Automated wear characterization for broaching tools based on machine vision systems. (October 2015)

• Record Type: Journal Article
• Authors: Loizou, Jamie; Tian, Wenmeng; Robertson, John; Camelio, Jaime
• Is Part Of: Journal of manufacturing systems. Volume 37:Part 2(2015)
• Page Start: 558
• Page End: 563
• Publication Date: 2015-10
• Subjects: Broaching -- Digital image processing -- Measurement system analysis -- Tool wear characterization; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2015.04.005
• Languages: English
• ISSNs: 0278-6125

Abstract

Abstract: Monitoring tool wear is essential to ensure consistently high quality of machined products. In the past, tool wear has been well characterized in common machining processes such as turning or milling. However, for cutting complex profiles, such as linear broaching, the only method reported for quantifying tool wear has been manual characterization of flank wear. This leads to significant information loss and large measurement variability. In response to these limitations, this paper presents a new measurement system that quantifies broaching tool wear based on the overall wear area. The proposed method uses automated image cropping and digital imaging processing tools to determine the affected area without requiring any manual intervention. A measurement system analysis has been performed on a hexagonal linear broach to determine the variance introduced by the measuring procedures and the image processing analysis. After implementing this measurement system, tool wear characterization for broaching tools becomes more precise, facilitating cross-industry collaboration, making operator training less intensive, and improving quality control practices.