IEEE Access (Jan 2019)

Modeling and Analysis of the Reliability of Machining Process of Diesel Engine Blocks Based on PFMECA

  • Guizhong Tian,
  • Wei Zhang,
  • Zhengyu Ma,
  • Honggen Zhou,
  • Xuwen Jing,
  • Guochao Li

DOI
https://doi.org/10.1109/ACCESS.2019.2938625
Journal volume & issue
Vol. 7
pp. 124759 – 124773

Abstract

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Due to its difficulty in maintenance, the diesel engine have special requirements on process reliability of the engine block, which is one of the most important and hard-to-machining components of the engine, and will directly affects the performance and service life of the engine. With continuous improvements to the engine quality, the process reliability of the engine block have become more and more important. However, the previous researches mainly focus on the reliability of products, machine tools, or cutting tools, while the researches on the reliability of machining process, which lead to unstable quality of the machined engine block, have been little discussed. Therefore, this paper proposes an integrated method to analyze the process reliability of DEB (Diesel Engine Blocks). First, the reliability model of the DEB machining process is established by using reliability block diagram method. The model is mainly concerned with the process reliability and error-free judgment probability of the key features of DEB, which is deduced by using the PFMECA (Process Failure Mode, Effects and Criticality Analysis) method. Then, the response surface and FEM method is used to establish a mathematical model for the key features and its key influencing factors, and the process reliability of the key features is evaluated by Monte Carlo simulation. The reliability of the machining process is evaluated by substituting the process reliability of the key features into the reliability model of the DEB machining process. The method is applied to evaluate the reliability of the machining process of a certain type of DEB and solves the problem that the actual machining data are insufficient for reliability evaluation.

Keywords