.