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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">powder</journal-id><journal-title-group><journal-title xml:lang="ru">Известия вузов. Порошковая металлургия и функциональные покрытия</journal-title><trans-title-group xml:lang="en"><trans-title>Powder Metallurgy аnd Functional Coatings (Izvestiya Vuzov. Poroshkovaya Metallurgiya i Funktsional'nye Pokrytiya)</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1997-308X</issn><issn pub-type="epub">2412-8767</issn><publisher><publisher-name>НИТУ "МИСИС"</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.17073/1997-308X-2026-2-96-106</article-id><article-id custom-type="elpub" pub-id-type="custom">powder-1128</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Материалы и покрытия, получаемые методами аддитивных технологий</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>Materials and coatings fabricated using the additive manufacturing technologies</subject></subj-group></article-categories><title-group><article-title>Многопараметрическая модель шероховатости поверхности сплава AlSi10Mg при селективном лазерном сплавлении на основе методов поверхности отклика</article-title><trans-title-group xml:lang="en"><trans-title>Multivariable model of the surface roughness of LPBF-manufactured AlSi10Mg alloy based on response surface methodology</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0001-5663-2758</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Коробов</surname><given-names>К. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Korobov</surname><given-names>K. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Константин Сергеевич Коробов – сотрудник лаборатории Цент­ра аэрокосмических материалов и технологий Московского авиационного института (национального исследовательского университета), аспирант Сколковского института науки и технологий</p><p>Россия, 121205, г. Москва, Большой бульвар, 30, стр. 1</p><p>Россия, 125993, г. Москва, Волоколамское шоссе, 4</p></bio><bio xml:lang="en"><p>Konstantin S. Korobov – Employee at the Laboratory of the Center for Aerospase Materials and Technologies, Moscow Aviation Institute (National Research University), Postgraduate Student of the Skolkovo Institute of Science and Technology</p><p>1 Bld., 30 Bolshoy Boulevard, Moscow 121205, Russia</p><p>4 Volokolamskoe Highway, Moscow 125993, Russia</p></bio><email xlink:type="simple">barlosh@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Сколковский институт науки и технологий; Московский авиационный институт (национальный исследовательский университет)</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Skolkovo Institute of Science and Technology; Moscow Aviation Institute (National Research University)</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>05</day><month>07</month><year>2026</year></pub-date><volume>20</volume><issue>2</issue><fpage>96</fpage><lpage>106</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; НИТУ "МИСИС", 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">НИТУ "МИСИС"</copyright-holder><copyright-holder xml:lang="en">НИТУ "МИСИС"</copyright-holder><license xlink:href="https://powder.misis.ru/jour/about/submissions#copyrightNotice" xlink:type="simple"><license-p>https://powder.misis.ru/jour/about/submissions#copyrightNotice</license-p></license></permissions><self-uri xlink:href="https://powder.misis.ru/jour/article/view/1128">https://powder.misis.ru/jour/article/view/1128</self-uri><abstract><p>Представлены результаты экспериментального и математического исследований влияния технологических параметров процесса селективного лазерного сплавления (СЛС) на формирование шероховатости поверхности изделий из алюминиевого сплава AlSi10Mg. Проведен полный факторный эксперимент, включающий 60 комбинаций основных факторов: мощность лазера, скорость сканирования и шаг штриховки. На основе полученных данных по шероховатости поверхности построена многопараметрическая модель поверхности отклика 3-го порядка, отражающая нелинейные