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The legislation for end-of-life vehicles (ELV) is anticipated to be fully enforced, and public awareness is likely to grow over the next few years, assuring the profitability of Malaysia’s ELV recycling enterprises in the future. However, the current state of ELV recycling operations is fraught with uncertainty, which has hampered this industry’s expansion. Thus, this study aims to identify critical uncertainties and provide suitable strategies to mitigate these uncertainties. A case study of multiple automotive treatment facilities (ATFs) in Malaysia was employed to conduct this study. A structured questionnaire comprising both closed-ended and open-ended questions was provided to Malaysian ATFs, and site observations were conducted to investigate the ATFs' production settings. Cross-case synthesis was utilised to compare the cases studied. Meanwhile, the closed-ended questions are assessed on a five-point Likert scale, and the responses were analysed with ATF to conduct the descriptive analysis. As a result, a cross-case synthesis between the ATFs was presented and the uncertainties in ELV recycling operation were identified, consisting of ELV supply (M = 4.250), ELV recycling costs (M = 4.188), ATF infrastructure (M = 4.125), production planning (M = 3.875), ELV characteristics (M = 3.550), and ELV distribution network (M = 2.833). In addition, a conceptual framework for improving the ELV dismantling system in Malaysia’s ATF was proposed. The novelty of this study is a detailed analysis of existing uncertainties in ELV recycling operation in the Malaysian context and an improved framework to enhance the ELV dismantling system for ATFs in Malaysia.

Food and vaccine supply chains are a top priority in the cold chain sector as consumers are particularly concerned for the quality, safety, and environmental effects of these temperature sensitive products. Moreover, any disruptions to these supply chains will have adverse effects on the overall supply chain system and significantly increase the cost of recovery. Therefore, this study aimed to determine the optimum recovery cost for transportation disruptions in a cold chain system. A mathematical model was developed to analyse transportation disruption’s effect, where the optimal recovery schedule consisting of production and shipment quantity decisions are determined by considering the economic and environmental impact. Particularly, the model quantifies the costs of carbon emissions from fuel consumption and the cooling system of the refrigerated truck. LINGO programming software was used to conduct a numerical analysis to determine the optimal recovery costs. Our findings indicate that truck load capacity was the main factor affecting total recovery costs as trucks carrying larger load capacities greatly reduced the frequency of shipment on a route thereby reducing the overall cost of carbon emissions.

This paper presents the passengers' perspective towards express bus safety issues based on the driver's behavioural characteristics, providing an important aspect in reducing the accidents in Malaysia. A pilot study with a respondent of 40 people, aged between 16 to 41 years old were conducted in Universiti Kebangsaan Malaysia. The developed questionnaires based on the five-point Likert Scale were implemented to assess the safety perception on express buses, and it has a higher reliability of Cronbach's Alpha score at 0.91. The findings show that more than 45 % of the respondents agreed that dangerous behaviour of express bus drivers were mainly due to the use of mobile during driving (63.33%), tailgating (57.58%) and driving above the given speed limit (48.59%). The reason of this behaviour is insufficient time to stick to running schedules and the shift pattern rotations. In terms of safety precautions, about 77% passengers preferred safety briefing using audio due to its ease in understanding the meaningful instruction. In addition, 97% passengers agreed on the needs of a second driver to ensure a safe journey to their destination. Hence, a proposed mitigated solution such as drivers monitoring is needed by the respective agencies to reduce this careless behaviour that may influence the dangerous driving behaviour.

Remanufacturing has now become one of the effective strategies for reducing the negative impact on the environment by prolonging the products’ life cycle in the automotive sector. Still considered as a relatively new industry in Malaysia, the low remanufacturing rate coupled with the lack of standardization are thus seen as causing a high inclination of disruption occurrences in the remanufacturing operations. As such, this paper had identified and investigated the existing disruptions in four problematic areas, namely the production planning, infrastructure facilities, distribution networking and inventory management of the automotive remanufacturing firms in Malaysia. From the SPSS analysis and calculation of the mean and standard deviation values on the semi-structured interviews that were conducted in three remanufacturing companies, the highest contributor to the disruption risks was found to have resulted from the difficulty in obtaining the spare parts components in the production planning process. By also exploring the awareness level on environmental sustainability and the significance of remanufacturing processes among the remanufacturer companies, this analysis is thus deemed useful for not only identifying suitable actions that can be taken for mitigating the various risks faced by the automotive remanufacturers in Malaysia, but also in solving the disruptions of the remanufacturing supply chain system.

This thesis presents a study of the effects of disruption on the production and inventory replenishment decisions of the overall supply chain system. The study focused on analyzing the optimal inventory and recovery policies for each node, so that the supply chain system is optimized as a whole. The problems considered are instances of the class of inventory management problems under disruptions with a finite horizon. A decision support system tool for managing supply chain disruptions was presented. Specifically, an efficient supply chain optimization framework was developed, in which the problems were formulated as mathematical models and heuristic algorithms were developed to solve these underlying optimization problems. The framework was applied to three different models: (1) a single stage production-inventory system following the Economic Production Quantity system (2) a two stage serial supply chain system and (3) a three stage supply chain system with multiple suppliers. Two different types of disruptions were explored, including (1) supply disruption and (2) transportation disruption. The results of the experimental analysis showed that the optimal recovery schedule is highly dependent on the relationship between the backorder cost and the lost sales cost parameters. When lost sales cost is low, it is found that the recovery duration is shorter. However, as the lost sales cost increases, it is more cost effective to have backorders, thus the recovery duration will become longer. In addition, the efficient heuristics developed in all three cases performed well and provided quality solutions in reasonable time. In the final work of this thesis, a simulation model was designed to investigate the effects of various pre-defined disruption scenarios over time. Results from the study showed that supply disruption at the supplier with higher inventory holding cost causes higher recovery costs. As for transportation disruption, the solution is more sensitive to the