{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T12:47:30Z","timestamp":1782823650891,"version":"3.54.5"},"reference-count":28,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers & Industrial Engineering"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.cie.2026.112095","type":"journal-article","created":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T08:57:42Z","timestamp":1778749062000},"page":"112095","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Generative large language models for predictive maintenance planning"],"prefix":"10.1016","volume":"218","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6526-3184","authenticated-orcid":false,"given":"Gerald","family":"Jones","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Williams","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tom","family":"Berg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Scott","family":"Lawson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luke","family":"Birt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ashley","family":"Stowe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1990-0159","authenticated-orcid":false,"given":"Xueping","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.cie.2026.112095_b1","doi-asserted-by":"crossref","DOI":"10.1016\/j.rser.2023.114088","article-title":"Machine learning scopes on microgrid predictive maintenance: Potential frameworks, challenges, and prospects","volume":"190","author":"Arafat","year":"2024","journal-title":"Renewable and Sustainable Energy Reviews"},{"issue":"3","key":"10.1016\/j.cie.2026.112095_b2","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1108\/JEDT-01-2021-0013","article-title":"A bibliometric review of advances in building information modeling (BIM) research","volume":"21","author":"Babalola","year":"2023","journal-title":"Journal of Engineering, Design and Technology"},{"key":"10.1016\/j.cie.2026.112095_b3","series-title":"A multitask, multilingual, multimodal evaluation of ChatGPT on reasoning, hallucination, and interactivity","author":"Bang","year":"2023"},{"issue":"2","key":"10.1016\/j.cie.2026.112095_b4","doi-asserted-by":"crossref","first-page":"866","DOI":"10.3390\/su14020866","article-title":"Taking responsibility for industrial digitalization: navigating organizational challenges","volume":"14","author":"Carlsson","year":"2022","journal-title":"Sustainability"},{"key":"10.1016\/j.cie.2026.112095_b5","article-title":"Application of retrieval-augmented generation for manufacturing systems integration","author":"Chen","year":"2025","journal-title":"Robotics and Computer-Integrated Manufacturing"},{"key":"10.1016\/j.cie.2026.112095_b6","series-title":"Determinants of LLM-assisted decision-making","author":"Eigner","year":"2024"},{"key":"10.1016\/j.cie.2026.112095_b7","first-page":"5539","article-title":"Openagi: When LLM meets domain experts","volume":"vol. 36","author":"Ge","year":"2023"},{"key":"10.1016\/j.cie.2026.112095_b8","series-title":"International conference on machine learning","first-page":"3929","article-title":"Retrieval augmented language model pre-training","author":"Guu","year":"2020"},{"issue":"4","key":"10.1016\/j.cie.2026.112095_b9","doi-asserted-by":"crossref","first-page":"1413","DOI":"10.1109\/TKDE.2023.3310002","article-title":"A survey of knowledge enhanced pre-trained language models","volume":"36","author":"Hu","year":"2024","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.cie.2026.112095_b10","series-title":"Leveraging passage retrieval with generative models for open domain question answering","author":"Izacard","year":"2021"},{"issue":"4","key":"10.1016\/j.cie.2026.112095_b11","doi-asserted-by":"crossref","DOI":"10.1061\/(ASCE)CF.1943-5509.0001604","article-title":"BIM-based maintenance management system for healthcare facilities","volume":"35","author":"Kamal","year":"2021","journal-title":"Journal of Performance of Constructed Facilities"},{"key":"10.1016\/j.cie.2026.112095_b12","series-title":"LLMs can\u2019t plan, but can help planning in LLM-modulo frameworks","author":"Kambhampati","year":"2024"},{"issue":"2","key":"10.1016\/j.cie.2026.112095_b13","doi-asserted-by":"crossref","first-page":"76","DOI":"10.3390\/info16020076","article-title":"Augmenting LLMs to securely retrieve information for facility management","volume":"16","author":"Kr\u00fctli","year":"2025","journal-title":"Information"},{"issue":"24","key":"10.1016\/j.cie.2026.112095_b14","doi-asserted-by":"crossref","first-page":"29758","DOI":"10.1007\/s10489-023-05092-4","article-title":"Exploring