{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T07:00:07Z","timestamp":1776322807476,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,8,26]],"date-time":"2022-08-26T00:00:00Z","timestamp":1661472000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Axioms"],"abstract":"<jats:p>The purpose of this research is to investigate different milling parameters for optimization to achieve the maximum rate of material removal with the minimum tool wear and surface roughness. In this study, a tool wear factor is specified to investigate tool wear parameters and the amount of material removed during machining, simultaneously. The second output parameter is surface roughness. The DOE technique is used to design the experiments and applied to the milling machine. The practical data is used to develop different mathematical models. In addition, a single-objective genetic algorithm (GA) is applied to numerate the optimal hyperparameters of the proposed adaptive network-based fuzzy inference system (ANFIS) to achieve the best possible efficiency. Afterwards, the multi-objective GA is employed to extract the optimum cutting parameters to reach the specified tool wear and the least surface roughness. The proposed method is developed under MATLAB using the practically extracted dataset and neural network. The optimization results revealed that optimum values for feed rate, cutting speed, and depth of cut vary from 252.6 to 256.9 (m\/min), 0.1005 to 0.1431 (mm\/rev tooth), and from 1.2735 to 1.3108 (mm), respectively.<\/jats:p>","DOI":"10.3390\/axioms11090430","type":"journal-article","created":{"date-parts":[[2022,8,26]],"date-time":"2022-08-26T02:04:32Z","timestamp":1661479472000},"page":"430","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Machine Learning-Based Modelling and Meta-Heuristic-Based Optimization of Specific Tool Wear and Surface Roughness in the Milling Process"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2974-1801","authenticated-orcid":false,"given":"Siamak","family":"Pedrammehr","sequence":"first","affiliation":[{"name":"Faculty of Design, Tabriz Islamic Art University, Tabriz 5164736931, Iran"},{"name":"Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds, VIC 3216, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mahsa","family":"Hejazian","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical Engineering, University of Tabriz, Tabriz 5166616471, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1839-029X","authenticated-orcid":false,"given":"Mohammad Reza","family":"Chalak Qazani","sequence":"additional","affiliation":[{"name":"Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds, VIC 3216, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hadi","family":"Parvaz","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical and Mechatronics Engineering, Shahrood University of Technology, Shahrood 36199-95161, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sajjad","family":"Pakzad","sequence":"additional","affiliation":[{"name":"Faculty of Design, Tabriz Islamic Art University, Tabriz 5164736931, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9229-3482","authenticated-orcid":false,"given":"Mir Mohammad","family":"Ettefagh","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical Engineering, University of Tabriz, Tabriz 5166616471, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4710-909X","authenticated-orcid":false,"given":"Adeel H.","family":"Suhail","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Middle East College, PB 79, Al Rusayl, Muscat PC 124, Oman"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"735","DOI":"10.3139\/120.111378","article-title":"A new hybrid Harris hawks-Nelder-Mead optimization algorithm for solving design and manufacturing problems","volume":"61","author":"Yildiz","year":"2019","journal-title":"Mater. 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