Fault Diagnosis Technology in Machinery Manufacturing

Dear Colleagues,

Fault diagnosis in machinery manufacturing is a critical aspect that ensures the reliability, safety, and efficiency of industrial operations. In the age of Industry 4.0, production equipment is becoming more integrated and intelligent, introducing new challenges for data-driven process monitoring and fault diagnosis. This journal explores the current technologies and methodologies used in diagnosing faults in machinery. It highlights the integration of traditional techniques, such as vibration analysis and thermal imaging, with modern advancements like machine learning, artificial intelligence (AI), and the Internet of Things (IoT). These innovations enable real-time monitoring, predictive maintenance, and data-driven decision-making. This journal also integrates the challenges in implementing fault diagnosis systems, including data management, integration with existing systems, and the need for skilled personnel.

Through recent R&D advancements, insights have been provided into the future trends in fault diagnosis technologies, emphasizing the potential for increased automation and accuracy, as well as the development of smarter manufacturing processes.

Prof. Dr. Grover Zurita Villarroel
Prof. Dr. René-Vinicio Sánchez
Guest Editors

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• fault detection and diagnosis technology for machine manufacturing
• vibration analysis for machine manufacturing
• advances diagnostics techniques for machine manufacturing
• neural networks methods for machine manufacturing
• fault diagnosis methods for smart manufacturing
• IoT-based monitoring and diagnostics of manufacturing systems
• remote control and detection and detection technology for intelligent manufacturing
• machine learning methods for machine manufacturing
• applied artificial intelligence for fault detection and diagnosis technology for machine manufacturing
• operational mode analysis for fault diagnostics and diagnostic for machine manufacturing