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1.
Adaptive self-learning controller design for feedrate maximization of machining process
Franc Čuš, Uroš Župerl, 2007, izvirni znanstveni članek

Opis: An adaptive control system is built which controlling the cutting force and maintaining constant roughness of the surface being milled by digital adaptation of cutting parameters. The paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy (Particle Swarm Optimization) in modeling and adaptively controlling the process of end milling. An overall approach of hybrid modeling of cutting process (ANfis-system), used for working out the CNC milling simulator has been prepared. The basic control design is based on the control scheme (UNKS) consisting of two neural identificators of the process dynamics and primary regulator. Experiments have confirmed efficiency of the adaptive control system, which is reflected in improved surface quality and decreased tool wear.
Ključne besede: end milling, adaptive force control, artificial intelligence, optimisation, adaptive control systems
Objavljeno: 31.05.2012; Ogledov: 689; Prenosov: 7
URL Celotno besedilo (0,00 KB)

2.
Design of row-based flexible manufacturing system with evolutionary computation
Mirko Ficko, Jože Balič, 2008, objavljeni znanstveni prispevek na konferenci

Opis: 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.
Ključne besede: flexible manufacturing system design, genetic algorithms, evolutionary computation, intelligent manufacturing systems, artificial intelligence
Objavljeno: 31.05.2012; Ogledov: 830; Prenosov: 12
URL Celotno besedilo (0,00 KB)

3.
Tool cutting force modeling in ball-end milling using multilevel perceptron
Uroš Župerl, Franc Čuš, 2004, izvirni znanstveni članek

Opis: This paper uses the artificial neural networks (ANNs) approach to evolve an efficient model for estimation of cutting forces, based on a set of input cutting conditions. A neural network algorithms are developed for use as a direct modeling method, to predict forces for ball-end milling operation. Supervised neural networks are used to successfully estimate the cutting forces developed during end milling process. The training of the networks is preformed with experimental machining data. The predictive capability of using analytical and neural network approaches are compared using statistics, which showed that neural network predictions for three cutting force components were for 4% closer to the experimental measurements, compared to 11% using analytical method. Exhaustive experimentation is conduced to develop the model and to validate it. The milling experiments prove that this model can predict accurately the cutting forces in three Cartesian directions.The force model can be used for simulation purposes and for defining threshold values in cutting tool condition monitoring system.
Ključne besede: ball end milling, cutting forces, modelling, artificial intelligence, neural networks
Objavljeno: 01.06.2012; Ogledov: 855; Prenosov: 4
URL Celotno besedilo (0,00 KB)

4.
Modeling of forming efficiency using genetic programming
Miran Brezočnik, Jože Balič, Zlatko Kampuš, 2001, izvirni znanstveni članek

Opis: This paper proposes new approach for modeling of various processes in metal-forming industry. As an example, we demonstrate the use of genetic programming (GP) for modeling of forming efficiency. The forming efficiency is a basis for determination of yield stress which is the fundamental characteristic of metallic materials. Several different genetically evolved models for forming efficiency on the basis of experimental data for learning were discovered. The obtained models (equations) differ in size, shape, complexity and precision of solutions. In one run out of many runs of our GP system the well-known equation of Siebel was obtained. This fact leads us to opinion that GP is a very powerful evolutionary optimization method appropriate not only for modeling of forming efficiency but also for modeling of many other processes in metal-forming industry.
Ključne besede: metal forming, yield stress, forming efficiency, mathematical modeling, adaptation, genetic methods, genetic algorithm, genetic programming, artificial intelligence, process optimisation
Objavljeno: 01.06.2012; Ogledov: 726; Prenosov: 9
URL Celotno besedilo (0,00 KB)

5.
A model of tool wear monitoring system for turning
Goran Šimunović, Mirko Ficko, Tomislav Šarić, Mijodrag Milošević, Aco Antić, 2013, izvirni znanstveni članek

