A Neural Network Approach to Tool Wear Detection via Infrared Sensor Monitoring

Jiahua Xia, Rui Song, Lavianna Teng, Zepei Ma, Anwar P. P. Abdul Majeed, Yi Chen, Yang Luo*

*Corresponding author for this work

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

Abstract

The modern manufacturing sector encounters substantial financial setbacks due to unforeseen equipment downtime, hence mandating the implementation of more proactive maintenance strategies. The present study explores the potential of utilising AI-driven thermal imaging to monitor tool conditions in the context of predictive maintenance. In the context of the milling process, infrared camera technology was implemented to observe and assess tool wear and surface finishes. The analysis of key features derived from thermal imaging was conducted using two distinct methodologies: statistical analysis and polynomial feature extraction. Subsequently, a neural network was trained to categorise tools as either “fresh” or “worn”. This study provides a comparative examination of feature extraction techniques, focusing on the significant contributions of neural network and thermal imaging in enhancing predictive maintenance in the manufacturing sector. The study demonstrates that both statistical and polynomial feature extraction methods are effective for tool condition monitoring, with statistical features showing marginally higher success rates across various regions of interest, underscoring their reliability in predictive maintenance applications.

Original languageEnglish
Title of host publicationRobot Intelligence Technology and Applications 8 - Results from the 11th International Conference on Robot Intelligence Technology and Applications
EditorsAnwar P.P. Abdul Majeed, Eng Hwa Yap, Pengcheng Liu, Xiaowei Huang, Anh Nguyen, Wei Chen, Ue-Hwan Kim
PublisherSpringer Science and Business Media Deutschland GmbH
Pages125-133
Number of pages9
ISBN (Print)9783031706837
DOIs
Publication statusPublished - 2024
Event11th International Conference on Robot Intelligence Technology and Applications, RiTA 2023 - Taicang, China
Duration: 6 Dec 20238 Dec 2023

Publication series

NameLecture Notes in Networks and Systems
Volume1132 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference11th International Conference on Robot Intelligence Technology and Applications, RiTA 2023
Country/TerritoryChina
CityTaicang
Period6/12/238/12/23

Keywords

  • artificial intelligence
  • machine learning
  • neural networks
  • Thermal imaging

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