The management of end-of-life vehicles (ELVs) conserves natural resources, provides economic benefits, and reduces water, air, and soil pollution. In an effort to adequately manage flow of ELVs, modern infrastructure is considered a prerequisite. Thus, development of an effective performance evaluation tool for monitoring and continuous improvement of ELV management systems is strongly desired. In this paper, a performance evaluation tool is proposed for ELV management system implementation, based on the analytic hierarchy process. A real-life case study in Malaysia was conducted in order to demonstrate the potential and applicability of the presented methodology. The scores of eight key success factors in establishing an ELV management system (i.e., management responsibility, performance management, capacity management, resource management, stakeholders' responsibility, education and awareness, improvement and enforcement, and cost management) are presented. The overall score of the ELV management system implementation in Malaysia is equal to 2.13. Therefore, its performance level is average. The presented multi-criteria decision analysis tool can be of assistance not only to stakeholders in the Malaysian ELV management system, but also to vehicle recycling managers from other countries in order to monitor and continuously improve their ELV management systems.
The conventional component repair in remanufacturing involves human decision making that is influenced by several factors such as conditions of incoming cores, modes of failure, severity of damage, features and geometric complexities of cores and types of reparation required. Repair can be enhanced through automation using additive manufacturing (AM) technology. Advancements in AM have led to the development of directed energy deposition and laser cladding technology for repair of damaged parts and components. The objective of this systematic literature review is to ascertain how intelligent systems can be integrated into AM-based repair, through artificial intelligence (AI) approaches capable of supporting the nature and process of decision making during repair. The integration of intelligent systems in AM repair is expected to enhance resource utilization and repair efficiency during remanufacturing. Based on a systematic literature review of articles published during 2005-2021, the study analyses the activities of conventional repair in remanufacturing, trends in the applications of AM for repair using the current state-of-the-art technology and how AI has been deployed to facilitate repair. The study concludes with suggestions on research areas and opportunities that will further enhance the automation of component repair during remanufacturing using intelligent AM systems.