зависимости и взаимодействия факторов. Полученная модель объясняет ~86 % вариаций экспериментальных данных и имеет среднюю погрешность прогнозирования порядка ±0,9 мкм по параметру Sa и ±0,2 мкм по параметру Ra . Определены параметры процесса, обеспечивающие минимальное значение средней арифметической шероховатости Sa ≈ 5 мкм (Ra ≈ 2 мкм): мощность лазера 400 Вт, скорость сканирования 938 мм/с, шаг между треками 80 мкм. Установлено, что наибольшее влияние на формирование шероховатости поверхности оказывают мощность лазера, шаг штриховки и их суперпозиция. Разработанная многопараметрическая модель может быть использована для прогнозирования качества поверхности и выбора оптимальных технологических режимов при СЛС-производстве изделий из алюминиевых сплавов.</p></abstract><trans-abstract xml:lang="en"><p>This study presents an experimental and mathematical investigations of the effects of Laser Powder Bed Fusion (LPBF) process parameters on the surface roughness of AlSi10Mg alloy parts. A full-factorial experiment comprising 60 combinations of the main process parameters – laser power, scanning speed, and hatch spacing – was conducted. A third-order multivariable response surface model was developed from the measured roughness data to describe nonlinear relationships and interactions among the process parameters. The model accounted for approximately 86 % of the total variance in the experimental data and yielded mean prediction errors of approximately 0.9 µm for Sa and ± 0.2 µm for Ra . The minimum roughness values, Sa ≈ 5 µm  and Ra ≈ 2 µm, were obtained at a laser power of 400 W, a scanning speed of 938 mm/s, and a hatch spacing of 80 µm. Laser power, hatch spacing, and their interaction had the greatest effect on the resulting surface roughness. The developed model can be used to predict surface quality and select optimal process parameters for the LPBF manufacturing of aluminum alloy components.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>селективное лазерное сплавление</kwd><kwd>AlSi10Mg</kwd><kwd>поверхность отклика</kwd><kwd>шероховатость</kwd><kwd>Sa</kwd><kwd>планирование эксперимента</kwd><kwd>регрессионное моделирование</kwd><kwd>оптимизация параметров</kwd></kwd-group><kwd-group xml:lang="en"><kwd>laser powder bed fusion</kwd><kwd>AlSi10Mg</kwd><kwd>response surface</kwd><kwd>roughness</kwd><kwd>Sa</kwd><kwd>design of experiments</kwd><kwd>regression modeling</kwd><kwd>process parameter optimization</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Pal S., Drstvenšek I., Brajlih T. Physical behaviors of materials in selective laser melting process. In: DAAAM International Scientific Book 2018. Vienna: DAAAM International Publishing, 2018. P. 239–256. https://doi.org/10.2507/daaam.scibook.2018.21</mixed-citation><mixed-citation xml:lang="en">Pal S., Drstvenšek I., Brajlih T. Physical behaviors of materials in selective laser melting process. In: DAAAM International Scientific Book 2018. Vienna: DAAAM International Publishing, 2018. P. 239–256. https://doi.org/10.2507/daaam.scibook.2018.21</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Kiass E.M., Zarbane K., Beidouri Z. Optimizing AlSi10Mg part quality aspects in laser powder bed fusion: A literature review. Lasers in Manufacturing and Mate­rials Processing. 2024;11(4):905–930. https://doi.org/10.1007/s40516-024-00267-4</mixed-citation><mixed-citation xml:lang="en">Kiass E.M., Zarbane K., Beidouri Z. Optimizing AlSi10Mg part quality aspects in laser powder bed fusion: A literature review. Lasers in Manufacturing and Mate­rials Processing. 2024;11(4):905–930. https://doi.org/10.1007/s40516-024-00267-4</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Subramaniyan A.K., Reddy A.S., Mathias S., Shrivastava A., Raghupatruni P. Influence of post-processing techniques on the microstructure, properties and surface integrity of Al–Si–Mg alloy processed by laser powder bed fusion technique. Surface and Coatings Technology. 