Abstract
This research aims to propose an innovative framework using ISO14649 standard to detect defects in manufactured shaped objects or geometric surfaces of non-linear products of the CNC machine. The significant importance in order to recognize the potential to improve industry product quality inspection and encourage the waste of timing machines and product rejection. Open Computer Vision (Open CV) offers a smart, non-contact measurement and cost-effective technique to fulfil the requirements. The framework depends on the new technique of Open CV, which includes two parts: an intelligent selection of work-piece capturing the image for a particular inspection of the planar interfaces such as the hole, rectangular, pocket one, and the symmetric lighting model comparison approach for measurement of defects in the matched images. The contribution of this study is to build a structure in the computer vision method with a convolution neural network that predicts the classification of the feature for better accuracy and emphasizes the significant characteristics of the image processing technique coupled with experimental data on demanding image datasets and quality inspection measures.
Highlights
Computer Vision is a newly increasing technology for object identification, analysis, and comprehension
Open Computer Vision (Open CV) is a library developed by Intel that may be available in the Python language as a programming tool
This study continues as auto-inspection with the non-contact section implements the Internet of Things (IoT) to make the machine more open and approximately meet the standard of industry 4.0
Summary
Computer Vision is a newly increasing technology for object identification, analysis, and comprehension. Developing a new inspection technique can measure the model of high-quality products at the lowest possible cost in the close loop of the process chain. The advanced system consists of an open computer vision hardware and software platform to capture the image in real-time and non-contact machine measurement. The new technologies of the intelligent manufacturing inspection system provide potential outcomes for factories all over the world. Developing a new inspection approach will accurately measure the model in the close loop of the process chain of useful high-quality products at the absolute lowest cost. This framework paper presents a new approach to the edge detection algorithm and a planar feature. In order to improve the wastages of timing machines and product rejection, this study is important to deteriorate real-time performance, accuracy, precision
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