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Research Article

Tools and Process of Defect Detection in Automated Manufacturing Systems

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  • @ARTICLE{10.4108/eetsis.4000,
        author={Hussein N. Al-Jubori and Izzat Al-Darraji},
        title={Tools and Process of Defect Detection in Automated Manufacturing Systems},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={10},
        number={6},
        publisher={EAI},
        journal_a={SIS},
        year={2023},
        month={9},
        keywords={Automated Defect detection, Artificial Intelligence, Machine Vision, Sensors, Manufacturing Systems},
        doi={10.4108/eetsis.4000}
    }
    
  • Hussein N. Al-Jubori
    Izzat Al-Darraji
    Year: 2023
    Tools and Process of Defect Detection in Automated Manufacturing Systems
    SIS
    EAI
    DOI: 10.4108/eetsis.4000
Hussein N. Al-Jubori1, Izzat Al-Darraji1,*
  • 1: University of Baghdad
*Contact email: izzat.a@kecbu.uobaghdad.edu.iq

Abstract

INTRODUCTION: A range of tools and technologies are at disposal for the purpose of defect detection. These include but are not limited to sensors, Statistical Process Control (SPC) software, Artificial Intelligence (AI) and machine learning (ML) algorithms, X-ray systems, ultrasound systems, and eddy current systems. OBJECTIVES: The determination of the suitable instrument or combination of instruments is contingent upon the precise production procedure and the category of flaw being identified. In certain cases, defects may necessitate real-time monitoring and analysis through the use of sensors and SPC software, whereas more comprehensive analysis may be required for other defects through the utilization of X-ray or ultrasound systems. METHODS: The utilization of AI and ML algorithms has gained significant traction in the realm of defect detection. This is attributed to their ability to process vast amounts of data and discern patterns that may have otherwise eluded detection. The aforementioned tools have the capability to anticipate potential flaws and implement pre-emptive measures to avert their occurrence. RESULTS: The detection of defects in automated manufacturing systems is a continuous process that necessitates meticulous observation and examination to guarantee prompt and effective identification and resolution of defects. CONCLUSION: The utilization of suitable tools and technologies is imperative for manufacturers to guarantee optimal production quality and operational success.

Keywords
Automated Defect detection, Artificial Intelligence, Machine Vision, Sensors, Manufacturing Systems
Received
2023-07-11
Accepted
2023-09-06
Published
2023-09-27
Publisher
EAI
http://dx.doi.org/10.4108/eetsis.4000

Copyright © 2023 H. N. Al-Jubori et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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