Abstract
The previous nine chapters present a number of control algorithms and their applications to unit operation of paper machines. The growing complexity of industrial processes and the need for higher efficiency, great flexibility, better product quality, lower cost and environment protection have changed the face of industrial practice. Mill wide information management, decision-making automation and operation support have become very crucial for the modern pulp and paper company to stay competitive internationally. Artificial intelligence can play an important role in attaining the above goal. Considering that most of the nowadays modern pulp and paper mills have successfully installed distributed computer control systems (DCS) and information management systems, it is of very significant economic benefit to improve the existing systems by adding “intelligence” and enhancing functionality. This chapter presents an intelligent on-line monitoring and control system (IOMCS) for pulp and paper processes. IOMCS is a real-time intelligent system which links with DCS and a mill wide information system. It takes advantage from the DCS value-added data in the information management system. The system fulfills functions such as monitoring the process for abnormal situations; advising evasive and corrective operation actions to operators; pulp quality prediction; and operation optimization. Unlike in the previous chapters, we will not limit our attention to paper machines, but to whole pulp and paper processes. The techniques proposed in this chapter are applicable to paper machines.
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© 1994 Springer-Verlag London Limited
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Rao, M., Xia, Q., Ying, Y. (1994). IOMCS for Pulp and Paper Processes. In: Modeling and Advanced Control for Process Industries. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-2094-0_10
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DOI: https://doi.org/10.1007/978-1-4471-2094-0_10
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