{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T15:17:16Z","timestamp":1784906236556,"version":"3.55.0"},"reference-count":39,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,4,9]],"date-time":"2020-04-09T00:00:00Z","timestamp":1586390400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Predictive Maintenance (PdM) is a prominent strategy comprising all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the main challenges of PdM is to design and develop an embedded smart system to monitor and predict the health status of the machine. In this work, we use a data-driven approach based on machine learning applied to woodworking industrial machines for a major woodworking Italian corporation. Predicted failures probabilities are calculated through tree-based classification models (Gradient Boosting, Random Forest and Extreme Gradient Boosting) and calculated as the temporal evolution of event data. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime (RUL) of woodworking machines. The effectiveness of the proposed method is showed by testing an independent sample of additional woodworking machines without presenting machine down. The Gradient Boosting model achieved accuracy, recall, and precision of 98.9%, 99.6%, and 99.1%. Our predictive maintenance approach deployed on a Big Data framework allows screening simultaneously multiple connected machines by learning from terabytes of log data. The target prediction provides salient information which can be adopted within the maintenance management practice.<\/jats:p>","DOI":"10.3390\/info11040202","type":"journal-article","created":{"date-parts":[[2020,4,9]],"date-time":"2020-04-09T14:42:03Z","timestamp":1586443323000},"page":"202","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":131,"title":["SOPHIA: An Event-Based IoT and Machine Learning Architecture for Predictive Maintenance in Industry 4.0"],"prefix":"10.3390","volume":"11","author":[{"given":"Matteo","family":"Calabrese","sequence":"first","affiliation":[{"name":"Accenture Digital, ICEG Artificial Intelligence Center of Excellence (CoE), viale Monza 265-259, 20126 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Cimmino","sequence":"additional","affiliation":[{"name":"Accenture Digital, ICEG Artificial Intelligence Center of Excellence (CoE), viale Monza 265-259, 20126 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6323-497X","authenticated-orcid":false,"given":"Francesca","family":"Fiume","sequence":"additional","affiliation":[{"name":"Accenture Digital, ICEG Artificial Intelligence Center of Excellence (CoE), viale Monza 265-259, 20126 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martina","family":"Manfrin","sequence":"additional","affiliation":[{"name":"Accenture Digital, ICEG Artificial Intelligence Center of Excellence (CoE), viale Monza 265-259, 20126 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1707-0147","authenticated-orcid":false,"given":"Luca","family":"Romeo","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria dell\u2019Informazione, Universit\u00e0 Politecnica delle Marche, viale Brecce Bianche 12, 60131 Ancona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8916-1262","authenticated-orcid":false,"given":"Silvia","family":"Ceccacci","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria di Ingegneria Industriale e Scienze Matematiche, Universit\u00e0 Politecnica delle Marche, viale Brecce Bianche 12, 60131 Ancona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5523-7174","authenticated-orcid":false,"given":"Marina","family":"Paolanti","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria dell\u2019Informazione, Universit\u00e0 Politecnica delle Marche, viale Brecce Bianche 12, 60131 Ancona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giuseppe","family":"Toscano","sequence":"additional","affiliation":[{"name":"BIESSE GROUP SpA, viale della Meccanica 16, 61122 Pesaro, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanni","family":"Ciandrini","sequence":"additional","affiliation":[{"name":"BIESSE GROUP SpA, viale della Meccanica 16, 61122 Pesaro, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alberto","family":"Carrotta","sequence":"additional","affiliation":[{"name":"BIESSE GROUP SpA, viale della Meccanica 16, 61122 Pesaro, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maura","family":"Mengoni","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria di Ingegneria Industriale e Scienze Matematiche, Universit\u00e0 Politecnica delle Marche, viale Brecce Bianche 12, 60131 Ancona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8893-9244","authenticated-orcid":false,"given":"Emanuele","family":"Frontoni","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria dell\u2019Informazione, Universit\u00e0 Politecnica delle Marche, viale Brecce Bianche 12, 60131 Ancona, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dimos","family":"Kapetis","sequence":"additional","affiliation":[{"name":"Accenture Digital, ICEG Artificial Intelligence Center of Excellence (CoE), viale Monza 265-259, 20126 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1007\/s10951-010-0222-9","article-title":"A survey of problems, solution techniques, and future challenges in scheduling semiconductor manufacturing operations","volume":"14","author":"Fowler","year":"2011","journal-title":"J. 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