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This study investigates the application of a multi-criteria decision-making (MCDM) approach to identify the optimal dressing factors for surface grinding of Hardox 500 steel. The problem was addressed using the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method, while the weights of the evaluation criteria were objectively found using the Entropy method. Two performance indicators—surface roughness (Ra) and material removal rate (MRR)—were selected as decision criteria. Five dressing parameters were evaluated: non-feeding dressing (Nnon), fine dressing depth (Tf), fine dressing times (Nf), rough dressing depth (Tr), and rough dressing times (Nr). A total of 16 experimental trials were designed and executed using an L16 (44 × 21) orthogonal array. The results revealed that dressing option No. 6, defined by Tr = 0.02 mm, Nr = 2 times, Nf = 0 times, Tf = 0.01 mm, and Nnon = 3, yielded the most favorable balance between Ra and MRR. This research demonstrates the effectiveness of integrating MARCOS and Entropy methods in optimizing dressing strategies for hard-to-machine materials.

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Application of MARCOS Method for Determining Best Dressing Mode for Surface Grinding Hardox 500

  • 会议论文

  • 发表日期：

    2026年

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  • Dinh Van Thanh,
  • Tran Quoc Hung,
  • Luu Anh Tung,
  • Nguyen Thanh Tu

摘要

This study investigates the application of a multi-criteria decision-making (MCDM) approach to identify the optimal dressing factors for surface grinding of Hardox 500 steel. The problem was addressed using the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method, while the weights of the evaluation criteria were objectively found using the Entropy method. Two performance indicators—surface roughness (Ra) and material removal rate (MRR)—were selected as decision criteria. Five dressing parameters were evaluated: non-feeding dressing (Nnon), fine dressing depth (Tf), fine dressing times (Nf), rough dressing depth (Tr), and rough dressing times (Nr). A total of 16 experimental trials were designed and executed using an L16 (44 × 21) orthogonal array. The results revealed that dressing option No. 6, defined by Tr = 0.02 mm, Nr = 2 times, Nf = 0 times, Tf = 0.01 mm, and Nnon = 3, yielded the most favorable balance between Ra and MRR. This research demonstrates the effectiveness of integrating MARCOS and Entropy methods in optimizing dressing strategies for hard-to-machine materials.