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1.
Yield strength modelling of formed material using evolutionary computational method
Leo Gusel, Rebeka Rudolf, 2009, original scientific article

Abstract: In this paper we propose an evolutionary computation approach for the modelling of yield strength in formed material. One of the most general evolutionary computation methods is genetic programming, which was used in our research. Genetic programming is an automated method for creating a working computer program from a problemćs high-level statement. Genetic programming does this by genetically breeding a population of computer programs using the principles of Darwinianćs natural selection and biologically inspired operations. During our research, material was cold formed by drawing using different process parameters and then determining yield strengths (dependent variable) of the specimens. On the basis of a training data set, various different genetic models for yield strength distribution were developed during simulated evolution. The accuracies of the best models were proved by a testing data set and comparing between the genetic and regression models. The research showed that very accurate genetic models can be developed by the proposed approach.
Keywords: metal forming, yield strength, genetic programming, modelling
Published: 31.05.2012; Views: 1396; Downloads: 24
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Modeling of impact toughness of cold formed material by genetic programming
Leo Gusel, Miran Brezočnik, 2006, original scientific article

Abstract: In the paper, an approach completely different from the conventional methods for determination of accurate models for the change of properties of cold formed material, is presented. This approach is genetic programming (GP) method which is based on imitation of natural evolution of living organisms. The main characteristic of GP is its non-deterministic way of computing. No assumptions about the form and size of expressions were made in advance, but they were left to the self organization and intelligence of evolutionary process. First, copper alloy rods were cold drawn under different conditions and then impact toughness of cold drawn specimens was determined by Charpy tests. The values of independent variables (effective strain, coefficient of friction) influence the value of the dependent variable, impact toughness. On the basis of training data, different prediction models for impact toughness were developed by GP. Only the best models, gained by genetic programming were presented in the paper. Accuracy of the best models was proved with the testing data set. The comparison between deviation of genetic model results and regression model results concerning the experimental results has showed that genetic models are more precise and more varied then regression models.
Keywords: metal forming, genetic programming, evolutionary computing, impact toughness, copper alloy, modelling
Published: 30.05.2012; Views: 1450; Downloads: 75
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4.
Study of crosslinking efficiency of cotton cellulose by different physical-chemical methods and genetic programming
Olivera Šauperl, Miran Brezočnik, 2006, original scientific article

Abstract: We have investigated the crosslinking effect of unmercerized and mercerized cotton celluose crosslinked with different BTCA mass fractions in the impregnation bath. Crosslinking efficiency was analyzed using FT-IR spectroscopy, water retention capacity method, tensiometry and the methylene blue method. On the basis of the experimental data which was obtained with theseparate physical-chemical methods, different prediction models for crosslinking efficiency was developed. Modelling was taken out with the genetic programming method. Research shows good accordance of the experimentaldata with the genetic models.
Keywords: textile fibres, cotton, cellulose, crosslinking, FTIR spectroscopy, methylene blue method, water retention capacity, tensiometry, genetic programming
Published: 30.05.2012; Views: 1358; Downloads: 44
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5.
Intelligent programming of CNC turning operations using genetic algorithm
Jože Balič, Miha Kovačič, Boštjan Vaupotič, 2006, original scientific article

Abstract: CAD/CAM systems are nowadays tightly connected to ensure that CAD data can be used for optimal tool path determination and generation of CNC programs for machine tools. The aim of our research is the design of a computer-aided, intelligent and genetic algorithm(GA) based programming system for CNC cutting tools selection, tool sequences planning and optimisation of cutting conditions. The first step is geometrical feature recognition and classification. On the basis of recognised features the module for GA-based determination of technological data determine cutting tools, cutting parameters (according to work piece material and cutting tool material) and detailed tool sequence planning. Material, which will be removed, is split into several cuts, each consisting of a number of basic tool movements. In thenext step, GA operations such as reproduction, crossover and mutation are applied. The process of GA-based optimisation runs in cycles in which new generations of individuals are created with increased average fitness of a population. During the evaluation of calculated results (generated NC programmes) several rules and constraints like rapid and cutting tool movement, collision, clamping and minimum machining time, which represent the fitness function, were taken into account. A case study was made for the turning operation of a rotational part. The results show that the GA-based programming has a higher efficiency. The total machining time was reduced by 16%. The demand for a high skilled worker on CAD/CAM systems and CNC machine tools was also reduced.
Keywords: CNC programming, genetic algorithm, intelligent CAM, turning, tool path generation
Published: 30.05.2012; Views: 1439; Downloads: 67
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6.
Prediction of the ultraviolet protection of cotton woven fabrics dyed with reactive dystuffs
Polona Dobnik-Dubrovski, Miran Brezočnik, 2009, original scientific article

Abstract: Textile materials provide a simple and convenient protection against UV radiation. To assign the degree of UV radiation protection of textile materials, the Ultraviolet Protection Factor (UPF) is commonly used. This paper reports the effect of woven fabric construction (yarn fineness, type of weave, relative fabric density), the colour of bi-functional reactive dyestuffs, and Cibacron dyed fabrics on the ultraviolet protection of light summer woven fabrics. A predictive model, determined by genetic programming, was derived to describe the influence of fabric construction. Warp and weft densities, weave factor and CIELab colour components were taken into account by developing the prediction model for UPF. The results show very good agreement between the experimental and predicted values.
Keywords: ultraviolet protection factor, woven fabric construction, colour, prediction model, genetic programming
Published: 31.05.2012; Views: 1179; Downloads: 33
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7.
Prediction of total manufacturing costs for stamping tool on the basis of CAD-model of finished product
Mirko Ficko, Igor Drstvenšek, Miran Brezočnik, Jože Balič, Boštjan Vaupotič, 2005, original scientific article

