Abstract
The quality of CNC (computer numerical control) machine tool is the key to the survival of manufacturing enterprises. How to comprehensively and accurately evaluate its quality is very important for the timely discovery and improvement of machine tool defects. The current research either only evaluates a certain quality characteristic of CNC machine tool, or ignores the dynamic characteristics of CNC machine tool quality, which reduces the accuracy of quality analysis results. To address these problems, firstly, RMS (reliability, maintainability, supportability) was taken as the comprehensive evaluation indexes of CNC machine tool quality characteristics to improve the comprehensiveness of the analysis. Secondly, considering the dynamic characteristics of machine tool reliability, the ADC (availability, dependability, capability) model was improved to obtain a comprehensive quality evaluation index function ERMS with time-varying characteristics. Finally, the characteristics of ERMS were analyzed, and its evaluation criteria were also given. Several CNC machine tools made in China were tracked, and the collected fault data were analyzed by the proposed method. The ERMS of the machine tools was obtained, and its characteristics were analyzed. The results verify the correctness of the proposed method, which provides theoretical basis and technical support for the improvement of the quality of CNC machine tool and the market competitiveness of enterprises.
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Funding
This work was supported by the National Natural Science Foundation of China (no. 51835001) and the National Major Scientific and Technological Special Project for “High-grade CNC and Basic Manufacturing Equipment” of China (no. 2018ZX04032-001).
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Yulong Li analyzed the data and wrote the manuscript. Donglong Li and Junfa Li were the major contributors in collecting the data. Shengquan Liu simulated the data. Genbao Zhang polished the manuscript. All authors read and approved the final manuscript.
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Li, Y., Liu, S., Li, J. et al. Time-varying comprehensive evaluation technology of CNC machine tool RMS based on improved ADC model. Int J Adv Manuf Technol 124, 4175–4182 (2023). https://doi.org/10.1007/s00170-022-09520-6
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DOI: https://doi.org/10.1007/s00170-022-09520-6