IF 0.8 4区 工程技术Q3 ENGINEERING, MULTIDISCIPLINARYDynaPub Date : 2023-11-01DOI:10.6036/10980
IÑIGO CAREAGA AJA, ANDREA CASAS OCAMPO, EKAITZ ZULUETA GUERRERO
{"title":"人工智能在电池回收方面提供的机会","authors":"IÑIGO CAREAGA AJA, ANDREA CASAS OCAMPO, EKAITZ ZULUETA GUERRERO","doi":"10.6036/10980","DOIUrl":null,"url":null,"abstract":"The new global decarbonization and energy transition guidelines have caused the industrial sector to undergo a metamorphosis towards more sustainable alternatives. To this end, phenomena such as digital transformation and the implementation of new solutions at the forefront of technological advances are helping to accelerate these changes. Key sectors for the future of society and industry, such as batteries, are already employing different tools based on big data, machine learning and artificial intelligence solutions to optimize both their design and production phases, with the aim of boosting a sector that is expected to reach a demand of almost 4.9 TWh by the end of this decade. However, these prospects also pose a major long-term challenge: the recycling of all these devices. Considering that this is an industry with increasingly stringent standards in terms of sustainability and circularity, this is where, once again, digital solutions such as those mentioned above can play a key role, both in terms of optimizing current recycling processes and developing new proposals and approaches. This paper aims to identify precisely that set of opportunities that artificial intelligence-based solutions can present to the battery recycling industry in its activities. Especially, in terms of development, evolution and optimization of the most promising technological routes (such as hydrometallurgy, pyrometallurgy or direct recycling), in order to respond to the challenges and needs of a strategic activity for the future of the battery value chain. Keywords: Batteries, Recycling, Recovery, Waste, Artificial Intelligence, Automation, Hydrometallurgy, Pyrometallurgy, Direct Recycling.","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"83 7","pages":"0"},"PeriodicalIF":0.8000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"OPPORTUNITIES OFFERED BY ARTIFICIAL INTELLIGENCE IN BATTERY RECYCLING\",\"authors\":\"IÑIGO CAREAGA AJA, ANDREA CASAS OCAMPO, EKAITZ ZULUETA GUERRERO\",\"doi\":\"10.6036/10980\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The new global decarbonization and energy transition guidelines have caused the industrial sector to undergo a metamorphosis towards more sustainable alternatives. To this end, phenomena such as digital transformation and the implementation of new solutions at the forefront of technological advances are helping to accelerate these changes. Key sectors for the future of society and industry, such as batteries, are already employing different tools based on big data, machine learning and artificial intelligence solutions to optimize both their design and production phases, with the aim of boosting a sector that is expected to reach a demand of almost 4.9 TWh by the end of this decade. However, these prospects also pose a major long-term challenge: the recycling of all these devices. Considering that this is an industry with increasingly stringent standards in terms of sustainability and circularity, this is where, once again, digital solutions such as those mentioned above can play a key role, both in terms of optimizing current recycling processes and developing new proposals and approaches. This paper aims to identify precisely that set of opportunities that artificial intelligence-based solutions can present to the battery recycling industry in its activities. Especially, in terms of development, evolution and optimization of the most promising technological routes (such as hydrometallurgy, pyrometallurgy or direct recycling), in order to respond to the challenges and needs of a strategic activity for the future of the battery value chain. Keywords: Batteries, Recycling, Recovery, Waste, Artificial Intelligence, Automation, Hydrometallurgy, Pyrometallurgy, Direct Recycling.\",\"PeriodicalId\":11386,\"journal\":{\"name\":\"Dyna\",\"volume\":\"83 7\",\"pages\":\"0\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Dyna\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.6036/10980\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dyna","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.6036/10980","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
OPPORTUNITIES OFFERED BY ARTIFICIAL INTELLIGENCE IN BATTERY RECYCLING
The new global decarbonization and energy transition guidelines have caused the industrial sector to undergo a metamorphosis towards more sustainable alternatives. To this end, phenomena such as digital transformation and the implementation of new solutions at the forefront of technological advances are helping to accelerate these changes. Key sectors for the future of society and industry, such as batteries, are already employing different tools based on big data, machine learning and artificial intelligence solutions to optimize both their design and production phases, with the aim of boosting a sector that is expected to reach a demand of almost 4.9 TWh by the end of this decade. However, these prospects also pose a major long-term challenge: the recycling of all these devices. Considering that this is an industry with increasingly stringent standards in terms of sustainability and circularity, this is where, once again, digital solutions such as those mentioned above can play a key role, both in terms of optimizing current recycling processes and developing new proposals and approaches. This paper aims to identify precisely that set of opportunities that artificial intelligence-based solutions can present to the battery recycling industry in its activities. Especially, in terms of development, evolution and optimization of the most promising technological routes (such as hydrometallurgy, pyrometallurgy or direct recycling), in order to respond to the challenges and needs of a strategic activity for the future of the battery value chain. Keywords: Batteries, Recycling, Recovery, Waste, Artificial Intelligence, Automation, Hydrometallurgy, Pyrometallurgy, Direct Recycling.
期刊介绍:
Founded in 1926, DYNA is one of the journal of general engineering most influential and prestigious in the world, as it recognizes Clarivate Analytics.
Included in Science Citation Index Expanded, its impact factor is published every year in Journal Citations Reports (JCR).
It is the Official Body for Science and Technology of the Spanish Federation of Regional Associations of Engineers (FAIIE).
Scientific journal agreed with AEIM (Spanish Association of Mechanical Engineering)
In character Scientific-technical, it is the most appropriate way for communication between Multidisciplinary Engineers and for expressing their ideas and experience.
DYNA publishes 6 issues per year: January, March, May, July, September and November.