A scheduling optimization method for maintenance, repair and operations service resources of complex products
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A scheduling optimization method for maintenance, repair and operations service resources of complex products Hao Li1 · Shanghua Mi1 · Qifeng Li1 · Xiaoyu Wen1 · Dongping Qiao1 · Guofu Luo1 Received: 9 May 2017 / Accepted: 12 February 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract Scheduling optimization of maintenance, repair and operations (MRO) service resources of complex product can help an enterprise improve customer service satisfaction, build value-added products, and enhance the enterprise’s market competitiveness. This paper studies a scheduling optimization method for the MRO service resources of complex product. First, the scheduling problem in service resources is analyzed, a mathematical model for the service scheduling problem is given, and three objective functions to be optimized are proposed, which are to reduce customer waiting time, reduce excessive human resources, and maximize the cost performance index of the resources. Then, three separate objectives for optimizing service resource scheduling are analyzed based on three proposed methods which are improved genetic algorithm method, combined weight coefficient optimization method, and multi-objective optimization method based on the nondominated sorting genetic algorithm II (NSGA-II). Finally, we use the three methods to carry out scheduling optimization of MRO service resources in the case of a large vertical mill. According to the analysis and comparison of results, the multi-objective optimization method based on the NSGA-II algorithm has an advantage in the scheduling optimization of complex product MRO service resources. In the engineering application, the service scheduling of complex products for managers provides theoretical basis, and can reduce the loss caused by subjective judgment. Keywords Maintenance, repair and operations · Scheduling optimization · Improved genetic algorithm · NSGA-II algorithm
Introduction In recent years, the drawbacks of traditional business models encompassing only the manufacturing and sale of physical products have become clear: their profit margins have continued to decrease (Li et al. 2016a, 2017). As a trend and feasible value-added solution, manufacturing servitization has been proposed and studied a lot (Vandermerwe and Rada 1988; White et al. 1999; Fishbein et al. 2000). The implementation of modern manufacturing services helps to improve an enterprise’s profits, enhance its competitiveness, and has become one of the best ways to transform and upgrade enterprises (Li et al. 2014; Oliva and Kallenberg 2003). When manufacturing enterprises plan to increase the added value via manufacturing services, they must also improve customer
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Guofu Luo [email protected] Henan Provincial Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, China
service satisfaction, which is mainly driven by service reliability and responsiveness (Mascio 2002). Nowadays, Complex products have certain characte
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