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

抄録

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.