Deviation compensation in LPBF series production via statistical predeformation and structural pattern analysis
This article proposes two approaches for a tailored geometrical deviation compensation for Laser-Powder-Bed-Fusion production. The deviation compensation is performed by a non-rigid deformation of the manufacturing geometry in each iteration to reduce the geometrical deviations from the target geome...
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| Veröffentlicht in: | Journal of intelligent manufacturing 2024-08, Vol.35 (6), p.2645-2652 |
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| container_title | Journal of intelligent manufacturing |
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| creator | Lechner, Philipp Hartmann, Christoph Wolf, Daniel Habiba, Abdelrahman |
| description | This article proposes two approaches for a tailored geometrical deviation compensation for Laser-Powder-Bed-Fusion production. The deviation compensation is performed by a non-rigid deformation of the manufacturing geometry in each iteration to reduce the geometrical deviations from the target geometry. It is important for geometric compensation approaches to separate deterministic deviations from random scatter, since compensating scatter can result in unstable behaviour. In order to compensate only deterministic deviations two novel approaches for a local estimation of the scatter are successfully introduced and tested using a hybrid model of a series production cycle. |
| doi_str_mv | 10.1007/s10845-023-02166-5 |
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In order to compensate only deterministic deviations two novel approaches for a local estimation of the scatter are successfully introduced and tested using a hybrid model of a series production cycle.</description><identifier>ISSN: 0956-5515</identifier><identifier>EISSN: 1572-8145</identifier><identifier>DOI: 10.1007/s10845-023-02166-5</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Accuracy ; Additive manufacturing ; Beds (process engineering) ; Business and Management ; Compensation ; Control ; Deviation ; Geometry ; Lasers ; Machine learning ; Machines ; Manufacturing ; Mechatronics ; Metal forming ; Pattern analysis ; Predeformation ; Processes ; Production ; Robotics ; Scattering</subject><ispartof>Journal of intelligent manufacturing, 2024-08, Vol.35 (6), p.2645-2652</ispartof><rights>The Author(s) 2023</rights><rights>The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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In order to compensate only deterministic deviations two novel approaches for a local estimation of the scatter are successfully introduced and tested using a hybrid model of a series production cycle.</description><subject>Accuracy</subject><subject>Additive manufacturing</subject><subject>Beds (process engineering)</subject><subject>Business and Management</subject><subject>Compensation</subject><subject>Control</subject><subject>Deviation</subject><subject>Geometry</subject><subject>Lasers</subject><subject>Machine learning</subject><subject>Machines</subject><subject>Manufacturing</subject><subject>Mechatronics</subject><subject>Metal forming</subject><subject>Pattern analysis</subject><subject>Predeformation</subject><subject>Processes</subject><subject>Production</subject><subject>Robotics</subject><subject>Scattering</subject><issn>0956-5515</issn><issn>1572-8145</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><recordid>eNp9kE9LxDAQxYMouK5-AU8Fz9VJ86fJUVdXhYIe9Bxim0qX3XbNpMJ-e2e3gjcPIcy83xsej7FLDtccoLxBDkaqHApBj2udqyM246oscsOlOmYzsIqWiqtTdoa4AgBrNJ-x4T58dz51Q5_Vw2YbepyGrs-q17tlhiF2AbNtHJqxPiiEZ5iIwtTVfk1SaEI7xM1k9H1DciR4jHvVpxTifu3XO-zwnJ20fo3h4vefs_flw9viKa9eHp8Xt1VeCy5TXgrrZQG6kcpLr8GYBqTm0tLgvfzgykgdWiNapVqjLJRCNAVXlEQ03oOYs6vpLiX_GgMmtxrGSCHQCSi14IWxlqhiouo4IMbQum3sNj7uHAe3L9ZNxToq1h2KdYpMYjIhwf1niH-n_3H9AP6EfQQ</recordid><startdate>20240801</startdate><enddate>20240801</enddate><creator>Lechner, Philipp</creator><creator>Hartmann, Christoph</creator><creator>Wolf, Daniel</creator><creator>Habiba, Abdelrahman</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>K9.</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-7211-730X</orcidid></search><sort><creationdate>20240801</creationdate><title>Deviation compensation in LPBF series production via statistical predeformation and structural pattern analysis</title><author>Lechner, Philipp ; Hartmann, Christoph ; Wolf, Daniel ; Habiba, Abdelrahman</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c314t-739a4206d45a4a6088d0461494a6aa4b15846ef83f55f8590733d215def3daa03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Accuracy</topic><topic>Additive manufacturing</topic><topic>Beds (process engineering)</topic><topic>Business and Management</topic><topic>Compensation</topic><topic>Control</topic><topic>Deviation</topic><topic>Geometry</topic><topic>Lasers</topic><topic>Machine learning</topic><topic>Machines</topic><topic>Manufacturing</topic><topic>Mechatronics</topic><topic>Metal forming</topic><topic>Pattern analysis</topic><topic>Predeformation</topic><topic>Processes</topic><topic>Production</topic><topic>Robotics</topic><topic>Scattering</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lechner, Philipp</creatorcontrib><creatorcontrib>Hartmann, Christoph</creatorcontrib><creatorcontrib>Wolf, Daniel</creatorcontrib><creatorcontrib>Habiba, Abdelrahman</creatorcontrib><collection>Springer Nature OA/Free Journals</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of intelligent manufacturing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lechner, Philipp</au><au>Hartmann, Christoph</au><au>Wolf, Daniel</au><au>Habiba, Abdelrahman</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Deviation compensation in LPBF series production via statistical predeformation and structural pattern analysis</atitle><jtitle>Journal of intelligent manufacturing</jtitle><stitle>J Intell Manuf</stitle><date>2024-08-01</date><risdate>2024</risdate><volume>35</volume><issue>6</issue><spage>2645</spage><epage>2652</epage><pages>2645-2652</pages><issn>0956-5515</issn><eissn>1572-8145</eissn><abstract>This article proposes two approaches for a tailored geometrical deviation compensation for Laser-Powder-Bed-Fusion production. 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| subjects | Accuracy Additive manufacturing Beds (process engineering) Business and Management Compensation Control Deviation Geometry Lasers Machine learning Machines Manufacturing Mechatronics Metal forming Pattern analysis Predeformation Processes Production Robotics Scattering |
| title | Deviation compensation in LPBF series production via statistical predeformation and structural pattern analysis |
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