Texture Descriptors for Automatic Estimation of Workpiece Quality in Milling

Castejón-Limas, Manuel; Sánchez-González, Lídia; Díez-González, Javier; Fernández-Robles, Laura; Riego, Virginia; Pérez, Hilde

doi:10.1007/978-3-030-29859-3_62

Cited by 5 publications

(2 citation statements)

References 12 publications

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“…In [2] a method to identify wear areas on machined workpieces is proposed; such computer vision is based on the use of an industrial boroscope that allows us to obtain images since it is linked to a microscope camera. The illumination system employs white LED.…”

Section: Inspection Methodsmentioning

confidence: 99%

Burr Detection Using Image Processing in Milling Workpieces

Castillo

Sánchez-González

Fernández-Robles

et al. 2020

Advances in Intelligent Systems and Computing

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Manufacturing processes require to satisfy quality standards in the produced parts. In particular, the edge finishing must be burr-free, avoiding that it yields different problems such as wasting time removing them what increases the production cost and time. A burr can be noticed microscopically, but it can contain imperfections or evidence of poor piece design. In order to detect automatically this imperfections and to evaluate the quality of the edge finishing, this paper proposes a complete vision based method using image processing and linear regression. With the calculated function, the slope is isolated and compared to obtain quality assessment thresholds. Results validate the good performance of the proposed method to differenciate three types of burrs.

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Section: Inspection Methodsmentioning

confidence: 99%

Burr Detection Using Image Processing in Milling Workpieces

Castillo

Sánchez-González

Fernández-Robles

et al. 2020

Advances in Intelligent Systems and Computing

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“…To quantify the quality of products, it is necessary to measure the physical parameters of the products (e.g., dimensional, strength, finishes). In this context, various systems are used, such as visual inspection [8] or manual or automated sample testing.…”

Section: Introductionmentioning

confidence: 99%

Full Automation of a Manual Inspection Unit for Industrial Borescopy

Gil-Cuadrado,

Martínez-Gutiérrez,

Díez-González

et al. 2023

Advances in Science and Technology

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The digitization of processes in the context of Smart Manufacturing enables the control and monitoring of production processes. Visual inspection of parts is a process where the surface finish of machined parts is evaluated. For this purpose, manual inspection units have been traditionally used to evaluate the validity of the parts. This manual inspection process requires the operator to position the lens to obtain the images, which supposes an inefficient and non-repeatable process producing a considerable waste of production time. In order to design a more competitive process in the context of Smart Manufacturing, we fully automate in this paper an industrial borescopy unit by implementing closed-loop stepper motors, sensors, and microcontrollers. In addition, a web server has been programmed where operators monitor and upload ISO codes depending on the inspected part. This web server is connected to the microcontroller and the borescope positioning camera for automatic imaging. Therefore, the visual part inspection unit has been digitized and provided with connectivity and intelligence as the cyber physical system of the Smart Manufacturing.

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