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A novel FMECA method for CNC machine tools based on D-GRA and data envelopment analysis.

Hailong Tian1, Yuzhi Sun2, Chuanhai Chen1

  • 1School of Mechanical and Aerospace Engineering, Jilin University, Key Laboratory of CNC Equipment Reliability, Ministry of Education, Changchun, 130022, Jilin Province, People's Republic of China.

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Summary
This summary is machine-generated.

This study enhances Failure Modes, Effects, and Criticality Analysis (FMECA) for CNC machine tools by refining risk factors and integrating new methods. The improved approach provides clearer directions for enhancing system reliability and reducing failures.

Keywords:
BCC modelCNC machine toolsDistance-grey relational analysisFMECAImprovement directions

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Area of Science:

  • Mechanical Engineering
  • Reliability Engineering
  • Manufacturing Systems

Background:

  • Traditional Failure Modes, Effects, and Criticality Analysis (FMECA) faces limitations in analyzing CNC machine tool reliability, including vague risk factors and unclear improvement strategies.
  • Existing methods struggle with equal treatment of risk factors and lack specific guidance for enhancing weak points.

Purpose of the Study:

  • To propose an enhanced FMECA methodology for CNC machine tools that addresses the limitations of traditional approaches.
  • To refine risk factor assessment and introduce a novel method for prioritizing failure modes.
  • To provide clear, actionable directions for improving the reliability of CNC machine tools.

Main Methods:

  • Expanded severity (S) into machine hazard (M) and personal hazard (P); subdivided detectability (D) into functional structural complexity (D1) and detection cost (D2).
  • Integrated Distance Analysis Method (DAM) and Grey Relational Analysis (GRA) to propose Distance-Grey Relational Analysis (D-GRA) for determining risk factor weights.
  • Introduced the BCC model to evaluate failure modes as decision-making units and determine efficiency values for targeted improvements.

Main Results:

  • A modified Risk Priority Number (RPN) calculation method was developed, integrating risk factor weights and failure mode efficiency values.
  • The proposed method was applied to an electric spindle system, demonstrating its effectiveness in ranking failure modes and comparing favorably with traditional RPN methods.
  • Specific improvement directions for enhancing the reliability of CNC machine tools were identified.

Conclusions:

  • The enhanced FMECA methodology offers a more precise and actionable approach to reliability analysis for CNC machine tools.
  • The integration of D-GRA and the BCC model provides a robust framework for identifying and addressing critical failure modes.
  • The study validates the proposed method's superiority over traditional approaches in guiding reliability enhancement efforts for complex machinery.