A Model-Based Visual Inspection System (MBVIS) for Critical Plastic Bottle Dimensional Measurements

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Abstract

Manufacturers have begun to adopt advanced digital methods and tools to release higher-quality products more quickly at a lower cost. Model-based technologies and Visual/Vision Inspection System (VIS) are two representative approaches and are trends to facilitate manufacturers’ digitalization. With model-based technologies, manufacturers can define digital product requirements and specifications as the primary data source for engineering activities during the product lifecycle rather than relying on traditional paper-based documents. Moreover, the manufacturers can improve product defect detection efficiency and reduce labor requirements by implementing a VIS without artificial visual inspection in their inspection process. Traditionally, inspectors rely heavily on information from Two-Dimensional (2D) engineering drawings to inspect manufactured products with/without a VIS. This inspection process is out of the model-based context, hindering manufacturers from transiting paper-based to model-based processes. This paper developed a Model-Based Visual Inspection System (MBVIS) driven by Geometric Dimensioning and Tolerancing (GD&T) information extracted from an MBD dataset. The proposed system established the feedback mechanism from the inspection phase to the design and manufacturing phases of the product lifecycle in a model-based environment. In addition, the system dynamically supported reading Regions of Interest (ROIs) from user selection and intelligently published analyzed inspection results. The proposed approach was also evaluated by Bland and Altman (B&A) plot analysis on a pharmaceutical plastic bottle from an industrial partner of the Digital Enterprise Center (DEC) at Purdue University.

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CITATION STYLE

APA

Zhou, J., & Hartman, N. W. (2024). A Model-Based Visual Inspection System (MBVIS) for Critical Plastic Bottle Dimensional Measurements. Computer-Aided Design and Applications, 21(2), 270–280. https://doi.org/10.14733/cadaps.2024.270-280

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