Machine learning-based shape error estimation in micromilling by using motor current

Kenta Mizuhara, Daisuke Nakamichi, Wataru Yanagihara, Yasuhiro Kakinuma

Research output: Contribution to conferencePaperpeer-review

Abstract

The requirement for Mass production of Microlens array (MLA) mold is increasing. MLA molds are manufactured by 5-axis ultra-precision machining center using an ultra-small diameter end mill. Since visual examination is not good at judging quality of product while machining, the development of effective process monitoring technology is required. The ultra-precision machining center used in this study employs a linear motor and has low sliding resistance while machining. Therefore, machining information is directly reflected in servo information. Focusing on this point, we developed a machine learning-based shape error estimation model using servomotor current alone and discussed its usefulness.

Original languageEnglish
Pages594-596
Number of pages3
Publication statusPublished - 2021
Event10th International Conference on Leading Edge Manufacturing Technologies in 21st Century, LEM 2021 - Virtual, Online
Duration: 2021 Nov 142021 Nov 18

Conference

Conference10th International Conference on Leading Edge Manufacturing Technologies in 21st Century, LEM 2021
CityVirtual, Online
Period21/11/1421/11/18

Keywords

  • Machine learning
  • Micro lens array
  • Sensorless
  • Servo motor current
  • Shape error estimation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Industrial and Manufacturing Engineering
  • Electronic, Optical and Magnetic Materials

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