The experience of disruptive events causing supply chain vulnerability and business downturns has motivated manufacturing purchasers to consider resilience capability when selecting suppliers. However, this problem is complex, mainly due to difficulties in obtaining precise data on supplier performance. Disruptions are viewed as low-possibility events, leading to incomplete or insufficient evidence to support assessment. A literature review presented in this paper identifies a list of prospective criteria for resilient supplier selection, within the electronics market, considering both quantitative and qualitative aspects in a symmetrical way. A new hybrid methodology, able to handle various forms of uncertain and incomplete data, is proposed to facilitate the supplier selection process. Evidence theory, which suggests the assignment of degrees of belief, instead of traditional probabilities, to expected results, is adopted to construct a decision matrix. The rule-based transformation technique is then employed to transform various forms of the assessment results into a unified format before further aggregation by the modified Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The proposed methodology is tested with a case of resilient supplier selection in a company producing computer hardware components. The proposed decision-making methodology can be applied not only by electronics purchasers but also by practitioners in other industries to logically and straightforwardly model the uncertainty and incompleteness of the available information.

Purpose: The purpose of this work is to develop a mathematical model for simultaneously determining the optimal period of preventive maintenance actions and the optimal size of buffer stock for a production unit that is owned by a lessor and leased to a lessee under a lease contract.Design/methodology/approach: A mathematical model is formulated and a numerical procedure is developed for finding the optimal period of preventive maintenance actions and the optimal size of buffer stock to minimize the total expected costs considering both a lessor and a lessee over a lease period.Findings: The proposed model gives better solutions than those where the maintenance cost to the lessor and the production inventory cost to the lessee are minimized separately.Originality/value: The joint determination of preventive maintenance and safety stock is a topic that has been extensively studied for decades. The majority of the models reported in the literature implicitly assume that the firm owns the production unit and maintenance actions are done in-house. However, equipment acquisition through leasing is a common practice nowadays. Normally, under a lease contract, the lessor who owns the equipment is responsible for maintenance services. This may lead to a conflict between the lessor and the lessee concerning the optimal choice of maintenance actions. To solve this conflict, we propose a joint determination of preventive maintenance and safety stock model for a production unit under a lease. The objective of our model is to simultaneously determine the optimal period of preventive maintenance actions that the lessor needs to perform and the optimal size of buffer stock the lessee needs to produce so that the total combined expected costs to both parties over the lease period are minimized.