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Reliability Analysis of Heavy-Duty Truck Diesel Engine Based on After-Sales Maintenance Data

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Abstract

Understanding the weak points and reliability influencing factors of products is the great significance for manufacturers to improve their design and make reasonable after-sales plans. Failure data are the basis for reliability analysis. Due to the long service life and high cost of engines, it is expensive and time-consuming to obtain failure data through reliability tests. After-sales maintenance data are an important reliability data, which intuitively reflects the field reliability performance of the product. In this paper, based on the after-sales maintenance data of heavy-duty truck diesel engines, the main failure points of diesel engines are identified, and the difference in service life of diesel engines under different service backgrounds is analyzed. In addition, gray relational analysis (GRA) is used to determine the main factors affecting the field reliability of diesel engines. The influence trend of usage rate on engine field reliability is analyzed. The results show that the fuel supply system has the highest proportion of failures in all subsystems. The failures of diesel engines mainly come from electronic devices and parts working in high-pressure environments. The service background has a significant impact on the life of the engine.

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Authors and Affiliations

  1. School of Mechanical Engineering, Shandong University, Jinan, 250061, China

    Chenhao Wang & Qiang Zhang

  2. National Demonstration Center for Experimental Mechanical Engineering Education, Shandong University, Jinan, 250061, China

    Chenhao Wang & Qiang Zhang

  3. Key Laboratory of High-Efficiency and Clean Mechanical Manufacture of Ministry of Education, Shandong University, Jinan, 250061, China

    Chenhao Wang & Qiang Zhang

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  1. Chenhao Wang
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Correspondence to Qiang Zhang.

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Wang, C., Zhang, Q. Reliability Analysis of Heavy-Duty Truck Diesel Engine Based on After-Sales Maintenance Data. J Fail. Anal. and Preven. 21, 993–1001 (2021). https://doi.org/10.1007/s11668-021-01145-3

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  • DOI: https://doi.org/10.1007/s11668-021-01145-3

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