{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T12:06:45Z","timestamp":1726229205693},"publisher-location":"Cham","reference-count":19,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031436659"},{"type":"electronic","value":"9783031436666"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-43666-6_46","type":"book-chapter","created":{"date-parts":[[2023,9,13]],"date-time":"2023-09-13T06:02:34Z","timestamp":1694584954000},"page":"674-688","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Development of Predictive Maintenance Models for a Packaging Robot Based on Machine Learning"],"prefix":"10.1007","author":[{"given":"Ayoub","family":"Chakroun","sequence":"first","affiliation":[]},{"given":"Yasmina","family":"Hani","sequence":"additional","affiliation":[]},{"given":"Sadok","family":"Turki","sequence":"additional","affiliation":[]},{"given":"Nidhal","family":"Rezg","sequence":"additional","affiliation":[]},{"given":"Abderrahmane","family":"Elmhamedi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,9,14]]},"reference":[{"key":"46_CR1","doi-asserted-by":"publisher","unstructured":"Chakroun, A., Hani, Y., Elmhamedi, A., Masmoudi, F.: A proposed integrated manufacturing system of a workshop producing brass accessories in the context of industry 4.0. Int. J. Adv. Manuf. Technol. 127, 2017\u20132033 (2022). https:\/\/doi.org\/10.1007\/s00170-022-10057-x","DOI":"10.1007\/s00170-022-10057-x"},{"key":"46_CR2","doi-asserted-by":"publisher","unstructured":"Chakroun, A., Hani, Y., Masmoudi. F., El Mhamedi, A.: Digital transformation process of a mechanical parts production workshop to fulfil the requirements of Industry 4.0. In: LOGISTIQUA 2022 IEEE: 14th International conference of Logistics and Supply Chain Management LOGISTIQUA 2022 \u2013 25\u201327 May 2022, ELJADIDA, Morocco, p. 6 (2022). https:\/\/doi.org\/10.1109\/LOGISTIQUA55056.2022.9938099","DOI":"10.1109\/LOGISTIQUA55056.2022.9938099"},{"key":"46_CR3","unstructured":"Gim\u00e9lec. Industry 4.0: The levers of transformation, p. 84 (2014). http:\/\/www.gimelec.fr\/"},{"issue":"3","key":"46_CR4","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1108\/13552510710780276","volume":"13","author":"A Parida","year":"2007","unstructured":"Parida, A., Chattopadhyay, G.: Development of a multi-criteria hierarchical framework for maintenance performance measurement (MPM). J. Qual. Maintenance Eng. 13(3), 241\u2013258 (2007). https:\/\/doi.org\/10.1108\/13552510710780276","journal-title":"J. Qual. Maintenance Eng."},{"key":"46_CR5","doi-asserted-by":"publisher","unstructured":"Parida, A., Kumar, U.: Maintenance performance measurement (MPM): issues and challenges. J. Qual. Maintenance Eng. 12(3), 239\u2013251 (2006). https:\/\/doi.org\/10.1108\/13552510610685084","DOI":"10.1108\/13552510610685084"},{"key":"46_CR6","doi-asserted-by":"publisher","unstructured":"Kans, M., Inglwad, A.: Common database for cost-effective improvement of maintenance performance. Int. J. Prod. Econ. 113(2), 734\u2013747. (2008). https:\/\/doi.org\/10.1016\/j.ijpe.2007.10.008","DOI":"10.1016\/j.ijpe.2007.10.008"},{"key":"46_CR7","doi-asserted-by":"publisher","unstructured":"Sari, E., Shaharoun, A.M., Ma\u2019aram, A., Yazid, A.M.: Sustainable maintenance performance measures: a pilot survey in Malaysian automotive companies. Procedia CIRP 26, 443\u2013448 (2015). https:\/\/doi.org\/10.1016\/j.procir.2014.07.163","DOI":"10.1016\/j.procir.2014.07.163"},{"issue":"4","key":"46_CR8","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1108\/JMTM-04-2013-0033","volume":"25","author":"D Maleti\u010d","year":"2014","unstructured":"Maleti\u010d, D., Maleti\u010d, M., Al-Najjar, B., Gomi\u0161\u010dek, B.: The role of maintenance in improving company\u2019s competitiveness and profitability: a case study in a textile company. J. Manuf. Technol. Manag. 25(4), 441\u2013456 (2014). https:\/\/doi.org\/10.1108\/JMTM-04-2013-0033","journal-title":"J. Manuf. Technol. Manag."},{"key":"46_CR9","doi-asserted-by":"publisher","unstructured":"Rault, R., Trentesaux, D.: Artificial intelligence, autonomous systems and robotics: legal innovations. In: Borangiu, T., Trentesaux, D., Thomas, A., Cardin, O. (eds.) Service Orientation in Holonic and Multi-Agent Manufacturing, pp. 1\u20139. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-73751-5_1","DOI":"10.1007\/978-3-319-73751-5_1"},{"key":"46_CR10","doi-asserted-by":"crossref","unstructured":"Leukel, J., Gonz\u00e1lez, J., Riekert, M.: Adoption of machine learning technology for failure prediction in industrial maintenance: a systematic review. J. Manuf. Syst. 61, 87\u201396 (2021)","DOI":"10.1016\/j.jmsy.2021.08.012"},{"key":"46_CR11","doi-asserted-by":"publisher","unstructured":"Shcherbakov, M.V., Glotov, A.V., Cheremisinov, S.V.: Proactive and predictive maintenance of cyber-physical systems. In: Kravets, A., Bolshakov, A., Shcherbakov, M. (eds.) Cyber-Physical Systems: Advances in Design & Modelling, vol. 259, pp. 263\u2013278. