@inproceedings{Alimam2023,
   abstract = {In the advent of Industry 5.0, the quest for high resilience and scalable smart manufacturing systems has strived for a retrofitting paradigm of brownfield development based on technology driven by Industry 4.0, where IIoT as a decentralised architecture of holistic data retrieval improvises a pivotal role of industrial system resilience in the transition from Industry 4.0 to Industry 5.0. This retrofitting paradigm leverages the technological advancement in artificial intelligence and digital transformation to diminish the complexity of imitating a comprehensive digital twin in cyberspace with distinguishing features of heuristic, scalability, adaptation, and interoperability, culminating in what is known as a 'digital triplet D3', in order to evoke the digital triplet adoption, eliminating the gap between the operators and smart technologies, especially in the oil and gas industry, which is still at an early stage when adopting digitalization in an intelligent environment. In this article, we propose an intelligent retrofitting paradigm that integrates the IIoT framework with the digital triplet hierarchy for fulfilling brownfield development that will enrich the human-centricity requirements of Industry 5.0 by harmonizing the augmentation of digitalization with humans for the resilience of human-machine symbiosis and Operator 5.0 by utilizing AR, machine learning, and artificial intelligence. This article also elucidates the implementation phases of the digital triplet paradigm for a case study of an oil and gas boosting plant that can leverage intelligent retrofitting scenarios in the IIoT framework.},
   author = {Hassan Alimam and Giovanni Mazzuto and Filippo Emanuele Ciarapica and Maurizio Bevilacqua},
   doi = {10.1109/SWC57546.2023.10449325},
   isbn = {979-8-3503-1980-4},
   booktitle = {2023 IEEE Smart World Congress (SWC)},
   month = {8},
   pages = {1-10},
   publisher = {IEEE},
   title = {Digital Triplet Paradigm for Brownfield Development towards Industry 5.0: A Case Study of Intelligent Retrofitting for Oil and Gas Boosting Plant in the Industrial Internet of Things (IIoT) Context},
   url = {https://ieeexplore.ieee.org/document/10449325/},
   year = {2023}
}

{"_id":"w7AWx8Gspew3boDy8","bibbaseid":"alimam-mazzuto-ciarapica-bevilacqua-digitaltripletparadigmforbrownfielddevelopmenttowardsindustry50acasestudyofintelligentretrofittingforoilandgasboostingplantintheindustrialinternetofthingsiiotcontext-2023","author_short":["Alimam, H.","Mazzuto, G.","Ciarapica, F. E.","Bevilacqua, M."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","abstract":"In the advent of Industry 5.0, the quest for high resilience and scalable smart manufacturing systems has strived for a retrofitting paradigm of brownfield development based on technology driven by Industry 4.0, where IIoT as a decentralised architecture of holistic data retrieval improvises a pivotal role of industrial system resilience in the transition from Industry 4.0 to Industry 5.0. This retrofitting paradigm leverages the technological advancement in artificial intelligence and digital transformation to diminish the complexity of imitating a comprehensive digital twin in cyberspace with distinguishing features of heuristic, scalability, adaptation, and interoperability, culminating in what is known as a 'digital triplet D3', in order to evoke the digital triplet adoption, eliminating the gap between the operators and smart technologies, especially in the oil and gas industry, which is still at an early stage when adopting digitalization in an intelligent environment. In this article, we propose an intelligent retrofitting paradigm that integrates the IIoT framework with the digital triplet hierarchy for fulfilling brownfield development that will enrich the human-centricity requirements of Industry 5.0 by harmonizing the augmentation of digitalization with humans for the resilience of human-machine symbiosis and Operator 5.0 by utilizing AR, machine learning, and artificial intelligence. This article also elucidates the implementation phases of the digital triplet paradigm for a case study of an oil and gas boosting plant that can leverage