Process control and automation
- Introduction to process control and automation
- Development of process automation
- Fibre process automation
- Chemical recovery as a control object
- Advances in paper machine automation
- Paper machine as a dynamical system
- Tasks in paper machine control and management
- Control of stock flow concentration and quality
- Machine direction control
- Cross-directional control – The static optimisation
- Cross-directional control – Dynamics
- Cross-directional control – further aspects
- Controlling functional paper properties
- Managing grade chances in the paper machine
- Managing disturbances caused by broke and recovered solids
- Millwide systems
- Modelling and control methods
Statistical process control Statistical process control (SPC) strives for continuous improvement in product quality and production costs. A definition of quality as “the degree of fitness for purpose or function” 1 emphasises the fact that quality is a measure of satisfying customer needs. In practice, SPC means a group of statistical tools used in estimating
Authors & references
Authors:
Professor Emeritus Kauko Leiviskä, University of Oulu
References:
- Oakland, J. S. 1996. Statistical process control. 3rd subedition. Butterworth-Heinemann, London, 438 p.
- Smith, K. E. 1985. Statistical controls improve quality, boost productivity at Federal mill. Pulp & Paper 59(1):132–135.
- Aldrich, W. D. 1990. Statistical process control and the philosophy of quality improvement. In: 24th EUCEPA Conference Proceedings, Control, Maintenance, Environment, Stockholm, Sweden, May 8–11. SPCI. pp. 29–44.
- White, K. and Roberts, C. 1994. Applying SPC data analysis techniques to continuous processes in the pulp and paper industry. In: 1994 Control Systems Preprints, SPCI, Stockholm, pp. 52–59.
- Sheasby, M.A. and Wilson, A. 2012. The use of SPC in the papermaking industry. Total Quality Management: Proceedings of the first world congress (ed. by G. Kanji). Springer Science & Business Media, 618 p.
- Ramos, A.W. 2006. Statistical process control on the paper machine. Tappsa, July 2006.
- Ramesh, S. and Vasu, B.A. 2019. Application of EWMA chart for monitoring process mean in paper industry. Management Science Letters 9:571–576.
- Rantamäki, J., Tiainen, E. and Kässi, T. 2013. A case of implementing SPC in a pulp mill. International Journal of Lean Six Sigma 4(3):321–337.
- Corbi, J.-C., Nay, M. J., and Belt, P. B. 1986. Statistical quality control in the bleach plant. TAPPI J. 69(2):60–61.
- Whitley, J. C., III 1987. Statistics improve k number control at Federal Paper board pulp mill. Pulp & Paper 61(1):99–102.
- Armstrong, M.K. 1991. Statistical process control of digester permanganate and kappa numbers: closing the loop with SPC. Tappi Journal 74(6):244–248.
- Ho, T. and Henriksson, C.D. 1992. Statistical process control and its application in a chemi-thermomechanical pulp mill. Tappi Journal 75(11):252–254.
- Latva-Käyrä, K. 2001. TMP pulp quality observer. Measurement29(2): 147–156.
- Matos, A., Requeijo, J. and Pereira. Z. (2008) Integration of Engineering Process Control and Statistical Control in pulp and paper industry. Computer Aided Chemical Engineering 25:399–404.
- Siddiqui, Y.A., Saif, A-W.A., Cheded, L., Elshafei, M. and Rahim, A. 2015. Integration of multivariate statistical process control and engineering process control: a novel framework. The International Journal of Advanced Manufacturing Technology 78(1–4):259–268.
- Duffuaa. S.O., Khursheed, S.N. and Noman, S.M. 2004. Integrating statistical process control, engineering process control and Taguchi’s quality engineering. International Journal of Product Research 42(19):4109–4118.
- Shao, Y.E. and Chiu, C-C. 1999. Developing identification techniques with the integrated use of SPC/EPC and neural networks. Quality Reliability Engineering International 15(4):287–294.
- Saif, A.W., Akram, M.A. and Rahim M.A. 2011. A fuzzy integrated SPC/APC scheme for optimised levels of process quality, performance and robustness. International Journal of Experimental Design Process Optimisation 2(2):161–189
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This page has been updated 15.11.2020