Industrial Applications of Soft Computing: Paper, Mineral and Metal Processing Industries PDF
Preview Industrial Applications of Soft Computing: Paper, Mineral and Metal Processing Industries
Industrial Applications of Soft Computing Studies in Fuzziness and Soft Computing Editor-in-chier Prof. Janusz Kacprzyk Systems Research Institute Polish Academy of Sciences ul. Newelska 6 01-447 Warsaw, Poland E-mail: [email protected] = http://www.springer.de/cgi-bin/search_book.pl?series 2941 Further volumes of this series can Vol. 60. K.J. Cios (Ed.) be found at our homepage. Medical Data Mining and Knowledge Discovery. 200} ISBN 3-7908-1340-0 Vol. 49. L.I. Kuncheva F/l'l.ZY Classifier Design, 2000 Vol. 61. D. Driankov and A. Saffiotti (Eds.) ISBN 3-7908-1298-6 Fuzzy Logic Techniques for Autonomous Vehicle Navigation. 200} Vol. 50. F. Crestani and G. Pasi (Eds.) ISBN 3-7908-1341-9 Soft Computing in Information Retrieval. 2000 ISBN 3-7908-1299-4 Vol. 62. N. Baba. L.c. Jain (Eds.) Vol. 51. J. Fodor, B. De Baets and P. Pemy (Eds.) Computational Intelligence in Games. 200} Preferences and Decisions under Incomplete ISBN 3-7908-1348-6 Knowledge. 2000 Vol. 63. O. Castillo. P. Melin ISBN 3-7908-1303-6 Soft Computing for Control of Non-Linear Vol. 52. E.E. Kerre and M. Nachtegael (Eds.) Dynamical Systems. 2001 Fuzzy Techniques in Image Processing. 2000 ISBN 3-7908-1349-4 ISBN 3-7908-1304-4 Vol. 64. I. Nishizaki. M. Sakawa Vol. 53. G. Bordogna and G. Pasi (Eds.) F/l'l.ZY and Multiobjective Games for Conflict Recent Issues on F/l'l.ZY Databases. 2000 Resolution. 200} ISBN 3-7908-1319-2 ISBN 3-7908-1341-9 Vol. 54. P. Sincak and 1. Vascak (Eds.) Vol. 65. E. OrIowska, A. Szalas (Eds.) Quo Vadis Computational Intelligence? 2000 Relational Methods for Computer Science ISBN 3-7908-1324-9 Applications. 200} Vol. 55. J.N. Mordeson. D.S. Malik ISBN 3-7908-1365-6 and S.-C. Cheng Vol. 66. R.J. Howlett, L.C. Jain (Eds.) F/l'l.ZY Mathematics in Medicine. 2000 Radial Basis Function Networks 1. 200] ISBN 3-7908-1325-7 ISBN 3-7908-1367-2 Vol. 56. L. Polkowski, S. Tsumoto and T. Y. Lin (Eds.) Vol. 67. R.I. Howlett and L.C. Jain (Eds.) Rough Set Methods and Applications. 2000 Radial Basis Function Networks 2. 200} ISBN 3-7908-1328-1 ISBN 3-7908-1368-0 Vol. 57. V. Novak and I. Pertilieva (Eds.) Discovering the World with Fuzzy Logic. 200} Vol. 68. A. Kandel. M. Last and H. Bunke (Eds.) ISBN 3-7908-1330-3 Data Minining and Computational Intelligence. 200] Vol. 58. D.S. Malik and J.N. Mordeson ISBN 3-7908-1371-0 Fuzzy Discrete Structures. 2000 ISBN 3-7908-1335-4 Vol. 69. A. Piegat Fuzzy Modeling and Control. 200] Vol. 59. T. Furuhashi, S. Tano and H.-A. Jacobsen ISBN 3-7908-1385-0 (Eds.) Deep Fusion of Computational Vol. 70. W. Pedrycz (Ed.) and Symbolic Processing. 200} Granular Computing. 200] ISBN 3-7908-1339-7 ISBN 3-7908-1387-7 Kauko Leiviska Editor Industrial Applications of Soft Computing Paper, Mineral and Metal Processing Industries With 118 Figures and 27 Tables Springer-Verlag Berlin Heidelberg GmbH PPrrooff.. 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HHaarrddccoovveerr DDeessiiggnn:: EErriicchh KKiirrcchhnneerr,, HHeeiiddeellbbeerrgg Preface My first contact with Soft Computing dates back to the end of 1970's. I got a letter from a foreign colleague who asked, if I were interested to study a new control methodology, fuzzy logic control. I had just finished with my Licentiate of Tech nology thesis that had led to the first commercial control system for the lime kiln. I had also started my Doctor of Technology studies and selected production scheduling algorithms for the pulp mill as my topic. So, I had to turn his proposal down. Next contact was about seven years later, 1985. I was working with the lime kiln again. This time, one my students was testing the expert system technology for the consulting application on the lime kiln. The program system we were using had a fuzzy system option, and we made a consulting fuzzy expert system for the lime kiln operation. The system was never installed on the actual kiln. I got my own laboratory to manage in 1990 and we started working with the its strategy. My interest to knowledge-based system and to fuzzy logic and neural networks had grown during years. We had also discussions with companies and financing sources and, together with the interest, we chose Intelligent Methods, how we called them at this time, our strategic growth area. After couple of years, we were working with the lime kiln control again. This time we used fuzzy logic control and the studies led to our first successful indus trial application on this new area. So, it is no wonder that also one of the chapters in this book deals with the use of Soft Computing methods in lime kiln. This book concentrates on the application of Soft Computing methods in Finland. Finland experienced a boom of neural network and fuzzy technologies during 1990's. There were several reasons for this. Finnish companies have been pioneering in many areas of industrial control applications for