Advances in Fault Detection Techniques for Automated Manufacturing Systems in Industry 4.0

Yassmin Seid Ahmed ^1,2* Abba AbuBakar ^1,2 Abufazal Arif ^1,2 Fadi badour ^1,2

• ¹ King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
• ² Interdisciplinary Research Center for Advanced Materials, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia, Dhahran, Saudi Arabia

Fault detection and diagnosis are essential for maintaining the continuous operation of manufacturing systems. To achieve this, an innovative tool is required to immediately identify any faults in the production process and recommend the appropriate mechanisms to be adopted proactively to prevent future mishaps or accidents. This capability is critical for many industries to improve the efficiency and effectiveness of their production processes. Several methods can be used to detect trends or patterns in any given process and determine if the process variable is within normal limits. However, these techniques may only detect evident process characteristics or defects while leaving behind latent ones. This paper aims to review recent achievements and classics in fault diagnosis and detection, and suggest steps that can be taken to plan and implement this process. It will also explore emerging research streams, critical issues in the field, and strategies that can be applied to overcome these barriers. The paper outlines how the performance of fault detection and diagnostics can be improved in production processes and how a safer and fully efficient production environment can be promoted.