Multi Objective Optimization of Servers Number in Auto After-Sale Service

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After-sales activities are nowadays attributed as a relevant source of competitive advantage, revenue and profit in the automotive industries. Intangibility of the service function makes it hard to quantify. However, there is an obligation to find out an efficient way to enhance service performance by quantitative methods so as to provide customers with a satisfactory level of service based on the current sources and costs. This research utilized design of experiments to analyze and evaluate the impact of relevant controllable variables on the performance of an automotive after-sale service workshop. This paper described a novel approach which aimed at simultaneous achievement of two distinctive goals, which play important roles in the service sector, improving efficiency and responsiveness by optimizing the number of servers in the whole system. Average time spent in the system by customers and average of idle time were two key performance indicators determined using WITNESS software as a simulator that represented responsiveness and efficiency criteria, respectively. Based on the 2-level full factorial design the maximum responses’ values were achieved by assigning 4, 1 or 2, 1 and 1 servers to the Defect Detection, Periodic Inspection, Road Test and Inspection Report Recording stations, respectively.
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Classical Design of Experiments (DOE); Customer Satisfaction; Service Rate; Simulation; Average Idle Time; Service Average Time; Performance

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