Implementation of Machine Vision based Quality Inspection in Production: An Approach for the Accelerated Execution of Case Studies

Abstract

The implementation of machine vision based quality inspection systems increases productivity and reduces human error during visual inspection, thus improving product quality. During the planning process of these inspection systems, case studies are executed to evaluate and ensure applicability, which so far has been an iterative and inefficient process due to the lack of existing methodologies and guidelines. Therefore, this paper presents a holistic approach for efficiently executing case studies to plan and implement machine vision based quality inspection systems in production. An evaluation via an industrial use-case resulted in a significantly quicker planning process.