Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability

This volume collects the latest research in condition monitoring, plant maintenance, and reliability from the 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network. Topics include vibro-acoustics monitoring, condition-based maintenance, sensing and instrumentation, machine health monitoring, maintenance auditing and organization, non-destructive testing, reliability, asset management, condition monitoring, life-cycle cost optimization, prognostics and health management, maintenance performance measurement, manufacturing process monitoring, and robot-based monitoring and diagnostics.

Format: Paperback / softback
Length: 935 pages
Publication date: 17 May 2022
Publisher: Springer Nature Switzerland AG

This comprehensive volume presents the latest advancements, innovations, and applications in the field of condition monitoring, plant maintenance, and reliability, as showcased by esteemed international researchers and engineers during the 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network (IncoME-V & CEPE Net-2020), held in Zhuhai, China, from October 23 to 25, 2020. The diverse range of topics covered in this publication includes vibro-acoustics monitoring, condition-based maintenance, sensing and instrumentation, machine health monitoring, maintenance auditing and organization, non-destructive testing, reliability, asset management, condition monitoring, life-cycle cost optimization, prognostics and health management, maintenance performance measurement, manufacturing process monitoring, and robot-based monitoring and diagnostics. The contributions, meticulously selected through a rigorous international peer-review process, offer insightful ideas that will ignite new research directions and foster innovative multidisciplinary collaborations.

Introduction:
Condition monitoring, plant maintenance, and reliability play pivotal roles in ensuring the efficient and effective operation of industrial systems. With the increasing demand for higher productivity, reduced downtime, and enhanced safety, there is a growing need for advanced technologies and methodologies to optimize these processes. The 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network (IncoME-V & CEPE Net-2020) provided a platform for researchers and engineers from around the world to share their latest findings and advancements in this field.

Highlights of the Conference:
The conference featured a wide range of presentations and discussions on various aspects of condition monitoring, plant maintenance, and reliability. Some of the key topics covered included:

Vibro-Acoustics Monitoring: This field involves the use of sound and vibration to detect and diagnose equipment faults and abnormalities. The conference showcased innovative techniques such as machine learning, artificial intelligence, and data analytics to enhance the accuracy and reliability of vibro-acoustics monitoring.

Condition-Based Maintenance: Condition-based maintenance is a proactive approach to maintenance that focuses on monitoring the actual condition of equipment rather than relying solely on scheduled maintenance. The conference discussed the development of condition-based maintenance algorithms, sensors, and instrumentation to improve the efficiency and effectiveness of maintenance operations.

Sensing and Instrumentation: Advances in sensing and instrumentation technologies have enabled the development of more accurate and reliable monitoring systems. The conference presented the latest developments in sensor technologies, data acquisition systems, and wireless communication protocols to facilitate remote monitoring and data collection.

Machine Health Monitoring: Machine health monitoring is a technique that uses real-time data analysis and machine learning algorithms to predict equipment failures and optimize maintenance schedules. The conference discussed the development of machine health monitoring systems, algorithms, and tools to improve the reliability and availability of industrial equipment.

Maintenance Auditing and Organization: Effective maintenance auditing and organization are essential for ensuring the efficient and effective use of resources. The conference explored the development of maintenance auditing systems, best practices, and organizational strategies to improve maintenance performance and reduce costs.

Non-Destructive Testing: Non-destructive testing is a technique that uses various methods to evaluate the condition of equipment without causing damage. The conference presented the latest developments in non-destructive testing technologies, such as ultrasound, X-ray, and infrared imaging, to improve the accuracy and efficiency of testing operations.

Reliability: Reliability is a critical aspect of industrial equipment and systems. The conference discussed the development of reliability models, failure analysis techniques, and maintenance strategies to improve the reliability of industrial equipment and systems.

Asset Management: Asset management is a process that involves the strategic planning, acquisition, and disposal of assets to optimize their performance and cost-effectiveness. The conference explored the development of asset management systems, tools, and methodologies to improve the efficiency and effectiveness of asset management operations.

Condition Monitoring, Life-Cycle Cost Optimization, and Prognostics and Health Management: Condition monitoring, life-cycle cost optimization, and prognostics and health management are techniques that involve the continuous monitoring and analysis of equipment to optimize its performance and lifespan. The conference presented the latest developments in these techniques, including the use of artificial intelligence, machine learning, and data analytics to improve the accuracy and efficiency of monitoring and analysis operations.

Maintenance Performance Measurement: Maintenance performance measurement is a process that involves the quantification and evaluation of maintenance activities to improve maintenance performance and reduce costs. The conference discussed the development of maintenance performance measurement systems, tools, and methodologies to improve the efficiency and effectiveness of maintenance operations.

Manufacturing Process Monitoring: Manufacturing process monitoring is a technique that involves the continuous monitoring and analysis of manufacturing processes to optimize production efficiency and quality. The conference presented the latest developments in manufacturing process monitoring technologies, such as sensor technologies, data acquisition systems, and machine learning algorithms, to improve the efficiency and effectiveness of manufacturing processes.

Robot-Based Monitoring and Diagnostics: Robot-based monitoring and diagnostics are emerging technologies that involve the use of robots to perform monitoring and diagnostic tasks in industrial environments. The conference presented the latest developments in robot-based monitoring and diagnostics technologies, including the use of robots for inspection, maintenance, and repair tasks.

Conclusion:
The 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network (IncoME-V & CEPE Net-2020) provided a valuable platform for researchers and engineers to share their latest findings and advancements in the field of condition monitoring, plant maintenance, and reliability. The contributions presented in this volume will undoubtedly spur novel research directions and foster new multidisciplinary collaborations. As the world continues to evolve, the importance of condition monitoring, plant maintenance, and reliability will only increase, and the insights and technologies presented in this publication will play a crucial role in shaping the future of these fields.

Weight: 1430g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030757953
Edition number: 1st ed. 2021