Unveiled Sustainability: Beyond Carbon and towards a Holistic Analysis of Industrial Processes

first_page Download PDF settings Order Article Reprints Font Type: Arial Georgia Verdana Font Size: Aa Aa Aa Line Spacing:    Column Width:    Background: Open AccessAbstract Unveiled Sustainability: Beyond Carbon and towards a Holistic Analysis of Industrial Processes † by Paolo TrucilloPaolo Trucillo SciProfiles Scilit Preprints.org Google Scholar Dipartimento di Ingegneria Chimica, dei Materiali e della Produzione Industriale, University of Naples Federico II, P.le V. Tecchio, 80, 80125 Napoli, Italy † Presented at the 3rd International Electronic Conference on Processes—Green and Sustainable Process Engineering and Process Systems Engineering (ECP 2024), 29–31 May 2024; Available online: https://sciforum.net/event/ECP2024. Proceedings 2024, 105(1), 39; https://doi.org/10.3390/proceedings2024105039 Published: 28 May 2024 (This article belongs to the Proceedings of The 3rd International Electronic Conference on Processes—Green and Sustainable Process Engineering and Process Systems Engineering) Download keyboard_arrow_down Download PDF Download PDF with Cover Download XML Download Epub Versions Notes Keywords: sustainability indicators; radar diagrams; process comparison The concept of sustainability has gained significant traction in recent times, permeating not only academic but also industrial fields. Unfortunately, the use of this term is often confined to carbon dioxide emissions associated with specific manufacturing processes, leading to a simplistic or partial comprehension. A deeper definition of sustainability transcends a narrow focus on carbon emissions, embracing a harmonious synthesis of economic, social, and environmental considerations. A sustainable process enhances profitability, minimizes environmental impact, and fosters positive social implications. In the contemporary landscape, processes are commonly evaluated using conventional life cycle assessment analysis. However, sustainability indicators provide an alternative and more comprehensive perspective. These indicators, expressed as percentages, find visual representation through one-shot spider diagrams. The primary objective of such analyses is to maximize the area enclosed within the spider diagram, serving as the objective function for developing a specific product. This analytical tool facilitates the evaluation of process sustainability, enabling comparisons with competitors and aiding decisions regarding the selection of raw materials based on customer needs. The integration of cutting-edge technologies like artificial intelligence (AI) and machine learning (ML) into sustainability assessments has the potential to significantly improve the precision and efficiency of evaluating complex systems. AI's ability to process large datasets and identify intricate patterns enhances the understanding of the multifaceted dynamics in sustainability, revealing subtle correlations within economic, social, and environmental factors. Meanwhile, machine learning continuously refines its models, ensuring adaptability to emerging trends and real-time changes. This technological amalgamation not only promises more accurate assessments but also signifies a shift toward informed, data-driven decision-making for a sustainable future. FundingThis research received no external funding.Institutional Review Board StatementNot applicable.Informed Consent StatementNot applicable.Data Availability StatementDataset available on request from the authors.Conflicts of InterestThe author declares no conflict of interest.Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. © 2024 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Share and Cite MDPI and ACS Style Trucillo, P. Unveiled Sustainability: Beyond Carbon and towards a Holistic Analysis of Industrial Processes. Proceedings 2024, 105, 39. https://doi.org/10.3390/proceedings2024105039 AMA Style Trucillo P. Unveiled Sustainability: Beyond Carbon and towards a Holistic Analysis of Industrial Processes. Proceedings. 2024; 105(1):39. https://doi.org/10.3390/proceedings2024105039 Chicago/Turabian Style Trucillo, Paolo. 2024. "Unveiled Sustainability: Beyond Carbon and towards a Holistic Analysis of Industrial Processes" Proceedings 105, no. 1: 39. https://doi.org/10.3390/proceedings2024105039 Article Metrics No No Article Access Statistics Multiple requests from the same IP address are counted as one view.