2021;425: 127679. https://doi.org/10.1016/j.surfcoat.2021.127679</mixed-citation><mixed-citation xml:lang="en">Subramaniyan A.K., Reddy A.S., Mathias S., Shrivastava A., Raghupatruni P. Influence of post-processing techniques on the microstructure, properties and surface integrity of Al–Si–Mg alloy processed by laser powder bed fusion technique. Surface and Coatings Technology. 2021;425:127679. https://doi.org/10.1016/j.surfcoat.2021.127679</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Majeed A., Ahmed A., Salam A., Sheikh M.Z. Surface quality improvement by parameters analysis, optimization and heat treatment of AlSi10Mg parts manufactured by SLM additive manufacturing. International Journal of Lightweight Materials and Manufacture. 2019; 1;2(4):288–295. https://doi.org/10.1016/j.ijlmm.2019.08.001</mixed-citation><mixed-citation xml:lang="en">Majeed A., Ahmed A., Salam A., Sheikh M.Z. Surface quality improvement by parameters analysis, optimization and heat treatment of AlSi10Mg parts manufactured by SLM additive manufacturing. International Journal of Lightweight Materials and Manufacture. 2019;1;2(4): 288–295. https://doi.org/10.1016/j.ijlmm.2019.08.001</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Басов A.A., Коробов К.С., Лесневский Л.Н., Николаев И.А., Рипецкий А.В. Анализ шероховатости сплава AlSi10Mg, полученного методом СЛС для использования в теплообменных элементах косми­чес­ких аппаратов. Тепловые процессы в технике. 2025; 17(3):111–122.</mixed-citation><mixed-citation xml:lang="en">Basov A.A., Korobov K.S., Lesnevsky L.N., Nikolaev I.A., Ripetsky A.V. Controlled surface roughness of AlSi10Mg alloy produced by LPBF for aerspace heat exchange elements. Thermal Processes in Engineering. 2025;17(3):111–122. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">ГОСТ 2789-73. Шероховатость поверхности. Пара­метры и характеристики. М.: Издательство стандартов, 2018.</mixed-citation><mixed-citation xml:lang="en">GOST 2789-73. Surface roughness. Parameters and cha­racteristics. Moscow: Izdatel’stvo standartov, 2018. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Gao C., Tang H., Zhang S., Ma Z., Bi Y., Rao J.H. Process optimization for up-facing surface finish of AlSi10Mg alloy produced by laser powder bed fusion. Metals. 2022;29;12(12):2053. https://doi.org/10.3390/met12122053</mixed-citation><mixed-citation xml:lang="en">Gao C., Tang H., Zhang S., Ma Z., Bi Y., Rao J.H. Process optimization for up-facing surface finish of AlSi10Mg alloy produced by laser powder bed fusion. Metals. 2022;29;12(12):2053. https://doi.org/10.3390/met12122053</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Boschetto A., Bottini L., Pilone D. Metallurgical defects and roughness investigation in the laser powder bed fusion multi-scanning strategy of AlSi10Mg parts. Metals. 2024;14(6):711. https://doi.org/10.3390/met14060711</mixed-citation><mixed-citation xml:lang="en">Boschetto A., Bottini L., Pilone D. Metallurgical defects and roughness investigation in the laser powder bed fusion multi-scanning strategy of AlSi10Mg parts. Metals. 2024;14(6):711. https://doi.org/10.3390/met14060711</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Vilanova M., Escribano-García R., Guraya T., San Sebastian M. Optimizing laser powder bed fusion parameters for IN-738LC by response surface method. Materials. 2020;13(21):4879. https://doi.org/10.3390/ma13214879</mixed-citation><mixed-citation xml:lang="en">Vilanova M., Escribano-García R., Guraya T., San Sebastian M. Optimizing laser powder bed fusion parameters for IN-738LC by response surface method. Materials. 2020;13(21):4879. https://doi.org/10.3390/ma13214879</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Kyarimov R.R., Statnik E.S., Sadykova I.A., Frantsuzov A.A., Salimon A.I., Korsunsky A.M. Factorial-experi­mental investigation of LPBF regimes for VZh159 nickel superalloy grain structure and structural strength optimization. Frontiers in Materials. 