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1.
An intelligent system for structural analysis-based design improvements
Marina Novak, Bojan Dolšak, 2008, original scientific article

Abstract: The goal of the research work presented in this paper was to collect, organize, and write the knowledge and experience about structural analysis-based design improvements into a knowledge base for a consultative advisory intelligent decision support system. The prototype of the system presented proposes possible design changes that should be taken into consideration to improve the design candidate according to the results of a prior stress-strain or thermal analysis. The system can be applied either in the design of new products or as an educational tool.
Keywords: computer-aided design, structural optimisation, knowledge based systems, decision support
Published: 31.05.2012; Views: 1473; Downloads: 19
URL Link to full text

2.
A model of data flow in lower CIM levels
Igor Drstvenšek, Ivo Pahole, Jože Balič, 2004, original scientific article

Abstract: After years of work in fields of computer-integrated manufacturing (CIM), flexible manufacturing systems (FMS), and evolutionary optimisation techniques, several models of production automation were developed in our laboratories. The last model pools the discoveries that proved their effectiveness in the past models. It is based on the idea of five levels CIM hierarchy where the technological database (TDB) represents a backbone of the system. Further on the idea of work operation determination by an analyse of the production system is taken out of a model for FMS control system, and finally the approach to the optimisation of production is supported by the results of evolutionary based techniques such as genetic algorithms and genetic programming.
Keywords: computer integrated manufacturing, flexible manufacturing systems, evolutionary optimisation techniques, production automation, CIM hierarchy, technological databases, production optimisation, genetic algorithms, genetic programming
Published: 01.06.2012; Views: 1293; Downloads: 62
URL Link to full text

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Proceedings of the 23rd IEEE International Symposium on Computer-Based Medical Systems CBMS 2010, October 12-15, 2010 Perth, Australia
proceedings of peer-reviewed scientific conference contributions (international and foreign conferences)

Keywords: medical systems, computer-based medical systems, machine learning methods, bioinformatics
Published: 05.06.2012; Views: 973; Downloads: 24
URL Link to full text

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GAJA
David Potočnik, Bojan Dolšak, Miran Ulbin, 2013, original scientific article

Abstract: Although the designing of cutting-dies is a complex and experience-based process, it is poorly supported by conventional 3D CAD software. Thus, the majority of design activities, including the (re)modeling of those cutting die-components that are directly responsible for performing shaping operations on a sheet-metal stamping part, traditionally still need to be carried-out repetitively, separately, and manually by the designer. In order to eliminate some of these drawbacks and upgrade the capabilities of conventional 3D CAD software, this paper proposes a new methodology for the development of a parametric system capable of automatically performing a (re)modeling process of compound washer diesć cutting-components. The presented methodology integrates CATIA V5 built-in modules, including Part Design, Assembly Design and Knowledge Advisor, publication mechanism, and compound cutting die-design knowledge. The system developed by this methodology represents an 'intelligent' assembly template composed of two modules 'GAJA1' and 'GAJA2', respectively. 'GAJA1' is responsible for the direct input of the die-design problem regarding the shape, dimensions and material of the stamping part, its extraction in the form of geometric features, and the transferring of relevant design parameters and features to the module 'GAJA2'. 'GAJA2' interprets the current values for the input parameters and automatically performs the modeling process of cutting die-components, using die-design knowledge and the company's internal design and manufacturing standards. Experimental results show that the use of this system significantly shortens the modeling-time for cutting the die-components, improves the modeling-quality, and enables the training of inexperienced designers.
Keywords: parametrično modeliranje, rezalna orodja, računalniško podprti sistemi, inteligentno računalniško podprto konstruiranje, parametric modeling, cutting dies, computer-aided systems, knowledge-based design
Published: 10.07.2015; Views: 1794; Downloads: 25
URL Link to full text

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