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Projects / Programmes source: ARIS

Synergetics of complex systems and processes

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Periods
January 1, 2020 - December 31, 2027
Research activity

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

Code Science Field
T000  Technological sciences   

Code Science Field
1.03  Natural Sciences  Physical sciences 
2.03  Engineering and Technology  Mechanical engineering 
Keywords
Synergetics, complexity, modelling, clustering, diagnostics, optimization, forecasting, predictive control, adaptive systems, laser material processing, laser direct metal deposition, 3D metal print, ensembles, neural networks, information-theoretical measures, parallel architectures
Evaluation (rules)
source: COBISS
Evaluation of bibliographic research performance indicators according to ARIS methodology
Points
1,880.3
A''
249.5
A'
591.66
A1/2
1,191.92
CI10
2,705
CImax
286
h10
27
A1
6.39
A3
3.82
Data for the last 5 years (citations for the last 10 years) on June 28, 2024; A3 for period 2018-2022
Data for ARIS tenders ( 04.04.2019 – Programme tender , archive )
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Database Linked records Citations Pure citations Average pure citations
WoS  219  3,190  2,887  13.18 
Scopus  282  4,267  3,875  13.74 
Researchers (17)
no. Code Name and surname Research area Role Period No. of publications
1.  55740  Ahmed A.F. Al-Tameemi  Technology driven physics  Junior researcher  2022  0 
2.  02272  PhD Andrej Dobnikar  Computer science and informatics  Retired researcher  2020 - 2024  0 
3.  08782  PhD Edvard Govekar  Manufacturing technologies and systems  Head  2020 - 2024  0 
4.  00800  PhD Igor Grabec  Computer science and informatics  Retired researcher  2020 - 2024  8 
5.  31379  PhD Nejc Ilc  Computer science and informatics  Researcher  2020 - 2024  0 
6.  54971  Slobodanka Ivanjić Kostrešević    Technical associate  2023 - 2024  0 
7.  20270  PhD Andrej Jeromen  Computer science and informatics  Researcher  2020 - 2024  0 
8.  29800  Jernej Korinšek    Technical associate  2022 - 2023  0 
9.  38155  PhD Matjaž Kotar  Technology driven physics  Junior researcher  2020  0 
10.  16109  PhD Uroš Lotrič  Computer science and informatics  Researcher  2020 - 2024  0 
11.  53508  Jaka Peternel  Technology driven physics  Junior researcher  2020 - 2024  0 
12.  53795  Tanja Plestenjak    Technical associate  2022 - 2024  0 
13.  15107  PhD Primož Potočnik  Computer science and informatics  Researcher  2020 - 2024  0 
14.  54772  Jaka Simončič  Technology driven physics  Junior researcher  2020 - 2024  0 
15.  33385  PhD Davor Sluga  Computer science and informatics  Researcher  2020 - 2024  0 
16.  14300  PhD Branko Šter  Computer science and informatics  Researcher  2020 - 2024  0 
17.  50588  Ana Vidergar  Technology driven physics  Junior researcher  2020 - 2021  0 
Organisations (2)
no. Code Research organisation City Registration number No. of publications
1.  0782  University of Ljubljana, Faculty of Mechanical Engineering  Ljubljana  1627031  0 
2.  1539  University of Ljubljana, Faculty of Computer and Information Science  Ljubljana  1627023  0 
Abstract
The optimization of existing, as well as the development of new, technologies and processes with complex and time-varying properties requires an understanding of the mutual nonlinear interactions that can often lead to instabilities and even chaos. The consideration of such processes is the subject of a number of intensive scientific investigations, in which we are involved within the framework of the research program 'Synergetics of complex systems and processes'.   The basic goals of the research program are to contribute to global science by describing and understanding complex dynamic systems and processes using synergetic methods. A synergetic treatment is based on the use of advanced methods of probability and statistics, information theory, chaotic dynamics, soft computing, data mining, adaptive empirical modelling, machine learning, optimization methods and predictive guidance (see attachment Fig. 1). Synergetic methods have proved to be an extremely useful and scientifically correct approach to describing complex systems and processes. Therefore, basic research is focused on the further development and use of synergetic methods for characterizing and modelling, optimizing, forecasting and the predictive control of complex systems and processes. We will also improve and implement methods for cluster analysis with ensembles in an open-source package. We will utilize information-theoretic measures to select relevant features from the data and use Bayesian statistics to model the complex systems.   The findings of synergetic treatments are used to improve existing and develop new technological processes, and to develop information and adaptive systems for automatic monitoring, characterizing, diagnosing, optimizing and control of complex technological systems, processes, loaded materials and products. Recently, we have focused on researching the interaction of the laser beam with the substance and the associated laser processing of materials, with an emphasis on the research and development of the system and process for the laser direct deposition of metal materials for the purposes of 3D metal printing and cladding.   Additionally, research of forecasting capabilities with the goal of developing predictive models and predictive control of complex systems and processes with emphasis on district heating systems, modern smart buildings and various production and manufacturing systems and processes are of paramount importance. Accordingly, intensive research is also the subject of modern methods of pattern recognition, neural networks and deep learning for industrial diagnostics and recognising the state of various industrial processes, as well as predictive maintenance in order to improve the quality of production processes and manufactured products.
Significance for science
