{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T19:02:25Z","timestamp":1750273345461,"version":"3.40.5"},"publisher-location":"Switzerland","reference-count":45,"publisher":"Trans Tech Publications Ltd","license":[{"start":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T00:00:00Z","timestamp":1696204800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.scientific.net\/PolicyAndEthics\/PublishingPolicies"},{"start":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T00:00:00Z","timestamp":1696204800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.scientific.net\/license\/TDM_Licenser.pdf"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>In recent years, the general population has become increasingly aware of the importance of adopting more sustainable lifestyles. For companies, the implementation of sustainable systems is essential. This study aims to examine the contribution of simulation in combination with artificial intelligence (AI) to the sustainability of production lines. Simulation plays a crucial role for managers, as it allows them to predict future scenarios based on past experiences, allowing for more informed with the rise of digitization in the industry, it is now possible to manage resources such as energy and water in a more efficient manner. This is achieved through the use of techniques such as data scanning, communication with intelligent industrial sensors, known as the Industrial Internet of Things (IIoT), and the application of optimization and AI-based solutions to tackle complex problems, both in terms of efficiency and sustainability. This analysis has confirmed the significance of simulation when partnered with AI in improving the sustainability of production lines. This is because they offer the means to improve resource management from an economic, environmental, and social perspective.<\/jats:p>","DOI":"10.4028\/p-cv6rt1","type":"proceedings-article","created":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T06:04:11Z","timestamp":1696226651000},"page":"405-412","source":"Crossref","is-referenced-by-count":3,"title":["The Use of Simulation and Artificial Intelligence as a Decision Support Tool for Sustainable Production Lines"],"prefix":"10.4028","volume":"132","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9920-4975","authenticated-orcid":false,"given":"Monica G.","family":"Cardoso","sequence":"first","affiliation":[{"name":"ISEP- Instituto de Engenharia do Porto"}]},{"given":"Enrique","family":"Ares","sequence":"additional","affiliation":[{"name":"University of Vigo"}]},{"given":"Luis Pinto","family":"Ferreira","sequence":"additional","affiliation":[{"name":"ISEP- Instituto de Engenharia do Porto"}]},{"given":"Gustavo","family":"Pel\u00e1ez","sequence":"additional","affiliation":[{"name":"University of Vigo"}]}],"member":"2457","published-online":{"date-parts":[[2023,10,2]]},"reference":[{"key":"4932600","doi-asserted-by":"publisher","first-page":"106773","DOI":"10.1016\/j.cie.2020.106773","article-title":"Machine learning applications in production lines: A systematic literature review","volume":"149","author":"Kang","unstructured":"Z. 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