Journal
JOURNAL OF CLEANER PRODUCTION
Volume 286, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2020.125314
Keywords
Life cycle assessment (LCA); Life cycle inventory (LCI); Enterprise resource planning (ERP); Industry 4.0; Business intelligence (BI)
Categories
Funding
- European Union under the LIFE Program [LIFE16ENV/IT/000307]
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With the advancement of Industry 4.0, new technologies have enabled companies to collect comprehensive data for monitoring and continuous improvement of production processes. Integrating ERP systems with customized LCA tools can effectively evaluate and monitor environmental impacts of the production process.
With the advent of Industry 4.0, new technologies have been made available to companies in order to monitor, integrate and trace processes through integrated digital systems; thanks to a combination of sensors and control systems, manufacturing information are collected and processed so that a detailed database helpful for the monitoring and continuous improvement of the production plant can be built. The potentiality of this comprehensive data collection may be exploited also from an environmental point of view, with the aim to enhance the sustainability of processes; in fact, a large part of this data provides the basis for the Life Cycle Inventory (LCI), the most energy and time-consuming phase of the Life Cycle Assessment (LCA) which in this way could become quicker and dynamic. Based on a case study related to an Italian ceramic tile manufacturer, the aim of this paper is to describe the architecture and the application of the Dynamic LCA system that integrates the Enterprise Resource Planning (ERP) system with a customized LCA tool through a Business Intelligence (BI) software. The model was tested on different levels of validation in order to verify first the proper functioning of the IT architecture and then the environmental impact results provided, both in a static and dynamic way. The validation processes were successful, and the Dynamic LCA system has proved to be a valuable tool for the evaluation and monitoring of environmental impacts related to the production process. (c) 2020 Elsevier Ltd. All rights reserved.
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