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-32579-4_21","DOI":"10.1007\/978-3-030-32579-4_21"},{"key":"46_CR12","doi-asserted-by":"publisher","unstructured":"Chaudhuri, A.: Predictive maintenance for industrial IoT of vehicle fleets using hierarchical modified fuzzy support vector machine. ArXiv preprint arXiv. 1806.09612 (2018). https:\/\/doi.org\/10.48550\/arXiv.1806.09612","DOI":"10.48550\/arXiv.1806.09612"},{"issue":"6","key":"46_CR13","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1016\/j.com-pind.2006.02.011","volume":"57","author":"MC Garcia","year":"2006","unstructured":"Garcia, M.C., Sanz-Bobi, M.A., Del Pico, J.: SIMAP: intelligent system for predictive maintenance: application to the health condition monitoring of a wind turbine gearbox. Comput. Ind. 57(6), 552\u2013568 (2006). https:\/\/doi.org\/10.1016\/j.com-pind.2006.02.011","journal-title":"Comput. Ind."},{"issue":"1","key":"46_CR14","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/S0951-8320(01)00107-7","volume":"75","author":"SK Yang","year":"2002","unstructured":"Yang, S.K.: An experiment of state estimation for predictive maintenance using Kalman filter on a DC motor. Reliab. Eng. Syst. Saf. 75(1), 103\u2013111 (2002). https:\/\/doi.org\/10.1016\/S0951-8320(01)00107-7","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"46_CR15","doi-asserted-by":"crossref","unstructured":"Xia, T., Ding, Y., Dong, Y., et al.: Collaborative production and predictive maintenance scheduling for flexible flow shop with stochastic interruptions and monitoring data. J. Manuf. Syst. 65, 640\u2013652 (2022)","DOI":"10.1016\/j.jmsy.2022.10.016"},{"key":"46_CR16","doi-asserted-by":"crossref","unstructured":"Bencheikh, G., Letouzey, A., Desforges, X.: An approach for joint scheduling of production and predictive maintenance activities. J. Manuf. Syst. 64, 546\u2013560 (2022)","DOI":"10.1016\/j.jmsy.2022.08.005"},{"key":"46_CR17","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1016\/j.jmsy.2021.12.013","volume":"62","author":"T Zonta","year":"2022","unstructured":"Zonta, T., da Costa, C.A., Zeiser, F.A., et al.: A predictive maintenance model for optimizing production schedule using deep neural networks. J. Manuf. Syst. 62, 450\u2013462 (2022)","journal-title":"J. Manuf. Syst."},{"key":"46_CR18","doi-asserted-by":"publisher","unstructured":"Ruiz-Sarmiento, J.R., Monroy, J., Moreno, F.A., Galindo, C., Bonelo, J.M., Gonzalez-Jimenez, J.: A predictive model for the maintenance of industrial machinery in the context of Industry 4.0. Eng. Appl. Artif. Intell. 87, 103289 (2020). https:\/\/doi.org\/10.1016\/j.engappai.2019.103289","DOI":"10.1016\/j.engappai.2019.103289"},{"key":"46_CR19","unstructured":"Chakroun, A., Hani, Y., Masmoudi, F., El Mhamedi, A.: Mod\u00e8le pr\u00e9dictif pour l\u2019\u00e9valuation de la sant\u00e9 d\u2019une unit\u00e9 d\u2019assemblage bas\u00e9 sur l\u2019apprentissage automatique dans le contexte de l\u2019industrie 4.0. 1 er Congr\u00e8s de la Soci\u00e9t\u00e9 Fran\u00e7aise d\u2019Automatique, G\u00e9nie Industriel et de Production SAGIP 2023, 7\u20139 Juin 2023, Marseille, France (2023)"}],"container-title":["IFIP Advances in Information and Communication Technology","Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-43666-6_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,13]],"date-time":"2023-09-13T07:22:50Z","timestamp":1694589770000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-43666-6_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031436659","9783031436666"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-43666-6_46","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"type":"print","value":"1868-4238"},{"type":"electronic","value":"1868-422X"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"14 September 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"APMS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"IFIP International Conference on Advances in Production Management Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Trondheim","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Norway","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"apms2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.apms-conference.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}