Opis: Acquiring high-quality and timely information on the tool wear condition in real time, presents a necessary prerequisite for identification of tool wear degree, which significantly improves the stability and quality of the machining process. Defined in this paper is a model of tool wear monitoring system with special emphasis on the module for acquisition and processing of vibration acceleration signal by applying discrete wavelet transformations (DWT) in signal decomposition. The paper presents a model of the developed fuzzy system for tool wear classification. The system comprises three modules: module for data acquisition and processing, module for tool wear classification, and module for decision-making. The selected method for feature extraction is presented within the module for data classification and processing. The selected model for the fuzzy classifier and classification in experimental laboratory conditions is shown within data classification and clustering. The proposed model has been tested in longitudinal and transversal machining operations.
Ključne besede: artificial intelligence, tool wear monitoring, feature extraction
Objavljeno: 10.07.2015; Ogledov: 153; Prenosov: 6
.pdf Celotno besedilo (1,87 MB)

6.
7.
Intelligent design and optimization of machining fixtures
Djordje Vukelić, Goran Šimunović, Branko Tadic, Borut Buchmeister, Tomislav Šarić, Nenad Simeunovic, 2016, izvirni znanstveni članek

Opis: This work presents an integral system for machining fixture layout design and optimization. The optimization module of this system allows determination of optimal positions of locating and clamping elements, which provides required accuracy and surface quality, while at the same time guarantees design of collision-free fixtures. The design module performs selection of required fixture elements based on a set of predefined production rules. Adequate criteria for the selection of fixture elements are defined for locating, clamping, tool guiding, and tool adjustment elements, as well as for fixture body elements, connecting elements and add-on elements. The system uses geometry and feature workpiece characteristics, as well as the additional machining, and process planning information. It has been developed to accommodate machining processes of turning, drilling, milling, and grinding of rotational and prismatic workpieces. A segment of output results is also shown. Finally, conclusions are presented with directions for future investigation.
Ključne besede: artificial intelligence, fixture, process planning
Objavljeno: 12.07.2017; Ogledov: 80; Prenosov: 3
.pdf Celotno besedilo (2,97 MB)

8.
Advances in Production and Industrial Engineering
2017, znanstvena monografija

Opis: This publication, scientific monograph, offers comprehensive chapter series from scientific researchers conducted by regional authors, authorities in the fields and summarizes the principal scientific contributions. The chapters deal with range topics from optimization techniques in production development, quality in production processes, product and process development, technologies for business development and factors of social and economic development. Edited by two editors with contributions from chapters’ authors, this scientific monograph presents advanced topics for students, educators and practitioners. The editors would like to thank all chapters’ authors for devoting of the research results and expertise with the great enthusiasm. We encourage all of them to continue successful highly valuable cooperation, between Faculty of Mechanical Engineering at the University of Maribor and Faculty of Mechanical
Ključne besede: mechanical engineering, production management, manufacturing, artificial intelligence, process development, economic development
Objavljeno: 19.07.2017; Ogledov: 125; Prenosov: 6
URL Celotno besedilo (0,00 KB)

9.
Artificial intelligence versus human talents in learning process
Janez Bregant, Boris Aberšek, 2011, izvirni znanstveni članek

Opis: To highlight the differences between conventional educational systems and CBLS - computer based learning systems. It is useful to consider CBLS, as the class of a system most closely related to artificial intelligence - AI. In such a system, the ultimate goal is to create a virtual duplicate of reality for learning, analysis, training, experimentation, or other purposes. Simulating reality is an approach that may or may not be useful at creating experience. This distinction yield several consequences. In CBLS, behaviour should be as realistic as possible, the representation of environment tends to be uniform and consistent and allowing users to act freely within that environment. To teach users through realistic experience CBLS design techniques can make the experience much more memorable. In such an environment the context and control afforded by design techniques allow the integration of technologies and evaluation of the overall experience. Perhaps it is time to take lessons of CBLS and AI in a learning design and teaching tools seriously. At the beginning we will point out one simple question: could the ideas, methodology and techniques of AI also be applied to a development of relatively serious mind applications and can they substitute human teachers? And the answer will be continued in our paper.
Ključne besede: education, intelligent tutors, artificial intelligence, CBLS
Objavljeno: 12.12.2017; Ogledov: 111; Prenosov: 4
.pdf Celotno besedilo (465,85 KB)

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