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Authors: Marco Vannocci 1 ; Valentina Colla 1 ; Piero Pulito 2 ; Michele Zagaria 2 ; Vincenzo Di Mastromatteo 2 and Marco Saccone 2

Affiliations: 1 Scuola Superiore Sant’Anna, Italy ; 2 ILVA S.p.A., Italy

Keyword(s): Fuzzy Control, Expert Systems, Sinter Plant.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer-Supported Education ; Domain Applications and Case Studies ; Fuzzy Control ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial, Financial and Medical Applications ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: Within an integrated steelwork, the industrial priorities in the automation of the sinter plant comprise stable production rate at the highest productivity level and classical control scheme may fail due to the complexity of the sinter process. The paper describes an approach exploiting a fuzzy rule-based expert system to control the charging gates of a sinter plant. Two different control strategies are presented and discussed within an innovative advisory system that supports the plant operators in the choice of the most promising action to do on each gate. Through the proposed approach the operators are supported by the system in the control of the plant: through a suitable exploitation of real-time data, the system suggests the most promising action to do, by reproducing the knowledge of the most expert operators. Thus, this approach can also be used to train new technicians before involving them in the actual plant operations. The performance of the strategies and the goodness of the system have been evaluated for long time in the sinter plant of one of the biggest integrated steelworks in Europe, namely the ILVA Taranto Works in Italy. (More)

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Paper citation in several formats:
Vannocci, M.; Colla, V.; Pulito, P.; Zagaria, M.; Di Mastromatteo, V. and Saccone, M. (2014). Fuzzy Control of a Sintering Plant. In Proceedings of the International Conference on Fuzzy Computation Theory and Applications (IJCCI 2014) - FCTA; ISBN 978-989-758-053-6, SciTePress, pages 68-75. DOI: 10.5220/0005082400680075

@conference{fcta14,
author={Marco Vannocci. and Valentina Colla. and Piero Pulito. and Michele Zagaria. and Vincenzo {Di Mastromatteo}. and Marco Saccone.},
title={Fuzzy Control of a Sintering Plant},
booktitle={Proceedings of the International Conference on Fuzzy Computation Theory and Applications (IJCCI 2014) - FCTA},
year={2014},
pages={68-75},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005082400680075},
isbn={978-989-758-053-6},
}

TY - CONF

JO - Proceedings of the International Conference on Fuzzy Computation Theory and Applications (IJCCI 2014) - FCTA
TI - Fuzzy Control of a Sintering Plant
SN - 978-989-758-053-6
AU - Vannocci, M.
AU - Colla, V.
AU - Pulito, P.
AU - Zagaria, M.
AU - Di Mastromatteo, V.
AU - Saccone, M.
PY - 2014
SP - 68
EP - 75
DO - 10.5220/0005082400680075
PB - SciTePress