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A Modular Tool to Support Data Management for LCA in Industry: Methodology, Application and Potentialities
 
 
Review

Systematic Literature Review on Dynamic Life Cycle Inventory: Towards Industry 4.0 Applications

1
Singapore Institute of Manufacturing Technology, 2 Fusionopolis Way, Singapore 138634, Singapore
2
Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117575, Singapore
3
STIIMA-CNR-Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, Via Alfonso Corti 12, 20133 Milan, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Vikas Kumar
Sustainability 2022, 14(11), 6464; https://doi.org/10.3390/su14116464
Received: 2 March 2022 / Revised: 18 May 2022 / Accepted: 22 May 2022 / Published: 25 May 2022
Life cycle assessment (LCA) is a well-established methodology to quantify the environmental impacts of products, processes, and services. An advanced branch of this methodology, dynamic LCA, is increasingly used to reflect the variation in such potential impacts over time. The most common form of dynamic LCA focuses on the dynamism of the life cycle inventory (LCI) phase, which can be enabled by digital models or sensors for a continuous data collection. We adopt a systematic literature review with the aim to support practitioners looking to apply dynamic LCI, particularly in Industry 4.0 applications. We select 67 publications related to dynamic LCI studies to analyze their goal and scope phase and how the dynamic element is integrated in the studies. We describe and discuss methods and applications for dynamic LCI, particularly those involving continuous data collection. Electricity consumption and/or electricity technology mixes are the most used dynamic components in the LCI, with 39 publications in total. This interest can be explained by variability over time and the relevance of electricity consumption as a driver of environmental impacts. Finally, we highlight eight research gaps that, when successfully addressed, could benefit the diffusion and development of sound dynamic LCI studies. View Full-Text
Keywords: dynamic life cycle assessment; temporal differentiation; temporal; dynamic modeling; real-time dynamic life cycle assessment; temporal differentiation; temporal; dynamic modeling; real-time
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MDPI and ACS Style

Cornago, S.; Tan, Y.S.; Brondi, C.; Ramakrishna, S.; Low, J.S.C. Systematic Literature Review on Dynamic Life Cycle Inventory: Towards Industry 4.0 Applications. Sustainability 2022, 14, 6464. https://doi.org/10.3390/su14116464

AMA Style

Cornago S, Tan YS, Brondi C, Ramakrishna S, Low JSC. Systematic Literature Review on Dynamic Life Cycle Inventory: Towards Industry 4.0 Applications. Sustainability. 2022; 14(11):6464. https://doi.org/10.3390/su14116464

Chicago/Turabian Style

Cornago, Simone, Yee Shee Tan, Carlo Brondi, Seeram Ramakrishna, and Jonathan Sze Choong Low. 2022. "Systematic Literature Review on Dynamic Life Cycle Inventory: Towards Industry 4.0 Applications" Sustainability 14, no. 11: 6464. https://doi.org/10.3390/su14116464

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