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<p>High-speed machining (HSM) offers significant potential for enhancing surface quality, productivity, and cost efficiency in machining processes. However, its application in difficult-to-machine materials, especially in hard turning, faces challenges related to rapid tool wear and process costs. These challenges, however, can be effectively addressed through multi-objective optimization that considers multiple conflicting objectives. Despite its importance, this approach remains underexplored in the current literature, which typically focuses on single-response optimization. This study addresses these gaps by proposing a comprehensive computational framework for multi-objective optimization in HSM processes. While leveraging established methods, including Response Surface Methodology, Factor Analysis, the Mean Squared Error of the Factor index, and the Normal Boundary Intersection method. A key methodological innovation is the explicit consideration of tool wear progression and its impact on surface roughness throughout the tool’s life, ensuring that process optimization accounts for the dynamic nature of surface quality, an aspect largely neglected in previous studies. To guarantee compliance with surface tolerance requirements, the optimization is based not on mean roughness values but on the maximum Ra observed over the tool life, combined with the upper prediction limit of Ra as a decision criterion. This statistically robust approach enhances reliability in precision machining and contributes to more sustainable manufacturing by reducing non-conforming parts, rework, and premature tool replacement. An experimental study has been performed on hardened AISI 52100 steel (59.5 ± 1 HRC) using mixed ceramic cutting tools at cutting speeds and feed rates ranging from 200 to 300&#xa0;m/min and 0.06–0.14&#xa0;mm/rev, respectively. Increasing the cutting speed proved beneficial for reducing surface roughness (Ra), achieving the lowest value of 0.28&#xa0;μm at 272.20&#xa0;m/min. Raising the speed from 200 to 225&#xa0;m/min resulted in a slight decrease in cost, but beyond 225&#xa0;m/min, the cost increased significantly. On the other hand, increasing the speed from 200 to 300&#xa0;m/min reduce machining times. Tool life optimization allowed for durations between 11.51 and 19.90&#xa0;min.</p>

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A multi-objective optimization framework for sustainable and precision-oriented high-speed hard turning

  • 期刊论文

  • 发表日期：

    2025年11月10日

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  • Luiz Gustavo Paes de Souza,
  • Robson Raimundo Cardoso Ribeiro,
  • Anderson Paulo de Paiva,
  • João Roberto Ferreira

摘要

High-speed machining (HSM) offers significant potential for enhancing surface quality, productivity, and cost efficiency in machining processes. However, its application in difficult-to-machine materials, especially in hard turning, faces challenges related to rapid tool wear and process costs. These challenges, however, can be effectively addressed through multi-objective optimization that considers multiple conflicting objectives. Despite its importance, this approach remains underexplored in the current literature, which typically focuses on single-response optimization. This study addresses these gaps by proposing a comprehensive computational framework for multi-objective optimization in HSM processes. While leveraging established methods, including Response Surface Methodology, Factor Analysis, the Mean Squared Error of the Factor index, and the Normal Boundary Intersection method. A key methodological innovation is the explicit consideration of tool wear progression and its impact on surface roughness throughout the tool’s life, ensuring that process optimization accounts for the dynamic nature of surface quality, an aspect largely neglected in previous studies. To guarantee compliance with surface tolerance requirements, the optimization is based not on mean roughness values but on the maximum Ra observed over the tool life, combined with the upper prediction limit of Ra as a decision criterion. This statistically robust approach enhances reliability in precision machining and contributes to more sustainable manufacturing by reducing non-conforming parts, rework, and premature tool replacement. An experimental study has been performed on hardened AISI 52100 steel (59.5 ± 1 HRC) using mixed ceramic cutting tools at cutting speeds and feed rates ranging from 200 to 300 m/min and 0.06–0.14 mm/rev, respectively. Increasing the cutting speed proved beneficial for reducing surface roughness (Ra), achieving the lowest value of 0.28 μm at 272.20 m/min. Raising the speed from 200 to 225 m/min resulted in a slight decrease in cost, but beyond 225 m/min, the cost increased significantly. On the other hand, increasing the speed from 200 to 300 m/min reduce machining times. Tool life optimization allowed for durations between 11.51 and 19.90 min.