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Reliability Assessment of CNC Machining Center Based on Weibull Neural Network

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  • Zhaojun Yang
  • Chao Chen
  • Jili Wang
  • Guofa Li

Abstract

CNC machining centers, as the key device in modern manufacturing industry, are complicated electrohydraulic products. The reliability is the most important index of CNC machining centers. However, simple life distributions hardly reflect the true law of complex system reliability with many kinds of failure mechanisms. Due to Weibull model’s versatility and relative simplicity and artificial neural networks’ (ANNs) high capability of approximating, they are widely used in reliability engineering and elsewhere. Considering the advantages of these two models, this paper defined a novel model: Weibull neural network (WNN). WNN inherits the hierarchical structure from ANNs which include three layers, namely, input layer, hidden layer, and output layer. Based on more than 3000 h field test data of CNC machining centers, WNN has been successfully applied in comprehensive operation data analysis. The results show that WNN has good approximation ability and generalization performance in reliability assessment of CNC machining centers.

Suggested Citation

  • Zhaojun Yang & Chao Chen & Jili Wang & Guofa Li, 2015. "Reliability Assessment of CNC Machining Center Based on Weibull Neural Network," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-8, November.
    • Handle: RePEc:hin:jnlmpe:292197
    DOI: 10.1155/2015/292197
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