decades. Especially this agrees with mining and metals and paper industries. Companies have seen the benefits of better control and improved information, and also in this case it was easy to find industrial partners ready for testing the new technology. Also the research policy that the State of Finland was carrying out was positive for new technologies. As a concrete example, the National Technology Agency, Tekes, launched an extensive research and technology development project concerning intelligent and adaptive systems. Its effect for the growth of fuzzy logic and neural network applications in the Finnish industry was a tremendous one. While choosing papers for this book I was in front of multitude of possibilities. I have tried to balance the material at least in two ways. First, I tried to find new VI interesting industrial applications that have not been too reported earlier in the literature. Secondly, I tried to give a chance to as many research groups as possi ble to tell about their research. After four short introductory chapters, applications in mineral and metal proc essing start. The first application tells about fuzzy logic control of the sintering plant. It is a good example, how a commercial software is used controlling a com plicated process. The second example tells about an application Kohonen self organising map to describe the behaviour of wall temperature profiles in the blast furnace. It shows the strength of SQM in visualising complicated process phenomena in giving improved information for operators. The third example tells about the smelt shop control. It is an example, how neural network models are integrated with existing models to a hybrid system with increased performance. It shows the ability of neural networks to cope with huge amounts of data. The fourth example of this topic takes us to mineral processing. It shows the results of a long research line concerning the modelling and control of a rotary dryer for minerals drying using conventional and advanced methods. The fifth, and the final example introduces even more difficult example from minerals processing. It deals with using image processing and an expert system in flotation plant control. Next we turn to the paper industry. These applications start from modelling. The first paper in this sequence deals with the comparison of different fuzzy mod elling methods using continuous pulp cooking as an example. The second example concerns with a conventional fuzzy logic control. It concern with a fuzzy control system for TMP-pulping installed at the Swedish mill. The third example is the "obligatory" lime kiln example. The existing control system combines fuzzy logic control, neural networks and an expert system framework. This system is in operation and the results have been good. The forth example is once again dealing with TMP- pUlping. It shows how fuzzy logic can be combined with Statistical Process Control to develop a flexible system to help operators in process monitoring. Finally comes an example from the paper machine control. It concentrates on paper grade changes that are usually too complicated for manual operation and the risks of production losses are also high in automatic changes. As the Editor of this book, I have many thanks to give. I thank the Series Editor for the possibility to write this book and good advises along the way. I thank my writer colleagues for good co-operation and patience, because the road was long. I thank my wife, Eija and my daughter, Minja, for just being there. This effort took a lot of our time together. Especially, I thank my son, Marko, for collecting the background material for the Chapter "Applications in Paper Industries". It was a good work. Qulu, November 20, 2000 Kauko Leiviska Contents v Preface Part I: Introduction Basics of Soft Computing Methods 3 K. Leiviskii Soft Computing Applications in Mineral and Metal Industries 23 K. Leiviskii Soft Computing Applications in Pulp and Paper Industries 35 K. Leiviskii Enhancing Maintainability of Knowledge-Based Soft Computing Systems 47 T. Rauma Part II: Mineral and Metal Industries Fuzzy Logic Control of a Sintering Plant 65 P. Myllymliki, 1. Poutiainen Pattern Recognition for Blast Furnace Temperature Classification 79 H. Saxen, L. Lassus Temperature Control of a Smelting Plant 93 T. Palovaara, M. Sipola Adaptive Fuzzy Control of a Rotary Dryer 109 L. Yliniemi Soft Computing at a Flotation Plant 133 H. Hyotyniemi, R. Ylinen, 1. Miettunen VIII Part III: Paper Industries Intelligent Modelling of Continuous Pulp Cooking 147 K. Leiviskii, E. Juuso, A.Isokangas Fuzzy Quality Control of a TMP Plant 159 J. Myllyneva, L. Karlsson, l. Joensuu Intelligent Supervisory Control of an Industrial Rotary Kiln 175 E. Juuso, M. Jiirvensivu, O. Ahava Fuzzy Logic and SPC 197 K. Latva-Kiiyrii Estimation of Target Values for Grade Changes in Paper Machine 211 P. Viljamaa, H. Peltonen, H. Koivo Index 223 List of Contributors 225 Part I Introduction
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