the potentials of online machine learning for predictive maintenance: a case study in the railway industry","volume":"53","author":"Le-Nguyen","year":"2023","journal-title":"Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies"},{"key":"10.1016\/j.cie.2026.112095_b15","series-title":"NeurIPS","article-title":"Retrieval-augmented generation for knowledge-intensive NLP","author":"Lewis","year":"2020"},{"issue":"1","key":"10.1016\/j.cie.2026.112095_b16","doi-asserted-by":"crossref","first-page":"160","DOI":"10.3901\/CJME.2012.01.160","article-title":"Reliability-based maintenance optimization under imperfect predictive maintenance","volume":"25","author":"Li","year":"2012","journal-title":"Chinese Journal of Mechanical Engineering"},{"issue":"1","key":"10.1016\/j.cie.2026.112095_b17","doi-asserted-by":"crossref","first-page":"233","DOI":"10.3390\/make6010013","article-title":"A text-based predictive maintenance approach for facility management requests utilizing association rule mining and large language models","volume":"6","author":"Lowin","year":"2024","journal-title":"Machine Learning and Knowledge Extraction"},{"key":"10.1016\/j.cie.2026.112095_b18","article-title":"An ontology-based retrieval augmented generation procedure for a voice-controlled maintenance assistant","author":"Ludwig","year":"2025","journal-title":"Robotics and Computer-Integrated Manufacturing"},{"issue":"3","key":"10.1016\/j.cie.2026.112095_b19","article-title":"Optimizing predictive maintenance with machine learning for reliability improvement","volume":"7","author":"Ren","year":"2021","journal-title":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering"},{"key":"10.1016\/j.cie.2026.112095_b20","article-title":"Generation of semantic knowledge graphs from maintenance work order data","author":"Tahsin","year":"2024","journal-title":"Semantic Web Journal"},{"issue":"2\u20133","key":"10.1016\/j.cie.2026.112095_b21","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/S0098-1354(00)00647-5","article-title":"Maintenance scheduling and process optimization under uncertainty","volume":"25","author":"Vassiliadis","year":"2001","journal-title":"Computers & Chemical Engineering"},{"key":"10.1016\/j.cie.2026.112095_b22","series-title":"ACL","article-title":"Knowledge graph retrieval-augmented generation for domain-specific question answering","author":"Wang","year":"2025"},{"key":"10.1016\/j.cie.2026.112095_b23","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2022.109068","article-title":"Maintenance planning recommendation of complex equipment based on knowledge graph and case-based reasoning","author":"Xia","year":"2023","journal-title":"Reliability Engineering & System Safety"},{"key":"10.1016\/j.cie.2026.112095_b24","series-title":"DSRAG: A domain-specific retrieval framework based on multimodal knowledge graphs","author":"Yang","year":"2025"},{"key":"10.1016\/j.cie.2026.112095_b25","series-title":"Knowledge plugins: Enhancing large language models for domain-specific recommendations","author":"Yao","year":"2023"},{"key":"10.1016\/j.cie.2026.112095_b26","series-title":"BIM-GPT: a prompt-based virtual assistant framework for BIM data retrieval and QA","author":"Zhang","year":"2023"},{"key":"10.1016\/j.cie.2026.112095_b27","series-title":"A survey of large language models","author":"Zhao","year":"2023"},{"key":"10.1016\/j.cie.2026.112095_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.119369","article-title":"Pre-training language model incorporating domain-specific heterogeneous knowledge into a unified representation","volume":"215","author":"Zhu","year":"2023","journal-title":"Expert Systems with Applications"}],"container-title":["Computers & Industrial Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360835226002962?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360835226002962?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T12:23:33Z","timestamp":1782822213000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0360835226002962"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":28,"alternative-id":["S0360835226002962"],"URL":"https:\/\/doi.org\/10.1016\/j.cie.2026.112095","relation":{},"ISSN":["0360-8352"],"issn-type":[{"value":"0360-8352","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Generative large language models for predictive maintenance planning","name":"articletitle","label":"Article Title"},{"value":"Computers & Industrial Engineering","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cie.2026.112095","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"112095"}}