Abstract: One of the orientations of the tool-making industry is towards shortening the time from enquiry to the supply of tools. The tool-making shops must prepare within the shortest possible time an offer for the manufacturer of the tool based on the enquiry in the form of the CAD-model of the final product. For preparation of a proper offer, the values of certain technological features occurring in the manufacture of the tool are needed. Most frequently the tool manufacturer is interested in total cost for manufacture of the tool. Because of lack of time for making a detailed analysis the total costs of tool manufacture are predicted by the expert on the basis of the experience gathered during several years of work in this area. In our work, we conceived an intelligent system for predicting of total cost of the tool manufacture. We limited ourselves to tools for manufacture of sheet metal products by stamping; the system is based on the concept of case-based reasoning. On the basis of target and source cases, the system prepares the prediction of costs.The target case is the CAD-model in whose costs we are interested, whereas the source cases are the CAD-model of products, for which the tools had already been made, and the relevant total costs are known. The system first abstracts from CAD-models the geometrical features, and then it calculates the similarities between the source cases and target case. Then the most similar cases are used for preparation of prediction by genetic programming method. The genetic programming method provides the model connecting the individual geometrical features with total costs searched for. In the experimental work, we made a system adapted for predicting of tool costs used for tool manufacture on the basis of a theoretic model. The results show that the quality of predictions made by the intelligent system is comparable to the quality assured by the experienced expert.
Keywords: intelligent systems, prediction of costs, tool-making, stamping, CAD model, costs, genetic programming
Published: 01.06.2012; Views: 1181; Downloads: 63
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8.
Prediction of maintenance of sinus rhythm after electrical cardioversion of atrial fibrillation by non-deterministic modelling
Petra Žohar, Miha Kovačič, Miran Brezočnik, Matej Podbregar, 2005, original scientific article

Abstract: Atrial fibrillation (AF) is the most common rhythm disorder. Because of the high recurrence rate of AF after cardioversion and because of potential side effects of electrical cardioversion, it is clinically important to predict persistence of sinus rhythm after electrical cardioversion before it is attempted. The aim of our study was the development of a mathematical model by"genetic" programming (GP), a non-deterministic modelling technique, which would predict maintenance of sinus rhythm after electrical cardioversion of persistent AF. PATIENTS AND METHODS: Ninety-seven patients with persistent AF lasting more than 48 h, undergoing the first attempt at transthoracic cardioversion were included in this prospective study. Persistence of AF before the cardioversion attempt, amiodarone treatment, left atrial dimension,mean, standard deviation and approximate entropy of ECG R-R intervals were collected. The data of 53 patients were randomly selected from the database and used for GP modelling; the other 44 data sets were used for model testing. RESULTS: In 23 patients sinus rhythm persisted at 3 months. In the other 21 patients sinus rhythm was not achieved or its duration was less than 3 months. The model developed by GP failed to predict maintenance ofsinus rhythm at 3 months in one patient and in six patients falsely predicted maintenance of sinus rhythm. Positive and negative likelihood ratiosof the model for testing data were 4.32 and 0.05, respectively. Using this model 15 of 21 (71.4%) cardioversions not resulting in sinus rhythm at 3 months would have been avoided, whereas 22 of 23 (95.6%) cardioversions resulting in sinus rhythm at 3 months would have been administered. CONCLUSION: This model developed by GP, including clinical data, ECG data from the time-domain and nonlinear dynamics can predict maintenance of sinus rhythm. Further research is needed to explore its utility in the present or anexpanded form.
Keywords: optimisation methods, evolutionary optimisation methods, genetic algorithms, genetic programming, defibrillation, cardiac arrest prediction, atrial fibrillation, electrical cardioversion, prediction
Published: 01.06.2012; Views: 1327; Downloads: 50
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9.
Evolutionary programming of CNC machines
Miha Kovačič, Miran Brezočnik, Ivo Pahole, Jože Balič, Borut Kecelj, 2005, original scientific article

Abstract: The paper proposes a new concept for programming of CNC machines. The concept based on genetic algorithms assures evolutionary generation and optimization of NC programs on the basis of CAD models of manufacturing environment. The structure, undergoing simulated evolution, is the population of NC programs. The NC programs control the machine which performs simple elementary motions. During the evolution the machine movement becomes more and more complex and intelligent solutions emerge gradually as a result of the interaction between machine movements and manufacturing environment. The examples of evolutionary programming of CNC lathe and CNC milling machine tool for different complexities of the blanks and products are presented. The proposed concept showed a high degree of universality, efficiency, and reliability and it can be also simply adopted to other CNC machines.
Keywords: manufacturing systems, NC-programming, CNC lathes, simulated evolution, genetic algorithms
Published: 01.06.2012; Views: 1012; Downloads: 71
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10.
Genetic programming approach for the material flow curve determination of copper alloy - CuCrZr
Leo Gusel, Miran Brezočnik, Rebeka Rudolf, Ivan Anžel, Z. Lazarević, Nebojša Romčević, 2010, original scientific article

Abstract: For the control of the forming process it is necessary to know as precisely as possible the flow curve of the formed material. The paper presents the determination of the equation for the flow curve of cooper alloy (CuCrZr) with artificial intelligence approach. The genetic programming method (GP) was used. It is an evolutionary optimization technique based on the Darwinist principles of the evolution of species and the survival of the fittest organisms. The main characteristic of GP is its non- deterministic way of computing. It is probably the most general approach out of evolutionary computation methods. The comparison between the experimental results, analytical solution and the solution obtained genetically clearly shows that the genetic programming method is a very promising approach.
Keywords: forming, flow curve, copper alloys, genetic programming
Published: 01.06.2012; Views: 910; Downloads: 12
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