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ORIGINAL RESEARCH article

Front. Robot. AI

Sec. Industrial Robotics and Automation

Volume 12 - 2025 | doi: 10.3389/frobt.2025.1620370

Developing Reliability Centered Maintenance in Automotive Robotic Welding Machines for a Tier 1 Supplier

Provisionally accepted
Hameed  Tolulope Olamide AlakaHameed Tolulope Olamide Alaka1,2*Khumbulani  MpofuKhumbulani Mpofu1Boitumelo  RamatsetseBoitumelo Ramatsetse3Taoreed  Adesola AdegbolaTaoreed Adesola Adegbola4Mathew  Olurotimi AdeotiMathew Olurotimi Adeoti4
  • 1Department of Industrial Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology, Pretoria, South Africa
  • 2Tshwane University of Technology, Pretoria, South Africa
  • 3Department of Industrial Engineering, Witwatersrand University, South Africa, Johannesburg, South Africa
  • 4Department of Mechanical and Mechatronics Engineering, Tshwane University of Technology,, Pretoria, South Africa

The final, formatted version of the article will be published soon.

The study highlights the effectiveness of FMEA in robotic spot-welding operations, providing a systematic approach to enhancing performance in an automotive assembly line. Robotic welding industries depend on mechanized, programmable tools to automate welding processes, ensuring efficiency, reliability, and effective material handling. In the automotive sector, Tier 1 suppliers utilize robotic welding machines to produce high volumes of welded assemblies, with daily output exceeding 450 units. However, frequent equipment downtime due to maintenance challenges disrupts productivity and impacts customer satisfaction. This study aims to develop a Reliability-Centered Maintenance (RCM) approach for robotic welding industries, optimizing machine uptime, enhancing product quality, and reducing financial losses caused by unexpected failures. A three-year dataset was analysed to identify the primary causes of downtime and their associated costs. Failure Modes and Effects Analysis (FMEA) was applied to assess failure modes, determine root causes, and calculate Risk Priority Numbers (RPNs), thereby formulating corrective actions to mitigate recurring failures and enhance operational efficiency. Findings revealed that maintenance-related issues accounted for 79% of total downtime, resulting in financial losses of R2,281,508.82 over three years. The application of FMEA provided a structured framework for prioritizing critical failure modes and implementing targeted corrective measures to reduce downtime and enhance overall reliability. To sustain high productivity and quality, it is recommended that robotic welding industries adopt proactive maintenance strategies based on FMEA findings. Regular monitoring, predictive maintenance, and workforce training will help minimize machine failures and optimize operational efficiency.

Keywords: Reliability, Maintenance, Robotic welding, reliability centred maintenance, Optimising

Received: 02 May 2025; Accepted: 04 Aug 2025.

Copyright: © 2025 Alaka, Mpofu, Ramatsetse, Adegbola and Adeoti. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Hameed Tolulope Olamide Alaka, Department of Industrial Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology, Pretoria, South Africa

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.