Today, improving machine availability is vital for industries to compete in the global market. Spare parts play an essential role in the maintenance and repair of equipment, but planning an extensive network in strategic industries with various spare parts can be very challenging due to the existence of different decision factors. The spare parts supply chain deals with inventory management issues, which necessitates considering the related decisions such as determining the stock level and order quantity. Moreover, demand uncertainty and long supply time make decision-making more complex. This paper presents a repair and supply planning model for repairable spare parts while considering a modified formulation of demand uncertainty to minimize costs. The model determines the optimal stock level, lateral transshipment, assignment of spare part orders to suppliers, equipment to repair centers, and the number of intervals over the planning horizon used in demand estimation. This research contributes to the literature by integrating recent decisions, using demand approximation by piecewise linearization, and considering backorder in warehouses evaluated by queuing models. A hybrid approach, including heuristic and genetic algorithms, is used to optimize the model using data from an oil company. The results show that using piecewise linearization and integrated repair and supply planning decisions optimizes costs and improves performance. Also, the availability is affected by the demand estimation, which necessitates precision prediction.

This study tends to investigate and assess the average waiting time (WT) in Dubai primary healthcare services centers. Healthcare centers will face critical problems if WT is not solved properly. Accordingly, this study tries to dig a deep insight on such problem and provides proper suggestions to reduce WT. An Electronic Medical Record audit is used to count the patients’ WT during a four-week period in health care service centers employing a universal sampling approach. All patients who visit the health medical centers during such period are considered for the study purpose except those need emergency services. A self-administered questionnaire is used to collect the needed records about WT longevity causes from direct em-ployees who use to interact patients in a continuous basis. The questionnaires are distributed in 12 healthcare centers throughout Emirate of Dubai in UAE. A total of 76,780 electronic medical records are audited for patients and 938 responses are analyzed for the employee survey. The study finds that about 45.2% of the patients were registered within less than 7 minutes of their visit and the mean WT was 11.7 minutes of entrance. While more than two third of them (75.3%) waited less than 30 minutes and the average consultation WT was 34.2 minutes. 65.9% of patients waited less than 28 days to get their appointment and the average appointment WT was 35 days. The data collected from employees denoted that the main causes of patients’ WT were high workload level, insufficient work procedure, employees-supervisor interaction problems and adequate facilities availability. There is a need for healthcare leaders and managers in charges in this sector to reduce patients’ complaints while waiting and to solve the WT problem in a planned manner.