Intensive Data and Knowledge‐based Approach for Sustainable and Circular Industrial Systems. Issue 4 (12th January 2022)

• Record Type: Journal Article
• Authors: Prioux, Nancy; Belaud, Jean‐Pierre; Hetreux, Gilles
• Is Part Of: Insight. Volume 24:Issue 4(2021)
• Page Start: 43
• Page End: 46
• Publication Date: 2022-01-12
• Subjects: Data Sciences -- Sustainability -- Circular Economy -- Biorefinery System -- Life Cycle Thinking -- Machine Learning; Systems engineering -- Periodicals; Systems engineering; Periodicals; 620.0011
• DOI: 10.1002/inst.12363
• Languages: English
• ISSNs: 2156-485X

Abstract

ABSTRACT: The circular economy and its various recirculation loops have become a major study subject over recent years, particularly the transformation of the actual processes into sustainable processes. However, these environmental analyses require a huge quantity of data: foreground data and background data. The collection of these data can be long and tedious. Nevertheless, an increasing number of scientific articles describe the processes, which is a great source of data. This source of information is heterogeneous but big data tools can be used to compile, process and analyze them. Following this perspective, this paper focus on the creation of methodological framework centered on intensive data and knowledge for an economically viable and ecologically responsible design of industrial processes or systems. Composed of five steps, this approach is oriented towards offering decision support for the researcher or R&D engineer during systems requirements and high‐level design steps of V‐model. It is implemented within the domain of pre‐treatment processes for corn stover.