The main focus of the research is the development and application of synergetic methods in order to describe complex technological processes, with the aim of contributing to the understanding and description of the physical properties, the dynamics and the causes of complexity of technological processes. The proposed research programme makes a significant contribution to the further establishment of synergetic methods as a successful scientific approach, thus bringing together the fields of physics, probability and statistics, informatics and technical sciences in terms of the theoretical and experimental treatment of complex systems and processes. The latter is in addition to the understanding of the physical properties, in the modelling of dynamic processes, and in the understanding of the causes of complexity of technological processes, of paramount importance for the research ad development of new, advanced technological systems and processes. Thus, an active contribution is made to the advancement of science with respect to the description, characterisation and modelling of the dynamics of complex technological processes. The importance of the synergetic approach to the description of complex technological systems and processes is confirmed by the large number of citations for the programme leader and the programme research group in international scientific journals. Within the context of the proposed research, topics that are presently related to the instability of manufacturing processes are considered, with focus on cutting processes and laser material processing. In the field of laser material processing, special attention is focused on research into applications of an annular laser beam for advanced material processing with focus on circular joints, generation and deposition of metal droplets, and laser direct deposition of metals. The expected results are of great importance for understanding of annular laser beam metal interactions as well as for laser material processing and manufacturing technologies including new technologies of droplet and annular micro joining, and 3D metal printing and cladding. In the field of the research and development of predictive methods for the analysis and prediction of time series and fields, a contribution will be made to the development of specific methods for given application domains (various energy, business, transport systems, etc.), thereby contributing to the development of science, both in terms of the basic development of methods, as well as in the terms of the application of the developed methods and models to the target domain areas. Particular attention is focused on the synergetic treatment of various methods (neural networks, support vector machines, extreme learning machines, the aggregation of predictors, adaptive forecasting, forecasting with computational intelligence, hierarchical forecasting, etc.) by combining and connecting them together into uniform functional predictive systems for forecasting the states of complex systems and processes. Within the context of the research and development of methods for multi-sensory data processing and intelligent adaptronic systems for monitoring, modelling, optimizing and controlling complex processes, and of the methods for the non-destructive testing and characterizing of loaded materials and products, a contribution will be made to the development of science in the field of advanced signal-processing methods, for use in the diagnostics for industrial processes and products based on neural networks and modern learning systems. The selection of relevant features in the data based on generalized information-theoretical measures is, due to the promising results obtained, increasingly popular, especially in the case of large data sets. Additionally, data clustering based on ensembles is one of the most interesting current approaches in machine learning. Due to the high level of interest in all areas of data analysi
Significance for the country
Direct importance of the program for the economy and social activities The research programme involves the improvement and optimization of existing technologies and methods, as well as the development of new such approaches, with the possibility of direct implementation in a variety of industries. This was recently confirmed by extensive collaboration with industrial partners. The results of the research, which involves the development of methods for the analysis and prediction of time series and fields, the development of multi-sensory data-processing methods and intelligent adaptronic systems for monitoring, modelling, optimizing and controlling complex processes, and methods for the non-destructive testing and characterizing of loaded materials and products, is directly aimed at the monitoring and improving of the quality of products, technological and industrial processes. Our investigations and applications of forecasting methods in the development of systems for the prediction and optimization of states of complex energetic, traffic and business systems, which are essential for the consistent and sustainable development of society, need to be emphasized. On the basis of previous successful results for the implementation of developed predictive methods into industrial and business environments, we plan to expand into new areas of application (e.g., the introduction and integration of forecasting models into district heating systems and the introduction of predictive methods in the field of smart buildings). In this way we contribute to the success and competitiveness of enterprises in complex modern business conditions. Research into synergetics, which includes research into the instability of technological processes and the development of new methods for annular laser material processing, including technology for the generation and deposition of metal droplets, is potentially applicable in the implementation of complex lead-free micro-joints, fulfilling the demanding temperature, corrosion, mechanical and environmental requirements. The research and development of annular-laser- and droplet-based micro-joining technologies and 3D structuring represents a significant development potential for the electrical and electronics industries, and the aircraft and aerospace industry, as well as for companies that produce functionally demanding components. Using these skills, it will be possible to introduce into the domestic and international industrial environments new, scientifically based methods for the treatment and improvement of technological processes and products, thus contributing to the international competitiveness of Slovenian and European industry. Indirect importance to society Through participation in international scientific meetings and the publication of scientific papers in high-quality international journals, Slovenian science, and the visibility of Slovenia within the international arena, will be promoted. By recruiting and training young researchers from other countries, as well as through the scientific exchange of researchers, we are involved in the international division of labour. All the contents of the research programme are regularly included in the courses of levels I, II and III of the Bologna process, so that we contribute to the education and transfer of those learning materials, which are needed to be able to understand and solve complex industrial problems. Scientific knowledge arising from the operation of the programme group is integral to the courses on Chaotic Dynamics, Neural Networks and the Empirical Modelling and Characterization of Processes, as well as within the context of international programs for the level II degrees EUREHO and TRIBOS. Importance for the development of the profession and engineering practice The results of the research contribute to the practical aspects of the application of knowledge in the field of the treatment of complex systems and processes, as
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