{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T00:55:28Z","timestamp":1760057728725,"version":"build-2065373602"},"reference-count":63,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T00:00:00Z","timestamp":1739923200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMMP"],"abstract":"<jats:p>The current trend in machining with robotic arms involves leveraging Industry 4.0 technologies to propose solutions that reduce path deviation errors. This approach presents significant challenges alongside promising advancements, as well as a substantial increase in the cost of future industrial robotic cells, which is not always amortizable. As an alternative or complementary approach to this trend, methods encouraging the occasional use of Industry 4.0 devices for characterizing the behavior of the actual physical cell, calibration, or adjustment are proposed. One such method, called FlePFaM, predicts flatness errors in face milling operations using robotic arms. This is achieved by estimating tool path deviation errors through the integration of a simple model of the robot arm\u2019s mechanics with the cutting forces vector of the process, thereby optimizing machining conditions. These conditions are determined through prior empirical estimations of mass, stiffness, and damping. The conducted tests enabled the selection of the most favorable combination of variables, such as the robot wrist configuration, the position and orientation of the workpiece, and the predominant milling orientation. This led to the identification of the configuration with the lowest absolute flatness error according to the model\u2019s predictions. The results demonstrated a high degree of similarity\u2014between 97% for the closest case and 57% for the farthest case\u2014between simulated and experimental flatness error values. FlePFaM represents a significant step forward in adopting innovative robotic arm solutions for reliable and efficient production. FlePFaM includes dimensional flatness indicators that provide practical support for decision making.<\/jats:p>","DOI":"10.3390\/jmmp9020066","type":"journal-article","created":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T03:29:53Z","timestamp":1739935793000},"page":"66","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Flatness Error Prediction Model in Face Milling Operations Using 6-DOF Robotic Arms"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3755-1896","authenticated-orcid":false,"given":"Iv\u00e1n","family":"Iglesias","sequence":"first","affiliation":[{"name":"Defense University Center in the Spanish Naval Academy (CUD-ENM), Universidade de Vigo, Plaza de Espa\u00f1a, 36920 Mar\u00edn, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4975-7472","authenticated-orcid":false,"given":"Alberto","family":"S\u00e1nchez-Lite","sequence":"additional","affiliation":[{"name":"School of Industrial Engineering, Universidad de Valladolid, Paseo del Cauce, 59, 47011 Valladolid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8668-4682","authenticated-orcid":false,"given":"Cristina","family":"Gonz\u00e1lez-Gaya","sequence":"additional","affiliation":[{"name":"Department of Construction and Manufacturing Engineering, Universidad Nacional de Educaci\u00f3n a Distancia-UNED, Juan del Rosal, n\u00b0 12, 28040 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8570-4362","authenticated-orcid":false,"given":"Francisco J. G.","family":"Silva","sequence":"additional","affiliation":[{"name":"CIDEM, ISEP\u2014School of Engineering, Polytechnic of Porto, Rua Dr. Ant\u00f3nio Bernardino de Almeida, 431, 4249-015 Porto, Portugal"},{"name":"LAETA, INEGI\u2014Associated Laboratory for Energy, Transports and Aeronautics, Campus FEUP, Rua Dr. Roberto Frias, 400, 4200-465 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,19]]},"reference":[{"key":"ref_1","first-page":"70","article-title":"Intelligent robot trends and predictions for the.net future","volume":"4572","author":"Hall","year":"2001","journal-title":"Intelligent Robots and Computer Vision XX: Algorithms, Techniques, and Active Vision, Proceedings of the Intelligent Systems and Advanced Manufacturing, Boston, MA, United States, 28\u201331 October, 2001"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1683","DOI":"10.1007\/s11431-022-2349-7","article-title":"Robotized manufacturing equipment: A review from the perspective of mechanism topology","volume":"66","author":"Ye","year":"2023","journal-title":"Sci. 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