The impact of Mean Time Between Disasters on inventory pre-positioning strategy

Purpose - This paper addresses the impact of Mean Time Between Disasters (MTBD) to inventory pre-positioning strategy of medical supplies prior to a sudden-onset disaster

Strategic maintenance technique selection using combined quality function deployment, the analytic hierarchy process and the benefit of doubt approach

The business performance of manufacturing organizations depends on the reliability and productivity of equipment, machineries and entire manufacturing system. Therefore, the main role of maintenance and production managers is to keep manufacturing system always up by adopting most appropriate maintenance methods. There are alternative maintenance techniques for each machine, the selection of which depend on multiple factors. The contemporary approaches to maintenance technique selection emphasize on operational needs and economic factors only. As the reliability of production systems is the strategic intent of manufacturing organizations, maintenance technique selection must consider strategic factors of the concerned organization along with operational and economic criteria. The main aim of this research is to develop a method for selecting the most appropriate maintenance technique for manufacturing industry with the consideration of strategic, planning and operational criteria through involvement of relevant stakeholders. The proposed method combines quality function deployment (QFD), the analytic hierarchy process (AHP) and the benefit of doubt (BoD) approach. QFD links strategic intents of the organizations with the planning and operational needs, the AHP helps in prioritizing the criteria for selection and ranking the alternative maintenance techniques, and the BoD approach facilitates analysing robustness of the method through sensitivity analysis through setting the realistic limits for decision making. The proposed method has been applied to maintenance technique selection problems of three productive systems of a gear manufacturing organization in India to demonstrate its effectiveness

An Efficient Heuristic for Pooled Repair Shop Designs

An effective spare part supply system planning is essential to achieve a high capital asset availability. We investigate the design problem of a repair shop in a single echelon repairable multi-item spare parts supply system. The repair shop usually consists of several servers with different skill sets. Once a failure occurs in the system, the failed part is queued to be served by a suitable server that has the required skill. We model the repair shop as a collection of independent sub-systems, where each sub-system is responsible for repairing certain types of failed parts. The procedure of partitioning a repair shop into sub-systems is known as pooling, and the repair shop formed by the union of independent sub-systems is called a pooled repair shop. Identifying the best partition is a challenging combinatorial optimization problem. In this direction, we formulate the problem as a stochastic nonlinear integer programming model and propose a sequential solution heuristic to find the best-pooled design by considering inventory allocation and capacity level designation of the repair shop. We conduct numerical experiments to quantify the value of the pooled repair shop designs. Our analysis shows that pooled designs can yield cost reductions by 25% to 45% compared to full flexible and dedicated designs. The proposed heuristic also achieves a lower average total system cost than that generated by a Genetic Algorithm (GA)-based solution algorithm. - 2019, Springer Nature Switzerland AG.Acknowledgement. This research was made possible by the NPRP award [NPRP 7-308-2-128] from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the author[s].Scopu