Markov Transition Field and Convolutional Long Short-Term Memory Neural Network for Manufacturing Quality Prediction

Jehn Ruey Jiang, Cheng Tai Yen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes a manufacturing quality prediction method, called MTF-CLSTM, to integrate the Markov transition field (MTF) model and the convolutional long short-term memory (CLSTM) neural network for wire electrical discharge machining (WEDM). Experiments are conducted to evaluate the proposed method in terms of the mean absolute percentage error (MAPE). Experimental results show that the proposed method outperforms a related method proposed recently.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728173993
DOIs
StatePublished - 28 Sep 2020
Event7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020 - Taoyuan, Taiwan
Duration: 28 Sep 202030 Sep 2020

Publication series

Name2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020

Conference

Conference7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
Country/TerritoryTaiwan
CityTaoyuan
Period28/09/2030/09/20

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