Open Physics (May 2020)

Heuristic decision of planned shop visit products based on similar reasoning method: From the perspective of organizational quality-specific immune

  • Liu Qiang,
  • Lian Zhifeng,
  • Guo Yu,
  • Tang Shulin,
  • Yang Feixue

DOI
https://doi.org/10.1515/phys-2020-0012
Journal volume & issue
Vol. 18, no. 1
pp. 126 – 138

Abstract

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The purpose of this study is to reduce the maintenance time, cost, and scheduling distance and to determine the maintenance priority of planned shop visit products. This study introduces the concept of maintenance map, establishes the evaluation indicators system of maintenance map from the perspective of organizational quality-specific immune, and puts forward two key dimensions named maintenance plan and technical support of maintenance map. Based on the theoretical framework, construct a heuristic decision model of planned shop visit products based on similar reasoning, set the maintenance services data of Harbin Dongan Engine Co., Ltd., as research objects, and use the concrete schemes and cases to solve and carry out an empirical analysis of the heuristic decision of planned shop visit products based on similar reasoning with the help of the ant colony algorithm; the empirical analysis results indicate that maintenance map and evaluation indicators system are the fundamental basis of the heuristic decision based on similar reasoning, the combinations of similar reasoning and ant colony algorithm can achieve the optimal heuristic decision of planned shop visit products, which have effectiveness, feasibility, and operability. This research will be conductive to give out the heuristic decision of scheduling schemes of planned shop visit products, which will be beneficial to enhance maintenance efficiency and quality, promote learning effects and learning pattern paths, and reduce maintenance scheduling distances of planned shop visit products from the aspects of theoretical framework guidance, empirical system enlightenment, and conceptual paradigm reference.

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