Username   Password       Forgot your password?  Forgot your username? 


Spare Parts Forecast Analysis based on Important Calculation of Element Fault Tree

Volume 15, Number 7, July 2019, pp. 1878-1885
DOI: 10.23940/ijpe.19.07.p14.18781885

Xiaoyan Wang, Hongkai Wang, Jinghui Zhang, and Chun Zhang

Shenyang Aerospace University, Shenyang, 100136, China


(Submitted on April 13, 2019; Revised on May 25, 2019; Accepted on June 25, 2019)


Spare parts are an important material basis for the use and maintenance of machine tools, and they are an important factor affecting equipment life cycle costs. In this paper, the element movements and the element action failure modes of equipment operation are found for the machine function unit. The reason of the failure of the unit base element is identified by using the element action fault tree to determine the reason of the fault of the unit base element. The calculation of the importance degree of the machine unit is carried out, and the importance degree is analyzed for rational distribution, thus ensuring the reduction of maintenance costs and the normal operation of the system. It is proven that the method based on the importance of the fault tree of the element action plays a guiding role in the analysis of spare parts.


References: 11

  1. Q. Hu, X. Jia, and J. Zhao, “A Model of Calculating Spare Parts Demand Volume by Considering Preventive Maintenance,” Acta Armamentarii, Vol. 37, No. 5, pp. 916-922, 2016
  2. X. Wang, “Research on Predictive Model of the Key Spare Parts of the Spindle System based on Dependent Failure,” Jilin University, Jilin, 2015
  3. A. Bacchetti and N. Saccani, “Spare Parts Classification and Demand Forecasting for Stock Control: Investigating the Gap Between Research and Practice,” Omega: The International Journal of Managements Science, Vol. 40, pp. 722-737, 2012
  4. A. Beaumont, “Data Transforms with Exponential Smoothing Methods of Forecasting,” International Journal of Forecasting, Vol. 30, No. 4, pp. 918-927, October-December 2014
  5. A. Ghobbar and C. Friend, “Evaluation of Forecasting Methods for Intermittent Parts Demand in the Field of Aviation: A Predictive Model,” Computers & Operations Research, Vol. 30, No. 14, pp. 2097-2114, 2003
  6. Y. Feng, D. Yi, and B. Luo, “Forecasting Model for Spare Parts with Intermittent Demand based on SES,” Ordnance Industry Automation, Vol. 30, No. 2, pp. 18-21, 2011
  7. J. D. Croston, “Forecasting and Stock Control for Intermittent Demands,” Operational Research Quarterly, Vol. 23, No. 2, pp. 289-303, 1972
  8. M. Villoria and R. Ignaccolo, “Bootstrap based Uncertainty Bands for Prediction in Functional Kriging,” Spatial Statistics, Vol. 21, pp. 130-148, Part A, August 2017
  9. H. Zhang, “Research of Reliability Analysis and Control Technology of CN Machine based on Element Action,” Chongqing University, Chongqing, 2012
  10. J. Zhang, H. Zhang, C. Du, and W. Zhao, “Research on the Dynamics of Ball Screw Feed System with High Acceleration,” International Journal of Machine Tools and Manufacture, Vol. 111, pp. 9-16, December 2016
  11. G. Pritschow and N. Croon, “Ball Screw Drives with Enhanced Bandwidth by Modification of the Axial Bearing,” CIRP Annals - Manufacturing Technology, Vol. 62, No. 1, pp. 383-386, 2013


Please note : You will need Adobe Acrobat viewer to view the full articles.Get Free Adobe Reader

This site uses encryption for transmitting your passwords.