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<p>Multi-axis computer numerical control machines are increasingly present in the industry, as both production performance and the complexity of operational tasks continue to rise. In this context, the machine selection process remains a perpetual challenge due to the multitude of possible machine configurations. Machines are generally used to perform different tasks, which explains why selection methods remain to be developed with a view to optimizing machine configuration for a specific task while minimizing machine cost. Special-purpose machines are usually selected off-the-shelf, designed based on experience, or focused on overall performance, often resulting in inadequate performance for the required task. With the aim to help the designer in the architecture selection process at the pre-study stage, a new task-based optimization method is proposed in this article, allowing to identify both optimal machine geometric parameters and joint tolerances, while minimizing the cost of key machine components. Task specifications, represented by the spatio-temporal tool trajectory, are defined as optimization constraints. The proposed method is applied to the selection of a five-axis machine architecture in the context of additive manufacturing for medical orthoses. The step-by-step optimization process, along with the results on costs and optimal parameters, is presented and discussed.</p>

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Manufacturing task-based optimization of multi-axis CNC machine tool architectures at the pre-design stage

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年8月1日

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  • Alexis Claude,
  • Maxime Chalvin,
  • Sébastien Campocasso,
  • Vincent Hugel,
  • Mathieu Orzalesi

摘要

Multi-axis computer numerical control machines are increasingly present in the industry, as both production performance and the complexity of operational tasks continue to rise. In this context, the machine selection process remains a perpetual challenge due to the multitude of possible machine configurations. Machines are generally used to perform different tasks, which explains why selection methods remain to be developed with a view to optimizing machine configuration for a specific task while minimizing machine cost. Special-purpose machines are usually selected off-the-shelf, designed based on experience, or focused on overall performance, often resulting in inadequate performance for the required task. With the aim to help the designer in the architecture selection process at the pre-study stage, a new task-based optimization method is proposed in this article, allowing to identify both optimal machine geometric parameters and joint tolerances, while minimizing the cost of key machine components. Task specifications, represented by the spatio-temporal tool trajectory, are defined as optimization constraints. The proposed method is applied to the selection of a five-axis machine architecture in the context of additive manufacturing for medical orthoses. The step-by-step optimization process, along with the results on costs and optimal parameters, is presented and discussed.