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Projects / Programmes source: ARIS

Synergetics of technological systems and processes

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Periods
January 1, 2004 - December 31, 2008
Research activity

Code Science Field Subfield
2.21.00  Engineering sciences and technologies  Technology driven physics   

Code Science Field
T000  Technological sciences   
Keywords
technological systems and processes, stability, non-linearty, chaotic dynamics, time series analysis, non-destructive testing, acoustic emission, neural networks, intelligent systems, modeling, monitoring, diagnostics, prediction, optimization, control
Evaluation (rules)
source: COBISS
Evaluation of bibliographic research performance indicators according to ARIS methodology
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Researchers (13)
no. Code Name and surname Research area Role Period No. of publications
1.  26554  MSc Jure Bezgovšek  Technology driven physics  Junior researcher  2006 - 2008  6 
2.  15839  PhD Anamarija Borštnik Bračič  Mathematics  Researcher  2008  53 
3.  08782  PhD Edvard Govekar  Manufacturing technologies and systems  Head  2004 - 2008  435 
4.  00800  PhD Igor Grabec  Computer science and informatics  Researcher  2004 - 2008  697 
5.  18081  PhD Janez Gradišek  Mechanical design  Researcher  2004 - 2008  92 
6.  20270  PhD Andrej Jeromen  Computer science and informatics  Researcher  2005 - 2008  78 
7.  21231  PhD Jure Klemenčič  Computer science and informatics  Junior researcher  2004 - 2005  17 
8.  22454  PhD Tadej Kokalj  Interdisciplinary research  Junior researcher  2004 - 2006  76 
9.  11438  PhD Miran Kokol  Computer science and informatics  Researcher  2004  16 
10.  09002  Peter Mužič  Manufacturing technologies and systems  Technical associate  2004 - 2008  95 
11.  15107  PhD Primož Potočnik  Computer science and informatics  Researcher  2004 - 2008  184 
12.  24244  PhD Robert Rozman  Energy engineering  Junior researcher  2005 - 2008  34 
13.  10425  PhD Egon Susič  Computer science and informatics  Researcher  2004  44 
Organisations (1)
no. Code Research organisation City Registration number No. of publications
1.  0782  University of Ljubljana, Faculty of Mechanical Engineering  Ljubljana  1627031  30,047 
Abstract
Technological systems and processes form the basis of manufacturing industry. Description and optimization of these systems and processes are therefore among the fundamental scientific tasks of engineering sciences. Most technological systems and processes exhibit unstable, nonlinear and stochastic behaviour that is difficult to describe using standard physical and engineering methods. Consequently, the synergetic description is increasingly being used for this purpose. The synergetic description combines methods from probability and statistics, chaotic dynamics and learning theory of intelligent systems. The basic goal of our investigations is to contribute to the understanding of physical properties of technological systems and to develop effective methods for automatic real-time monitoring, diagnostics and surveillance as well as modeling, prediction, optimization and control of state and operation of technological systems and processes, loaded constructions and materials, and operating machines and applicances. For this purpose, the research programme activities include basic research of dynamic phenomena in complex technological systems and processes, development of novel and adaptation of existing data analysis methods, and development of adaptive intelligent systems.
Significance for science
The research contributes to a closer connection of physics, probability and statistics, informatics and technical sciences from the point of view of theoretical and experimental treatment of complex systems and processes. Thereby, we contribute to the understanding of physical properties and causes of complexity of technological processes that are a consequence of nonlinear dynamic interaction of various process variables. Theoretical research contributes to the development of novel methods and techniques for automatic monitoring of process states, adaptive modelling, identification, control and optimisation of complex processes based on multi-sensor data. The fundamental research goal is to develop and adapt existing general methods for adaptive modelling and optimisation of properties of complex technological processes, based on experimental data, in order to establish model-predictive control of the process. Such an approach requires development of methods for optimal information processing, development of learning systems for automated statistical modelling of physical laws (adaptive and/or soft systems), and development and application of nonlinear optimisation methods. This field of research is currently attracting interest in the area of scientific treatment of technological systems and processes also from the complexity point of view, and is worldwide the subject of intense research. We actively co-operate with and attend to the progress in the field of the dynamics of complex technological processes and in the field of development of adaptive intelligent systems for automatic monitoring, control and optimisation of complex technological systems and processes.
Significance for the country
Our research is directed into development of methods for automated monitoring, diagnostics, forecasting and identification, optimisation and control of complex technological systems and processes, which is a basis for improvement of quality and development of new products and processes in various industrial branches. The core of our research is focused on complex processes caused by either the chaotic properties of processes, the nonlinear and unstable interaction of several dominant process components, or due to nonlinear interaction of many components and process parameters. We aim to introduce into the domestic industrial environment novel scientifically based methods of treatment and improvement of technological processes, and into undergraduate and postgraduate study programmes novel learning contents that are essential for understanding and solving complex industrial problems. Results of our research contribute to practical applications of knowledge in the field of treatment of complex systems and processes, and to knowledge transfer in the field of engineering science and technology. Various branches of Slovenian industry are interested in results about research of the synergetics of complex technological processes and systems. Knowledge, acquired through methods of synergetics in co-operation with industry, is included in the development of adaptronic systems for automatic condition monitoring of production processes, development of systems for predictive control and process optimisation, and optimisation of existing (and development of novel) technologies, processes and manufacturing procedures. We aim to introduce into industrial environment new technological methods for improved quality of machining processes and products, and also contribute toward the international competitiveness of companies.
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