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Integration of E-Quality Control Modules with Engineering Computer Numerical Control Laboratory
Conference proceeding   Open access

Integration of E-Quality Control Modules with Engineering Computer Numerical Control Laboratory

Richard Chiou, Yalcin Ertekin, Michael Mauk and Robin Kizirian
Association for Engineering Education - Engineering Library Division Papers, pp 22.920.1-22.920.14
26 Jun 2011
DOI: https://doi.org/10.18260/1-2--18824
url
https://doi.org/10.18260/1-2--18824View
Published, Version of Record (VoR)Maybe Open Access (Publisher Bronze),  Open

Abstract

Computer numerical control Control equipment Coordinate measuring machines Diagnostic systems Image processing Inspection Laboratories Machine vision Manufacturing Measurement techniques Process parameters Quality assessment Quality control Remote control Remote monitoring Students Data Analysis Manufacturing Engineering Miniaturization
The paper presents a major novelty in the integration of multidisciplinary web-based quality control topics into the advanced manufacturing engineering technology as the existing core discipline. This is aligned with a current trend for manufacturing industry, which includes remote monitoring/control/diagnosis, product miniaturization, high precision, zero-defect manufacturing and information-integrated distributed production systems. The use of modern sensors and data acquisition instrumentation for manufacturing processes is implemented into computer numerical control (CNC)laboratory practices in undergraduate classes for Web-based measurement, inspection, diagnostic system, and quality control at Drexel University. The network hardware and software components are integrated with quality methodologies to achieve maximum effectiveness in teaching Web-based quality concepts in MET 316 CNC. In MET 316, a10-week upper-level undergraduate course was offered that included a classroom component presenting lectures on CNC integrated with quality control principles and methods, combined with hands-on laboratory sessions. The class includes product manufacture and quality assessment measurements to support statistical data analysis in a quality control framework. Students made various measurements of CNC-machined parts using a coordinate measuring machine (CMM), machine vision (i.e., a charge coupled device (CCD) camera with image processing software), and laser scanning. Students then analyzed measurement data to compare measurement techniques (Gage R&R), establish part variations, correlate quality metrics with process parameters, and optimize the CNC machining process.

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