Key Performance Indicators Relevant Fault Diagnosis and Process Control Approaches for Industrial Applications

摘要

With the development of science and technology, automatic control systems have been widely integrated into complex industrial processes such as chemical, polymers, metallurgy, power systems, and semiconductor manufacturing. In order to meet the ever increasing demands for high production efficiency and product quality as well as for economic and ecological operations, today's industrial processes have become more complex and their degree of automation is significantly growing. This development calls for more system reliability, dependability, and safety. Associated with this, process monitoring and control receive considerably enhanced attention, both in the engineering and in the research domains. However, practical processes still continuously pose new challenges due to quality requirements, safety and complex dynamics, performance evaluation, diagnosis, and maintenance, especially the Key Performance Indicators-(KPI-) relevant issues that call for more accurate and efficient operations which challenge the existing process monitoring and control technologies and meanwhile urgently push scientists and engineers to develop new methodologies to solve the above unsolved issues for complex practical plants. Therefore, the establishment and development of new model-based or data-driven process monitoring and control technologies are urgent issues in both theory and applications.