A new approach presented in this book chapter enables the neural network-aided creation of alternative scenarios of future events, strategic placement of technologies with graphical analytical, i.e., contextual matrices and a comparative analysis of technologies using roadmaps and technology information sheets. The methodological approach presented serves to lessen the risk in predicting the prospective development directions of engineering materials surface layer properties and structure formation technologies. The analyses carried out indicate that heuristic studies, based on expert knowledge, allow to produce credible results of predicted technology development, without having to support them each time with the results of materials science research. This was confirmed in the experimental verification process of the new approach undertaken for 36 groups of technologies. The results of detailed experimental investigations into the structure and properties of engineering materials surface layers were used as a reference point. The newly established methodology, describing concisely the actions and activities targeted at creating multivariant probabilistic scenarios of future events, at selecting and characterizing the critical technologies in a clear and harmonized manner, and at paving the strategic development directions, organizes, streamlines, and modernizes the prediction process. The use of information technology encompassing a virtual organization, web platform, and artificial neural networks plays an important role here. It is reasonable to use artificial neural networks to create multivariant probabilistic scenarios of future events because they allow to generate very quickly alternative forecasts as probability values that the alternative macroscenarios of future events occur dependent upon the emergence of the special conditions or factors considered at a mezo-level. It was recognized that it is possible, needed, and necessary to implement the outcomes of the research performed in the economic reality at the macro-, mezo-, and microlevel and that the new methodology, supported with extended information technology, is suitable for direct applications in other areas of knowledge while maintaining economically reasonable costs. It is foreseen that if the effects of the e-foresight research performed are broadly disseminated via the Internet, this will represent – in line with the technology e-transfer concept – one of the crucial factors contributing to accelerated sustainable development, to a stronger knowledge- and innovation-based economy, and to statistical growth in the quality of technologies used in industry.

Comments

All the results, figures, and detailed diagrams presented in this chapter of the book have been developed in the framework of an author’s multiannual foresight project entitled FORSURF founded by EFFR and Polish Ministry of Science and Education completed in September 2012 aimed at determining the future development trends of materials surface engineering and at identifying the priority innovative technologies in this area.

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