E3S Web Conf.
Volume 217, 2020International Scientific and Practical Conference “Environmental Risks and Safety in Mechanical Engineering” (ERSME-2020)
|Number of page(s)||7|
|Published online||14 December 2020|
Cognitive analysis of eco-economic processes
1 Southern Federal University, Bolshaya Sadovaya str., 105/42 Rostov-on Don, 344000, Russia
2 PJSC «Rostvertol», Nagibina str. 30, Rostov-on Don, 344000, Russia
* Corresponding author: firstname.lastname@example.org
It has been noted that the 21st century saw significant changes in public views on the economy-ecology relationship. Growing number of applied studies of eco-economic issues as well as the need to comprehend achieved results brought the use of cognitive analytics to the fore. Cognitive model provides a holistic view on the existing eco-economic process through its graphic representation reflecting nature and dynamics of causal relationships. Cognitive analysis of the conventional models of eco-economic process revealed that they mainly focus on economic procedures while environmental issues being shifted towards the periphery. Likewise, the traditional model essentially limits production development by ecological requirements while environmental condition is inherently impaired and requires further restoration or, at the very least, decontamination. The new models of manufacturing organization must aim to improve human environment as a whole and base on a zero-waste production principle where underused resources and raw materials are considered as waste. This article presents a cognitive model of green manufacturing in the shape of a multi-circuit system with all the circuits involved in the zero-waste production cycle. Considering that all circuits employ positive feedback, they initiate growth and mutually support consistent operation of an enterprise. A zero-waste enterprise can and should develop in cooperation with other enterprises that consciously or implicitly (formally) implement sustainable manufacturing plans.
© The Authors, published by EDP Sciences, 2020
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.
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