intelligent retrofitting scenarios in the IIoT framework.","author":[{"firstnames":["Hassan"],"propositions":[],"lastnames":["Alimam"],"suffixes":[]},{"firstnames":["Giovanni"],"propositions":[],"lastnames":["Mazzuto"],"suffixes":[]},{"firstnames":["Filippo","Emanuele"],"propositions":[],"lastnames":["Ciarapica"],"suffixes":[]},{"firstnames":["Maurizio"],"propositions":[],"lastnames":["Bevilacqua"],"suffixes":[]}],"doi":"10.1109/SWC57546.2023.10449325","isbn":"979-8-3503-1980-4","booktitle":"2023 IEEE Smart World Congress (SWC)","month":"8","pages":"1-10","publisher":"IEEE","title":"Digital Triplet Paradigm for Brownfield Development towards Industry 5.0: A Case Study of Intelligent Retrofitting for Oil and Gas Boosting Plant in the Industrial Internet of Things (IIoT) Context","url":"https://ieeexplore.ieee.org/document/10449325/","year":"2023","bibtex":"@inproceedings{Alimam2023,\n abstract = {In the advent of Industry 5.0, the quest for high resilience and scalable smart manufacturing systems has strived for a retrofitting paradigm of brownfield development based on technology driven by Industry 4.0, where IIoT as a decentralised architecture of holistic data retrieval improvises a pivotal role of industrial system resilience in the transition from Industry 4.0 to Industry 5.0. This retrofitting paradigm leverages the technological advancement in artificial intelligence and digital transformation to diminish the complexity of imitating a comprehensive digital twin in cyberspace with distinguishing features of heuristic, scalability, adaptation, and interoperability, culminating in what is known as a 'digital triplet D3', in order to evoke the digital triplet adoption, eliminating the gap between the operators and smart technologies, especially in the oil and gas industry, which is still at an early stage when adopting digitalization in an intelligent environment. In this article, we propose an intelligent retrofitting paradigm that integrates the IIoT framework with the digital triplet hierarchy for fulfilling brownfield development that will enrich the human-centricity requirements of Industry 5.0 by harmonizing the augmentation of digitalization with humans for the resilience of human-machine symbiosis and Operator 5.0 by utilizing AR, machine learning, and artificial intelligence. This article also elucidates the implementation phases of the digital triplet paradigm for a case study of an oil and gas boosting plant that can leverage intelligent retrofitting scenarios in the IIoT framework.},\n author = {Hassan Alimam and Giovanni Mazzuto and Filippo Emanuele Ciarapica and Maurizio Bevilacqua},\n doi = {10.1109/SWC57546.2023.10449325},\n isbn = {979-8-3503-1980-4},\n booktitle = {2023 IEEE Smart World Congress (SWC)},\n month = {8},\n pages = {1-10},\n publisher = {IEEE},\n title = {Digital Triplet Paradigm for Brownfield Development towards Industry 5.0: A Case Study of Intelligent Retrofitting for Oil and Gas Boosting Plant in the Industrial Internet of Things (IIoT) Context},\n url = {https://ieeexplore.ieee.org/document/10449325/},\n year = {2023}\n}\n","author_short":["Alimam, H.","Mazzuto, G.","Ciarapica, F. E.","Bevilacqua, M."],"key":"Alimam2023","id":"Alimam2023","bibbaseid":"alimam-mazzuto-ciarapica-bevilacqua-digitaltripletparadigmforbrownfielddevelopmenttowardsindustry50acasestudyofintelligentretrofittingforoilandgasboostingplantintheindustrialinternetofthingsiiotcontext-2023","role":"author","urls":{"Paper":"https://ieeexplore.ieee.org/document/10449325/"},"metadata":{"authorlinks":{}},"downloads":0,"html":""},"bibtype":"inproceedings","biburl":"https://bibbase.org/network/files/bZwErNh59xRSxEay2","dataSources":["ckSAQwMWRg82iJe5D"],"keywords":[],"search_terms":["digital","triplet","paradigm","brownfield","development","towards","industry","case","study","intelligent","retrofitting","oil","gas","boosting","plant","industrial","internet","things","iiot","context","alimam","mazzuto","ciarapica","bevilacqua"],"title":"Digital Triplet Paradigm for Brownfield Development towards Industry 5.0: A Case Study of Intelligent Retrofitting for Oil and Gas Boosting Plant in the Industrial Internet of Things (IIoT) Context","year":2023}