• DocumentCode
    229784
  • Title

    Preventive Maintenance Schedule of CNC Machine Tool Based on Monte Carlo Simulation

  • Author

    Liqing Qiu

  • Author_Institution
    Coll. of Mech. & Electr. Eng., Nanning Coll. for Vocational Technol., Nanning, China
  • fYear
    2014
  • fDate
    22-25 Oct. 2014
  • Firstpage
    993
  • Lastpage
    996
  • Abstract
    This paper studies the preventive maintenance schedule of CNC machine tool, which is of failure rate of Weilbull distribution. The machine failure cause by tool wear is modeled by Poisson process of Weilbull distribution, and the optimal period preventive maintenance schedule on the principle of maximum average service rate is represented by mathematical model. The existence of optimal preventive maintenance schedule is analyzed. By the means of Monte Carlo stochastic numerical simulation, a sample of optimal preventive maintenance strategy of CNC machine tool is obtained based on the real data of machine failure. The result of the paper shows that the machine preventive maintenance could improve the average service rate, which is valuable to the industry practice.
  • Keywords
    Monte Carlo methods; Weibull distribution; computerised numerical control; failure analysis; machine tools; preventive maintenance; stochastic processes; CNC machine tool; Monte Carlo stochastic numerical simulation; Poisson process; Weilbull distribution; failure rate; industry practice; machine failure; mathematical model; maximum average service rate principle; optimal period preventive maintenance schedule; tool wear; Computer numerical control; Electric breakdown; Machine tools; Monte Carlo methods; Preventive maintenance; Schedules; Maximum Average Service Rate; Monte Carlo Simulation; Period Preventive Maintenance Schedule; Tool Wear; Weilbull Distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Machines and Systems (ICEMS), 2014 17th International Conference on
  • Conference_Location
    Hangzhou
  • Type

    conf

  • DOI
    10.1109/ICEMS.2014.7013630
  • Filename
    7013630