2024;11:1470651. https://doi.org/10.3389/fmats.2024.1470651</mixed-citation><mixed-citation xml:lang="en">Kyarimov R.R., Statnik E.S., Sadykova I.A., Frantsuzov A.A., Salimon A.I., Korsunsky A.M. Factorial-experimental investigation of LPBF regimes for VZh159 nickel superalloy grain structure and structural strength optimization. Frontiers in Materials. 2024;11:1470651. https://doi.org/10.3389/fmats.2024.1470651</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Yang T., Liu T., Liao W., Wei h., Zhang C., Chen X., Zhang K. Effect of processing parameters on overhan­ging surface roughness during laser powder bed fusion of AlSi10Mg. Journal of Manufacturing Processes. 2021;61:440–453. https://doi.org/10.1016/j.jmapro.2020.11.030</mixed-citation><mixed-citation xml:lang="en">Yang T., Liu T., Liao W., Wei h., Zhang C., Chen X., Zhang K. Effect of processing parameters on overhanging surface roughness during laser powder bed fusion of AlSi10Mg. Journal of Manufacturing Processes. 2021;61:440–453. https://doi.org/10.1016/j.jmapro.2020.11.030</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Коробов К.С., Рипецкий А.В., Николаев И.А., Лесневс­кий Л.Н. Статистические подходы к анализу шероховатости вертикальных поверхностей образцов, изготовленных по технологии СЛС из порошка AlSi10Mg. Проблемы машиностроения и надежности машин. 2025;(2):32–41. https://doi.org/10.31857/S0235711925020049</mixed-citation><mixed-citation xml:lang="en">Korobov K.S., Ripetsky A.V., Nikolaev I.A., Lesnevs­ky L.N. Statistical approaches to analysis of the roughness of vertical surfaces of samples manufactured by the SLM technology from AlSi10Mg powder. Journal of Machi­nery Manufacture and Reliability. 2025;54(2):150–158. https://doi.org/10.1134/S1052618824701802</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Harris C.R., Millman K.J., van der Walt S.J., Gommers R., Virtanen P., Cournapeau D., Wieser E., Taylor J., Berg S., Smith N.J., Kern R., Picus M., Hoyer S., van Kerk­wijk M.H., Brett M., Haldane A., del Río J.F., Wiebe M., Peterson P., Gérard-Marchant P., Sheppard K., Reddy T., Weckesser W., Abbasi H., Gohlke C., Oliphant T.E. Array programming with NumPy. Nature. 2020;585:357–362. https://doi.org/10.1038/s41586-020-2649-2</mixed-citation><mixed-citation xml:lang="en">Harris C.R., Millman K.J., van der Walt S.J., Gommers R., Virtanen P., Cournapeau D., Wieser E., Taylor J., Berg S., Smith N.J., Kern R., Picus M., Hoyer S., van Kerk­wijk M.H., Brett M., Haldane A., del Río J.F., Wiebe M., Peterson P., Gérard-Marchant P., Sheppard K., Reddy T., Weckesser W., Abbasi H., Gohlke C., Oliphant T.E. Array programming with NumPy. Nature. 2020;585:357–362. https://doi.org/10.1038/s41586-020-2649-2</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Majeed A., Zhang Y., Lv J., Peng T., Atta Z., Ahmed A. Investigation of T4 and T6 heat treatment influences on relative density and porosity of AlSi10Mg alloy components manufactured by SLM. Computers &amp; Industrial Engineering. 2020;139:106194. https://doi.org/10.1016/j.cie.2019.106194</mixed-citation><mixed-citation xml:lang="en">Majeed A., Zhang Y., Lv J., Peng T., Atta Z., Ahmed A. Investigation of T4 and T6 heat treatment influences on relative density and porosity of AlSi10Mg alloy components manufactured by SLM. Computers &amp; Industrial Engineering. 2020;139:106194. https://doi.org/10.1016/j.cie.2019.106194</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Shubham P., Sharma A., Vishwakarma P.N., Phanden R.K. Predicting strength of selective laser melting 3D printed AlSi10Mg alloy parts by machine learning models. In: Proceedings of the 2021 8th International Conference on Signal Processing and Integrated Networks (SPIN). Noida, India, 2021. P. 745–749. https://doi.org/10.1109/SPIN52536.2021.9566142</mixed-citation><mixed-citation xml:lang="en">Shubham P., Sharma A., Vishwakarma P.N., Phanden R.K. Predicting strength of selective laser melting 3D printed AlSi10Mg alloy parts by machine learning models. In: Proceedings of the 2021 8th International Conference on Signal Processing and Integrated Networks (SPIN). Noida, India, 2021. P. 745–749. https://doi.org/10.1109/SPIN52536.2021.9566142</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">ISO 4287-1:1984. Шероховатость поверхности. Терминология. Часть 1: Поверхность и ее параметры.