| Issue |
SHS Web of Conf.
Volume 44, 2018
IV International Scientific Conference “The Convergence of Digital and Physical Worlds: Technological, Economic and Social Challenges” (CC-TESC2018)
|
|
|---|---|---|
| Article Number | 00045 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/shsconf/20184400045 | |
| Published online | 05 June 2018 | |
A fuzzy set model for assessment of a perspectives level for integration of new materials in industrial enterprise processesa
Peter the Great St. Petersburg Polytechnic University, Institute of Industrial Management, Economics and Trade, 195251 Politekhnicheskaya st. 29, Russian Federation
* Corresponding author: konnikov.evgeniy@gmail.com
The definition of effective improvement vectors is currently one of the most pressing challenges facing the industry representatives. The transition to the sixth technological mode effectively contributes to competition intensification in all markets of industrial products. This is largely due to the fact that existing process systems are at the peak of their effectiveness. Further development requires qualitative changes. However, the principal improvement is a long-term and high-risk process. For this reason the issue of creating effective models for assessment of the strategic lines of processes improvement becomes increasingly important for industrial enterprises. This article considers in details the vector of industrial enterprise processes improvement based on the integration of new materials. As a result, a model allowing to assess a perspectives level for integration of new materials in industrial enterprise processes is created.
The research results were published in the framework of the project “Development of a forecast for implementing the scientific and technological advancement priority defined in item 20a of the Scientific and Technological Development Strategy of the Russian Federation (transition to the advanced digital, intelligent production technologies, robotic systems, new materials and design methods, big data, machine learning and artificial intelligence)” is funded by the Ministry of Education and Science of the Russian Federation from the grant funds in the framework of the Federal Program “Research and Development in Priority Fields for Advancement of the Scientific and Technological Sector of Russia for 2014-2020”, Event 1.1, Granting Agreement No. 14.572.21.0008 dated October 23, 2017, the unique identifier: RFMEFI57217X0006
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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