Abstract
Over the last twenty years, it has become increasingly obvious that the performance of process control systems depends not only on the control algorithms but also on how these integrate into the operational policy in terms of safety, environmental protection, equipment protection, as well as general monitoring to identify poor performance and detect faults. This calls for creating a virtual environment which is able to provide a comprehensive assessment of performance and can identify the factors which determine it. The important agents which are responsible for bringing these together are the plant operators and supervisors. This implies that it is important to consider them as part of the overall solutions, and if they are part of the system they must be provided with the means of carrying out the role effectively. While attention has been given to improving the interface of control systems for operators and supervisors through the design of information display and alarm systems, most of this is concerned with awareness, with little concern as to processing functionality in assessing the large volume of multivariate data more effectively.
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© 1999 Springer-Verlag London
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Wang, X.Z. (1999). Introduction. In: Data Mining and Knowledge Discovery for Process Monitoring and Control. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-0421-6_1
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DOI: https://doi.org/10.1007/978-1-4471-0421-6_1
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1137-5
Online ISBN: 978-1-4471-0421-6
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