</mixed-citation><mixed-citation xml:lang="en">ISO 4287-1:1984. Surface roughness. Terminology. Part 1: Surface and its parameters. (In Russ.).</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Hastie T. Ridge regularization: An essential concept in data science. Technometrics. 2020;62(4):426–433. https://doi.org/10.1080/00401706.2020.1791959</mixed-citation><mixed-citation xml:lang="en">Hastie T. Ridge regularization: An essential concept in data science. Technometrics. 2020;62(4):426–433. https://doi.org/10.1080/00401706.2020.1791959</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Tougui I., Jilbab A., El Mhamdi J. Impact of the choice of cross-validation techniques on the results of machine learning-based diagnostic applications. Healthcare Informatics Research. 2021;27(3):189–199. https://doi.org/10.4258/hir.2021.27.3.189</mixed-citation><mixed-citation xml:lang="en">Tougui I., Jilbab A., El Mhamdi J. Impact of the choice of cross-validation techniques on the results of machine learning-based diagnostic applications. Healthcare Informatics Research. 2021;27(3):189–199. https://doi.org/10.4258/hir.2021.27.3.189</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Zhao R., Shmatok A., Fischer R., Deng P., Bel­­hadi M.E.A., Hamasha S., Prorok B.C. Employing spatial and amp­litude discriminators to partition and analyze LPBF surface features. Precision Engineering. 2022;78:90–101. https://doi.org/10.1016/j.precisioneng.2022.07.014</mixed-citation><mixed-citation xml:lang="en">Zhao R., Shmatok A., Fischer R., Deng P., Bel­­hadi M.E.A., Hamasha S., Prorok B.C. Employing spatial and amp­litude discriminators to partition and analyze LPBF surface features. Precision Engineering. 2022;78:90–101. https://doi.org/10.1016/j.precisioneng.2022.07.014</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Molinari A., Ancellotti S., Fontanari V., Iacob E., Luchin V., Zappini G., Benedetti M. Effect of process parameters on the surface microgeometry of a Ti6Al4v alloy manufactured by laser powder bed fusion: 3D vs. 2D cha­racterization. Metals. 2022;12(1):106. https://doi.org/10.3390/met12010106</mixed-citation><mixed-citation xml:lang="en">Molinari A., Ancellotti S., Fontanari V., Iacob E., Luchin V., Zappini G., Benedetti M. Effect of process parameters on the surface microgeometry of a Ti6Al4v alloy manufactured by laser powder bed fusion: 3D vs. 2D characterization. Metals. 2022;12(1):106. https://doi.org/10.3390/met12010106</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Xiao B., Zhou C., Liu B., Cai W., Xue Q., Jin L., Wang Y., Liu C., Zhang Q., Pan h. The effects of hatch spacing and stripe offset on the surface morphology and microstructure of biomedical 316L stainless steel formed by laser powder bed fusion. Journal of Materials Research and Techno­logy. 2025;36:10183–10198. https://doi.org/10.1016/j.jmrt.2025.05.211</mixed-citation><mixed-citation xml:lang="en">Xiao B., Zhou C., Liu B., Cai W., Xue Q., Jin L., Wang Y., Liu C., Zhang Q., Pan h. The effects of hatch spacing and stripe offset on the surface morphology and microstructure of biomedical 316L stainless steel formed by laser powder bed fusion. Journal of Materials Research and Techno­logy. 2025;36:10183–10198. https://doi.org/10.1016/j.jmrt.2025.05.211</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang H., Vallabh C.K., Zhao X. Influence of spattering on in-process layer surface roughness during laser powder bed fusion. Journal of Manufacturing Processes. 2023;104:289–306. https://doi.org/10.1016/j.jmapro.2023.08.058</mixed-citation><mixed-citation xml:lang="en">Zhang H., Vallabh C.K., Zhao X. Influence of spattering on in-process layer surface roughness during laser powder bed fusion. Journal of Manufacturing Processes. 2023;104:289–306. https://doi.org/10.1016/j.jmapro.2023.08.058</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
