This investigation is designed to contrast two methodologies, RAWEC (Ranking of Alternatives with WEights of Criterion) and AROMAN (Alternative Ranking Order Method Accounting for two-step Normalization), for material selection in both new manufacturing and maintenance contexts. These approaches represent recent advancements in MCDM (Multiple Criteria Decision Making) techniques. The examination encompasses four distinct scenarios concerning both new manufacturing processes and maintenance tasks: material selection for car protective plates, gear manufacturing, cutting tool materials, and transmission rod materials. Each scenario evaluates the ranking outcomes of materials using the RAWEC and AROMAN methods against alternative MCDM methodologies. While the RAWEC method consistently identifies optimal materials similar to other MCDM techniques across all scenarios, the AROMAN method exhibits limitations particularly in the context of cutting tool material selection, where it fails to discern the best material compared to alternative methods.

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Comparison of RAWEC and AROMAN Methods in Material Selection for Manufacturing or Maintenance

  • Do Duc Trung,
  • Aleksandar Ašonja,
  • Duong Van Duc,
  • Nguyen Chi Bao,
  • Nguyen Hoai Son

摘要

This investigation is designed to contrast two methodologies, RAWEC (Ranking of Alternatives with WEights of Criterion) and AROMAN (Alternative Ranking Order Method Accounting for two-step Normalization), for material selection in both new manufacturing and maintenance contexts. These approaches represent recent advancements in MCDM (Multiple Criteria Decision Making) techniques. The examination encompasses four distinct scenarios concerning both new manufacturing processes and maintenance tasks: material selection for car protective plates, gear manufacturing, cutting tool materials, and transmission rod materials. Each scenario evaluates the ranking outcomes of materials using the RAWEC and AROMAN methods against alternative MCDM methodologies. While the RAWEC method consistently identifies optimal materials similar to other MCDM techniques across all scenarios, the AROMAN method exhibits limitations particularly in the context of cutting tool material selection, where it fails to discern the best material compared to alternative methods.