Advancements in Roundness Measurement Parts for Industrial Automation Using Internet of Things Architecture-Based Computer Vision and Image Processing Techniques

Saif, Yazid; Rus, Anika Zafiah M.; Yusof, Yusri; Ahmed, Maznah Lliyas; Al-Alimi, Sami; Didane, Djamal Hissein; Adam, Anbia; Gu, Yeong Hyeon; Al-masni, Mohammed A.; Abdulrab, Hakim Qaid Abdullah

doi:10.3390/app132011419

Open AccessArticle

Advancements in Roundness Measurement Parts for Industrial Automation Using Internet of Things Architecture-Based Computer Vision and Image Processing Techniques

by

Yazid Saif

¹

,

Anika Zafiah M. Rus

^1,*,

Yusri Yusof

¹,

Maznah Lliyas Ahmed

^2,*,

Sami Al-Alimi

¹,

Djamal Hissein Didane

¹

,

Anbia Adam

³,

Yeong Hyeon Gu

^4,*

,

Mohammed A. Al-masni

⁴

and

Hakim Qaid Abdullah Abdulrab

⁵

¹

Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja 86400, Johor, Malaysia

²

Politeknik Sultan Azlan Shah, Behrang Stesion, Behrang 35950, Perak, Malaysia

³

Faculty of Mechanical and Manufacturing Engineering Technology, Universiti Teknikal Malaysia Meleka (UTeM), Durian Tunggal 76100, Melaka, Malaysia

⁴

Department of Artificial Intelligence, College of Software and Convergence Technology, Sejong University, Seoul 05006, Republic of Korea

⁵

Department of Electrical and Electronics Engineering, University Teknologi PETRONAS, Seri Iskandar 32610, Perak, Malaysia

^*

Authors to whom correspondence should be addressed.

Appl. Sci. 2023, 13(20), 11419; https://doi.org/10.3390/app132011419

Submission received: 18 July 2023 / Revised: 15 October 2023 / Accepted: 16 October 2023 / Published: 18 October 2023

(This article belongs to the Special Issue Advanced Manufacturing Technologies: Development and Prospect)

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Abstract

In the era of Industry 4.0, the digital capture of products has become a critical aspect, which prompts the need for reliable inspection methods. In the current technological landscape, the Internet of Things (IoT) holds significant value, especially for industrial devices that require seamless communication with local and cloud computing servers. This research focuses on the advancements made in roundness measurement techniques for industrial automation by leveraging an IoT architecture, computer vision, and image processing. The interconnectedness enables the efficient collection of feedback information, meeting the demands of closed-loop manufacturing. The accuracy and performance of assemblies heavily rely on the roundness of specific workpiece components. In order to address this problem, automated inspection methods are needed. A new method of computer vision for measuring and inspecting roundness is proposed in this paper. This method uses a non-contact method that takes into account all points on the contours of measured objects, making it more accurate and practical than conventional methods. The system developed by AMMC Laboratory captures Delrin work images and analyzes them using a specially designed 3SMVI system based on Open CV with Python script language. The system can measure and inspect several rounded components in the same part, including external frames and internal holes. It is calibrated to accommodate various units of measurement and has been tested using sample holes within the surface feature of the workpiece. According to the results of both techniques, there is a noticeable difference ranging from 2.9 µm to 11.6 µm. However, the accuracy of the measurements can be enhanced by utilizing a high-resolution camera with proper lighting. The results were compared to those obtained using a computer measurement machine (CMM), with a maximum difference of 8.7%.

Keywords: computer vision; image processing; CMM; 3SMVI; inspection; IoT; roundness

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MDPI and ACS Style

Saif, Y.; Rus, A.Z.M.; Yusof, Y.; Ahmed, M.L.; Al-Alimi, S.; Didane, D.H.; Adam, A.; Gu, Y.H.; Al-masni, M.A.; Abdulrab, H.Q.A. Advancements in Roundness Measurement Parts for Industrial Automation Using Internet of Things Architecture-Based Computer Vision and Image Processing Techniques. Appl. Sci. 2023, 13, 11419. https://doi.org/10.3390/app132011419

AMA Style

Saif Y, Rus AZM, Yusof Y, Ahmed ML, Al-Alimi S, Didane DH, Adam A, Gu YH, Al-masni MA, Abdulrab HQA. Advancements in Roundness Measurement Parts for Industrial Automation Using Internet of Things Architecture-Based Computer Vision and Image Processing Techniques. Applied Sciences. 2023; 13(20):11419. https://doi.org/10.3390/app132011419

Chicago/Turabian Style

Saif, Yazid, Anika Zafiah M. Rus, Yusri Yusof, Maznah Lliyas Ahmed, Sami Al-Alimi, Djamal Hissein Didane, Anbia Adam, Yeong Hyeon Gu, Mohammed A. Al-masni, and Hakim Qaid Abdullah Abdulrab. 2023. "Advancements in Roundness Measurement Parts for Industrial Automation Using Internet of Things Architecture-Based Computer Vision and Image Processing Techniques" Applied Sciences 13, no. 20: 11419. https://doi.org/10.3390/app132011419

APA Style

Saif, Y., Rus, A. Z. M., Yusof, Y., Ahmed, M. L., Al-Alimi, S., Didane, D. H., Adam, A., Gu, Y. H., Al-masni, M. A., & Abdulrab, H. Q. A. (2023). Advancements in Roundness Measurement Parts for Industrial Automation Using Internet of Things Architecture-Based Computer Vision and Image Processing Techniques. Applied Sciences, 13(20), 11419. https://doi.org/10.3390/app132011419

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Advancements in Roundness Measurement Parts for Industrial Automation Using Internet of Things Architecture-Based Computer Vision and Image Processing Techniques

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