The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 17, 2019

Filed:

Dec. 07, 2017
Applicant:

Metal Industries Research & Development Centre, Kaohsiung, TW;

Inventors:

Haw-Ching Yang, Tainan, TW;

Min-Nan Wu, Kaohsiung, TW;

Cheng-Yen Chen, Kaohsiung, TW;

Wen-Chieh Wu, Taichung, TW;

Chia-Ming Jan, Kaohsiung, TW;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 19/00 (2018.01); B23H 7/20 (2006.01); G05B 13/04 (2006.01); B23H 1/02 (2006.01); G05B 19/418 (2006.01); B23H 7/02 (2006.01);
U.S. Cl.
CPC ...
B23H 7/20 (2013.01); B23H 1/02 (2013.01); G05B 13/041 (2013.01); G05B 19/41875 (2013.01); B23H 7/02 (2013.01); G05B 2219/32194 (2013.01); G05B 2219/45221 (2013.01);
Abstract

A method for predicting precision of an electrical discharge machine is provided. In the method, plural sets of process data are obtained while the electrical discharge machine processes workpiece samples. Process features are established based on the process data. Each of the workpiece samples with respect to each of at least one measurement item is measured by using a metrology tool, thereby obtaining measurement values of the workpiece samples with respect to each measurement item. A correlation analysis operation is performed to obtain correlation coefficients. At least one key feature is selected from the process features as representative according to the correlation coefficients. The measurement values of the workpiece samples with respect to each measurement item, and the sets of process data corresponding to the key features are used to build a predictive model for predicting the precision of the electrical discharge machine.


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