Research On Maintenance Strategy Of CNC Machine Tools Based On Reliability-Centered Maintenance

As the mainstream products and underpinning products of the machinery and equipment manufacturing industry, CNC machine tools become the key equipment to modernize the equipment manufacturing industry, and a significant symbol to measure comprehensive national power. At present, the domestic demand for high-end CNC machine tools is bigger and bigger, but, unfortunately, most of them are made abroad. The main cause of low competitiveness of CNC machine tools made in China is the low reliability and poor precision maintenance. Thus, due to the difficulty in reliability maintenance, intensive study should be taken to perfect the maintenance strategy of CNC machine tools made in China.The thesis aimed at CNC machine tools, based on Reliability-Centered Maintenance, the key maintenance technique and problems in using are investigated, and the methods of establishing and quantifying models in Maintenance Strategy are argued. The results of this paper are critical to improve the reliability of CNC machine tools made in China.Several research results are showed as follows:1. To find the weakness parts in CNC machine tools, an importance analysis method based on Triangular Fuzzy Number and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS) is proposed to improve the shortcomings in classical method such as subjective factors affecting the results, without consideration of the fuzziness in the engineering practice, and lacking an overall consideration of influencing factors. By using Triangular Fuzzy Number to quantify the fuzzy information, and considering 7 influencing factors such as detection difficulty, maintenance time, maintenance difficulty and so on, TOPSIS is used to give an importance sort of subsystems in CNC machine tools. Then the weakness parts in CNC machine tools can be confirmed.2. To solve the contradiction of different repair degrees against reliability and maintenance cost, based on hypothesis on “as bad as old”, “better than old but worse than new”, and “as good as new” in repair degrees, a repair degree strategy model is established, and Multi Objective Particle Swarm Optimization(MOPSO) is used to solve the proposed model. Then a tradeoff repair degree strategy can be got which can maintain a high reliability but doesn’t cost too much.3. To determine the best preventive maintenance period during early failure period, an integrated method is proposed. 3 methods are introduced in this paper: the model based on the maximum reliability, the model based on the minimum cost, and Fault Tree Analysis(FTA) maintenance period prediction which is used to reflect the uncertainty and randomness of failures. By introducing the absolute contrasting method in fuzzy decision making to band these methods together, the best preventive maintenance period during early failure period can be got.