| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

Search the digital library catalog Help

Query: search in
search in
search in
search in
* old and bologna study programme

Options:
  Reset


1 - 6 / 6
First pagePrevious page1Next pageLast page
1.
Design of row-based flexible manufacturing system with evolutionary computation
Mirko Ficko, Jože Balič, 2008, published scientific conference contribution

Abstract: This paper discusses design of flexible manufacturing systems (FMSs) in one or multiple rows. Evolutionary computation, particularly genetic algorithms (GAs) proved to be successful in search of optimal solution for this type of problems. The model of solution, the most suitable way of coding the solutions into the organisms and the selected evolutionary and genetic operators are presented. In this connection, the most favourable number of rows and the sequence of devices in the individual row are established by means of genetic algorithms (GAs). In the end the test results of the application made and the analysis are discussed.
Keywords: flexible manufacturing system design, genetic algorithms, evolutionary computation, intelligent manufacturing systems, artificial intelligence
Published: 31.05.2012; Views: 1137; Downloads: 62
URL Link to full text

2.
3.
Encyclopedia of complexity and systems science
dictionary, encyclopaedia, lexicon, manual, atlas, map

Abstract: Encyclopedia of Complexity and Systems Science provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering. The science and tools of complexity and systems science include theories of self-organization, complex systems, synergetics, dynamical systems, turbulence, catastrophes, instabilities, nonlinearity, stochastic processes, chaos, neural networks, cellular automata, adaptive systems, and genetic algorithms. Examples of near-term problems and major unknowns that can be approached through complexity and systems science include: The structure, history and future of the universe; the biological basis of consciousness; the integration of genomics, proteomics and bioinformatics as systems biology; human longevity limits; the limits of computing; sustainability of life on earth; predictability, dynamics and extent of earthquakes, hurricanes, tsunamis, and other natural disasters; the dynamics of turbulent flows; lasers or fluids in physics, microprocessor design; macromolecular assembly in chemistry and biophysics; brain functions in cognitive neuroscience; climate change; ecosystem management; traffic management; and business cycles. All these seemingly quite different kinds of structure formation have a number of important features and underlying structures in common. These deep structural similarities can be exploited to transfer analytical methods and understanding from one field to another. This unique work will extend the influence of complexity and system science to a much wider audience than has been possible to date.
Keywords: cellular automata, complex networks, computational nanoscience, ecological complexity, ergodic theory, fractals, game theory, granular computing, graph theory, intelligent systems, perturbation theory, quantum information science, system dynamics, traffic management, chaos, climate modelling, complex systems, dynamical sistems, fuzzy theory systems, nonlinear systems, soft computing, stochastic processes, synergetics, self-organization, systems biology, systems science
Published: 01.06.2012; Views: 1514; Downloads: 74
URL Link to full text

4.
Automated and intelligent programming of cnc machine tools
Afrim Gjelaj, 2014, doctoral dissertation

Abstract: Nowadays, many scientists focus on increasing the level of automation, respectively flexibility in manufacturing systems. In addition, automated programming of CNC machine tools has reached a high level of machining operations. However, it is still impossible for a machine to manipulate completely in an autonomous way. Special attention in this doctoral thesis is focused on the automated programming of CNC machine tools regarding artificial intelligence. The purpose of automated programming is to improve quality and to fulfil the requirements of manufacturing industry and provide commercial solutions. This thesis also provides a description of artificial intelligence usage in order to solve optimal tool path-length and tool selection, as well as the preparation of planned technology. Firstly, the automated programming of CNC machine tools enjoys great success when applying artificial intelligence in regard to the machining processes. Choices of path length and tool selection are analysed in great detail in order to ascertain the optimal problems of tool path- length and tool selection. However, in order to achieve automated and intelligent CNC programming of machine tools, their flexibilities are of major importance. Automation today tends to improve and implement manufacturing flexibility at a strategic level. This means increasing the degree of flexibility whilst at the same time increasing the degree of automation regarding CNC machine tools. In addition to the above-mentioned investigated problems, the influences of cutting force (Fc), power cutting (Pc), tool life (T) and surface roughness (Ra) as functions of tool path- length are also analysed. Analytical and mathematical models are optimised using a multi-objective genetic algorithm (MOGA). MOGA enables optimisation by employing two or more equations simultaneously. Another problem for the automated and intelligent CNC programming of machine tools focuses on the application of Discrete Systems (DS). The discrete system in our work focuses on analysing cutting force (Fc) in regard to the turning operation.
Keywords: inteligent CNC programming, intelligent manufacturing, discrete system, automated programming, multiobjective genetic algorithm MOGA
Published: 23.01.2015; Views: 1752; Downloads: 303
.pdf Full text (1,57 MB)

5.
Prediction of technological parameters of sheet metal bending in two stages using feed-forward neural network
Jernej Šenveter, Jože Balič, Mirko Ficko, Simon Klančnik, 2016, original scientific article

Abstract: This paper describes sheet metal bending in two stages as well as predicting and testing of the final bend angle by means of a feed-forward neural network. The primary objective was to research the technological parameters of bending sheet metal in two stages and to develop an intelligent method that would enable the predicting of those technological parameters. The process of bending sheet metal in two stages is presented by demonstrating the various technological parameters and the test tool used to carry out tests and measurements. The results of the tests and measurements were of decisive guidance in the evaluation of individual technological parameters. Developed method for prediction of the final bend angle is based on a feed-forward neural network that receives signals at the input level. These signals then travel through the hidden level to the output level, where the responses to input signals are received. The input to the neural network is composed of data that affect the selection of the final bend angle. Only five different inputs are used for the total neural network. By choosing the desired final bend angle by means of the trained neural network, bending sheet metal in two stages is optimised and made more efficient.
Keywords: bending in two stages, intelligent system, neural network, prediction of the final bend angle
Published: 12.07.2017; Views: 324; Downloads: 210
.pdf Full text (900,30 KB)
This document has many files! More...

6.
Modular and branched structure of individualized intelligent e-learning materials for science and technology subject course
Kosta Dolenc, Igor Pesek, Boris Aberšek, 2013, original scientific article

Abstract: E-learning and online education offers important opportunities for educators as well as for students. Traditional e-materials, as they are known today, do not allow the recognition of different parameters, such as: learning differences, prior knowledge, learning capabilities, learning environment, styles of learning, etc. Because e-materials are structured in such a way they cannot be successfully adapted for learners who consequently cannot control their own learning (Berge, 2002; Picciano, 2000; Saba, 2002). Such a result offers, among others, a highly anti-motivational effect. The preparation of modern e-materials therefore requires a thorough preparation in terms of content and design, which has to be (mostly) based on pedagogical and didactic theories. Modern e-materials, which can also be named educational e-materials, are usually accessible online (internet-based training (IBT), web-based training (WBT), online education, etc.), they enable and encourage self-learning, they are flexible, dynamic, interactive, use different types of media, individualized and adapted to the users needs. Mostly the latter characteristic will receive special attention in the following research.
Keywords: education, individualized e-learning, intelligent system, metadata
Published: 15.12.2017; Views: 388; Downloads: 32
.pdf Full text (1,31 MB)
This document has many files! More...

Search done in 0.12 sec.
Back to top
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica