Reliability Evaluation of Numerical Control Machine Tools Based on Game Theory Combination Weighting and Improved TOPSIS

ABSTRACT The evaluation of reliability, crucial for identifying pivotal subsystems in machine tools, primarily hinges on the allocation of weights and the choice of appropriate evaluation methodologies. This research initially contemplates both subjective and objective elements inherent in the process of appraising machine tools. Subsequently, it employs the best worst method (BWM) in conjunction with the entropy weight method (EWM) to ascertain the subjective and objective weights attributed to each decision‐making criterion. Moreover, the combination weight is obtained using the game theory combination weighting method. Additionally, a game theory combination weighting‐Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) analysis model is constructed based on the combination weight and TOPSIS, addressing and rectifying the shortcomings of conventional TOPSIS in the evaluation process through pertinent enhancements, with numerical examples employed for validation. Finally, based on the fault repair data of a CNC boring and milling machine, such decision criteria as fault severity ratio, hazard rate, and downtime are selected for experimental analyses. The critical subsystems of the machine tool are identified, providing support for maintenance decision‐making.