Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation

Year : 2025 | Volume : 12 | Issue : 02 | Page : 17 26
    By

    Swapna Narla,

  • Sai Sathish Kethu,

  • Durai Rajesh Natarajan,

  • Sreekar Peddi,

  • Dharma Teja Valivarthi,

  • Purandhar N,

  1. Chief Executive Officer, Tek Yantra Inc, California, USA 2Technical Architect, NeuraFlash, Georgia, USA
  2. Technical Architect, NeuraFlash, Georgia, USA
  3. Solution Architect, Estrada Consulting Inc, California, USA
  4. Cloud Security and Infrastructure Architect, Tek Leaders, Texas, USA
  5. Industrial Engineer, Tek Leaders, Texas, USA
  6. Assistant Professor, Department of Computer Science and Engineering (Artificial Intelligence), School of Computers, Madanapalle Institute of Technology and Science, Andhra Pradesh, India

Abstract

Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into determinate outputs. In contrast, the GRU network captures temporal dependencies to establish patterns in machine data over time. This hybrid enables Industry 4.0 objectives through enhanced scalability, handling uncertainty, and real-time decision-making. With 93% accuracy, 92.5% precision, 92.9% recall, and a 92.7% F1 score, the proposed model surpassed competitors and could process data in as little as 4.5 ms. As a reliable, scalable, and flexible alternative to traditional methods, this hybrid system is suitable for real-time machine fault detection in industrial environments.

Keywords: Sugeno fuzzy logic, GRU networks, industrial automation, real-time analysis, and machine defect detection

[This article belongs to Journal of Mechatronics and Automation ]

How to cite this article:
Swapna Narla, Sai Sathish Kethu, Durai Rajesh Natarajan, Sreekar Peddi, Dharma Teja Valivarthi, Purandhar N. Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation. Journal of Mechatronics and Automation. 2025; 12(02):17-26.
How to cite this URL:
Swapna Narla, Sai Sathish Kethu, Durai Rajesh Natarajan, Sreekar Peddi, Dharma Teja Valivarthi, Purandhar N. Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation. Journal of Mechatronics and Automation. 2025; 12(02):17-26. Available from: https://journals.stmjournals.com/joma/article=2025/view=224094


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Regular Issue Subscription Original Research
Volume 12
Issue 02
Received 25/03/2025
Accepted 26/04/2025
Published 15/05/2025
Publication Time 51 Days
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