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1.
Software tools overview : process integration, modelling and optimisation for energy saving and pollution reduction
Hon Loong Lam, Jiri Klemeš, Zdravko Kravanja, Petar Varbanov, 2011, original scientific article

Abstract: This paper provides an overview of software tools based on long experience andapplications in the area of process integration, modelling and optimisation. The first part reviews the current design practice and the development of supporting software tools. Those are categorised as: (1) process integration and retrofit analysis tools, (2) general mathematical modelling suites with optimisation libraries, (3) flowsheeting simulation and (4) graph-based process optimisation tools. The second part covers an assessment of tools which enable the generation of new sustainable alternatives to adapt to the future needs. They deal with waste, environment, energy consumption, resources depletion and production cost constrains. The emphasis of the sustainable process design tools is largely on the evaluation of process viability under sustainable economic conditions, synthesis of sustainable process and supply chain process maintenance and life cycle analysis. Major software tools development and the potential of the research-based tools for sustainable process design task are overviewed in theconcluding part.
Keywords: software tools, process integration, process modelling, process optimisation, energy saving
Published: 01.06.2012; Views: 1337; Downloads: 81
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2.
Modeling of forming efficiency using genetic programming
Miran Brezočnik, Jože Balič, Zlatko Kampuš, 2001, original scientific article

Abstract: 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.
Keywords: metal forming, yield stress, forming efficiency, mathematical modeling, adaptation, genetic methods, genetic algorithm, genetic programming, artificial intelligence, process optimisation
Published: 01.06.2012; Views: 1216; Downloads: 87
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