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

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Publicado en:Association for Engineering Education - Engineering Library Division Papers (Jun 26, 2011), p. 22.920.1
Autor principal: Chiou, Richard
Otros Autores: Ertekin, Yalcin, Mauk, Michael G, Kizirian, Robin
Publicado:
American Society for Engineering Education-ASEE
Materias:
Data analysis
Quality assessment
Machine vision
Quality control
Inspection
Coordinate measuring machines
Remote control
Remote monitoring
Measurement techniques
Diagnostic systems
Manufacturing engineering
Image processing
Miniaturization
Students
Process parameters
Control equipment
Numerical controls
Manufacturing
Data processing
Laboratories
Teaching
Medical diagnosis
Engineering
Data quality
Measurement
Lectures
Interdisciplinary aspects
Acceso en línea:Citation/Abstract
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Resumen:The paper presents a major novelty in the integration of multidisciplinary web-basedquality control topics into the advanced manufacturing engineering technology as theexisting core discipline. This is aligned with a current trend for manufacturing industry,which includes remote monitoring/control/diagnosis, product miniaturization, highprecision, zero-defect manufacturing and information-integrated distributed productionsystems. The use of modern sensors and data acquisition instrumentation formanufacturing 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 andsoftware components are integrated with quality methodologies to achieve maximumeffectiveness in teaching Web-based quality concepts in MET 316 CNC. In MET 316, a10-week upper-level undergraduate course was offered that included a classroomcomponent presenting lectures on CNC integrated with quality control principles andmethods, combined with hands-on laboratory sessions. The class includes productmanufacture and quality assessment measurements to support statistical data analysis in aquality control framework. Students made various measurements of CNC-machined partsusing a coordinate measuring machine (CMM), machine vision (i.e., a charge coupleddevice (CCD) camera with image processing software), and laser scanning. Students thenanalyzed measurement data to compare measurement techniques (Gage R&R), establishpart variations, correlate quality metrics with process parameters, and optimize the CNCmachining process.
Fuente:Library Science Database