1. A numerical simulation of metal injection mouldingBoštjan Berginc, Miran Brezočnik, Zlatko Kampuš, Borivoj Šuštaršič, 2009, izvirni znanstveni članek Opis: Metal injection moulding (MIM) is already a well-established and promising technology for the mass production of small, complex, near-net-shape products. The dimensions and mechanical properties of MIM products are influenced by the feedstock characteristics, the process parameters of the injection moulding, as well as the debinding and the sintering. Numerical simulations are a very important feature of the beginning of any product or technology development. In the article two different techniques for measuring the rheological properties of MIM feedstocks are presented and compared. It was established that capillary rheometers are more appropriate for MIM feed stocks, while on the other hand, parallel-plate rheometers are only suitable for shear rates lower than 10 s[sup]{-1}. Later on we used genetic algorithms to determine the model coefficients for some numerical simulation software. The results of the simulation of the filling phase and a comparison with the experimental results are presented in the article. Ključne besede: metal injection moulding, numerical simulation, genetic algorithms Objavljeno v DKUM: 14.03.2017; Ogledov: 1311; Prenosov: 169
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2. Modeling of forming efficiency using genetic programmingMiran 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 v DKUM: 01.06.2012; Ogledov: 2212; Prenosov: 123
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