Smart Segregation and Defect Detection of Nuts for Fasteners Industries

Akhilesh Kumar; Gurleen Kaur; Bhavyae Mittal; Gaurav Sapra; Rajesh Kumar; Garima Joshi

doi:10.1007/978-981-19-1906-0_23

Smart Segregation and Defect Detection of Nuts for Fasteners Industries

Akhilesh Kumar, Gurleen Kaur, Bhavyae Mittal, Gaurav Sapra, Rajesh Kumar, Garima Joshi

Panjab University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents the design and fabrication of economically viable nut segregation and defect detection machine for fasteners industries. This prototype is developed to help manufacturers in achieving quality assurance at minimal cost. Simulations are performed in ANSYS to optimize the design parameters of machine prototype. Working of machine prototype is categorized in three stages: (i) linearization, (ii) slot allocation, and (iii) image processing. To segregate, the individual nut from the feeder motoring mechanism is adopted for the linearization stage. For defect analysis, nuts are moved with the help of a motor on the vacant slots of rotating disk mounted with camera at fixed location. Images of nuts are captured by camera and processed for defect detection by adopting edge detection and background subtraction algorithms in image processing. The detection of nut dimensions using machine prototype is also reported.

Original language	English
Title of host publication	Microelectronics, Communication Systems, Machine Learning and Internet of Things - Select Proceedings of MCMI 2020
Editors	Vijay Nath, Jyotsna Kumar Mandal
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	253-259
Number of pages	7
ISBN (Print)	9789811919053
DOIs	https://doi.org/10.1007/978-981-19-1906-0_23
State	Published - 2023
Externally published	Yes
Event	1st International Conference on Microelectronics, Communication Systems, Machine Learning, and Internet of Things, MCMI 2020 - Ranchi, India Duration: 12 Sep 2020 → 13 Sep 2020

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	887
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	1st International Conference on Microelectronics, Communication Systems, Machine Learning, and Internet of Things, MCMI 2020
Country/Territory	India
City	Ranchi
Period	12/09/20 → 13/09/20

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Keywords

Finite element analysis
Image processing
Linearization
Segregation of nuts
Slot allocation

Access to Document

10.1007/978-981-19-1906-0_23

Cite this

Kumar, A., Kaur, G., Mittal, B., Sapra, G., Kumar, R., & Joshi, G. (2023). Smart Segregation and Defect Detection of Nuts for Fasteners Industries. In V. Nath, & J. K. Mandal (Eds.), Microelectronics, Communication Systems, Machine Learning and Internet of Things - Select Proceedings of MCMI 2020 (pp. 253-259). (Lecture Notes in Electrical Engineering; Vol. 887). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-1906-0_23

Kumar, Akhilesh ; Kaur, Gurleen ; Mittal, Bhavyae et al. / Smart Segregation and Defect Detection of Nuts for Fasteners Industries. Microelectronics, Communication Systems, Machine Learning and Internet of Things - Select Proceedings of MCMI 2020. editor / Vijay Nath ; Jyotsna Kumar Mandal. Springer Science and Business Media Deutschland GmbH, 2023. pp. 253-259 (Lecture Notes in Electrical Engineering).

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abstract = "This paper presents the design and fabrication of economically viable nut segregation and defect detection machine for fasteners industries. This prototype is developed to help manufacturers in achieving quality assurance at minimal cost. Simulations are performed in ANSYS to optimize the design parameters of machine prototype. Working of machine prototype is categorized in three stages: (i) linearization, (ii) slot allocation, and (iii) image processing. To segregate, the individual nut from the feeder motoring mechanism is adopted for the linearization stage. For defect analysis, nuts are moved with the help of a motor on the vacant slots of rotating disk mounted with camera at fixed location. Images of nuts are captured by camera and processed for defect detection by adopting edge detection and background subtraction algorithms in image processing. The detection of nut dimensions using machine prototype is also reported.",

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Kumar, A, Kaur, G, Mittal, B, Sapra, G, Kumar, R & Joshi, G 2023, Smart Segregation and Defect Detection of Nuts for Fasteners Industries. in V Nath & JK Mandal (eds), Microelectronics, Communication Systems, Machine Learning and Internet of Things - Select Proceedings of MCMI 2020. Lecture Notes in Electrical Engineering, vol. 887, Springer Science and Business Media Deutschland GmbH, pp. 253-259, 1st International Conference on Microelectronics, Communication Systems, Machine Learning, and Internet of Things, MCMI 2020, Ranchi, India, 12/09/20. https://doi.org/10.1007/978-981-19-1906-0_23

Smart Segregation and Defect Detection of Nuts for Fasteners Industries. / Kumar, Akhilesh; Kaur, Gurleen; Mittal, Bhavyae et al.
Microelectronics, Communication Systems, Machine Learning and Internet of Things - Select Proceedings of MCMI 2020. ed. / Vijay Nath; Jyotsna Kumar Mandal. Springer Science and Business Media Deutschland GmbH, 2023. p. 253-259 (Lecture Notes in Electrical Engineering; Vol. 887).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Kumar A, Kaur G, Mittal B, Sapra G, Kumar R, Joshi G. Smart Segregation and Defect Detection of Nuts for Fasteners Industries. In Nath V, Mandal JK, editors, Microelectronics, Communication Systems, Machine Learning and Internet of Things - Select Proceedings of MCMI 2020. Springer Science and Business Media Deutschland GmbH. 2023. p. 253-259. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-19-1906-0_23

Smart Segregation and Defect Detection of Nuts for Fasteners Industries

Abstract

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Keywords

Access to Document

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