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Neural networks aided future events scenarios presented on the example of laser surface treatment

Dobrzańska-Danikiewicz A., Trzaska J., Jagiełło A., Jonda E., Labisz K.

Archives of Materials Science and Engineering

2011

Vol. 51, nr 2

69-96

Purpose: The purpose of the paper is to present a methodological concept allowing to demonstrate the development directions of materials surface engineering according to the level of generality and the intensity of the phenomena analysed on other phenomena. Design/methodology/approach: A set of analytical methods and tools was used to present the development directions of materials surface engineering at the three levels analysed, i.e.: a macro-, meso- and microlevel. The analytical methods and tools comprise the scenario method, artificial neural networks, Monte Carlo method, e-Dephix method, statistical lists as bar charts, foresight matrices together with technology development tracks, technology roadmaps, technology information sheets and the classical materials science methods. Findings: A research methodology allowing to combine a presentation and description of the forecast future events having a varied level of generality and capturing the cause and effect relationships existing between the events. Research limitations/implications: The methodological concept discussed, implemented with reference to materials surface engineering, has a much broader meaning, and can be successfully applied in other technology foresights, and also in industrial and thematic foresights after minor modifications. Practical implications: The outcomes of the research conducted may be and should be used in the process of creating and managing the future of materials surface engineering and, within the time horizon of 20 years, may and should influence positively the development of the economy based on knowledge and innovation, sustainable development and the statistical level of the technologies used in industry, especially in small- and medium-sized enterprises. Originality/value: An own methodological concept constitutes an original way of presenting the development directions of the investigated field of knowledge. The use of neural networks