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Online cutting temperature prediction using ink-jet printed sensors and model order reduction method

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Abstract

In metal cutting, how to measure the tool tip temperature is always an issue. The highest temperature occurs at the contact surface between the tool and the chip, which is difficult for non-contact measuring methods such as the infrared thermal imaging technique. For other measuring methods, such as thermocouples, an additional small hole is required to be drilled before the sensor is able to be placed at the designated position, which greatly increases the cost. This paper presented a cutting temperature measurement with an ink-jet printed thermistor array. The printed sensor had high thermal index β, which possessed high temperature sensitivity, while its miniature dimension contributed to a fast response time. The ink-jet printing sensors can be made in advance so the setup time is short. Also, the sensors can be easily installed at different locations on the tool or the workpiece. In order to estimate the tool tip temperature, the finite element method (FEM) was used with the measured temperatures as inputs, which was known as an inverse heat conduction problem (IHCP). In order to increase computation efficiency to meet the requirement of online monitoring, the model order reduction method (MOR) was applied. In both non-cutting and cutting experiments, the temperature history could be easily estimated. In this study, the tool tip temperature was updated in 0.72 s, while the errors were only about 10% in non-cutting tests. This made it possible for online monitoring of cutting temperatures, while complex tool geometry and boundary conditions were considered.

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source by remote sensors. (b) Estimated temperature of the 300 °C heat source by remote sensors

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Acknowledgements

The authors would like to express their appreciation to Ministry of Science and Technology in Taiwan (grant number NSC101-2221-E-002-011 and NSC 102-2221-E-002-051) for their financial support of this research.

Funding

This study was supported by Ministry of Science and Technology in Taiwan (grant number NSC101-2221-E-002–011 and NSC 102–2221-E-002–051).

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Authors and Affiliations

  1. Department of Mechanical Engineering, National Taiwan University, Taipei, 10617, Taiwan

    Kuan-Ming Li, Chi-Wen Chang & Chia-Hao Chang

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  1. Kuan-Ming Li
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  2. Chi-Wen Chang
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  3. Chia-Hao Chang
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Contributions

Kuan-Ming Li performed conceptualization, resources, writing – original draft, review and editing, project administration, supervision, and funding acquisition. Chi-Wen Chang was involved in methodology, software, formal analysis, investigation, data curation, writing – original draft. Chia-Hao Chang contributed to methodology, software, validation, formal analysis, investigation, and data curation.

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Correspondence to Kuan-Ming Li.

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Li, KM., Chang, CW. & Chang, CH. Online cutting temperature prediction using ink-jet printed sensors and model order reduction method. Int J Adv Manuf Technol 120, 1989–2002 (2022). https://doi.org/10.1007/s00170-022-08900-2

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