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<p>The development of materials and methods used in the aircraft manufacturing industry has been advancing to provide a reliable and mainly lighter aircraft. The use of composite materials becomes essential; however, the processing of this type of material must be studied to obtain the highest manufacturing efficiency and the best product quality. Presently, process control and monitoring tools are integrated into Industry 4.0 concepts such as the internet of things, cloud computing, digital twins, and others. In this sense, this study aims to evaluate the capability of a system assembled with low-cost instrumentation to monitor and report on the state of the tools used in the machining of composite materials with robotic manipulators. This task is carried out based on the analysis of the mechanical vibrations of the motor and cutting tool assembly, thus aiming to reduce waste and guarantee the quality and surface integrity of the finished parts. Process self-awareness is enhanced by combining signal processing algorithms and statistical techniques to aid in constant monitoring of tool wear. In this sense, a digital model is constantly updated to optimize the cutting process.</p>

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Tool wear monitoring in robotic milling of composite materials using low-cost vibration-based instrumentation

  • 期刊论文

  • 发表日期：

    2025年10月9日

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  • José Otávio Savazzi,
  • Sidney Bruce Shiki,
  • Gustavo Franco Barbosa

摘要

The development of materials and methods used in the aircraft manufacturing industry has been advancing to provide a reliable and mainly lighter aircraft. The use of composite materials becomes essential; however, the processing of this type of material must be studied to obtain the highest manufacturing efficiency and the best product quality. Presently, process control and monitoring tools are integrated into Industry 4.0 concepts such as the internet of things, cloud computing, digital twins, and others. In this sense, this study aims to evaluate the capability of a system assembled with low-cost instrumentation to monitor and report on the state of the tools used in the machining of composite materials with robotic manipulators. This task is carried out based on the analysis of the mechanical vibrations of the motor and cutting tool assembly, thus aiming to reduce waste and guarantee the quality and surface integrity of the finished parts. Process self-awareness is enhanced by combining signal processing algorithms and statistical techniques to aid in constant monitoring of tool wear. In this sense, a digital model is constantly updated to optimize the cutting process.