Non-destructive evaluation of melt-extruded part quality using in situ data
Purpose This study aims to collect real-time, in situ data from polymer melt extrusion (ME) 3D printing and use only the collected data to non-destructively identify printed parts that contain defects. Design/methodology/approach A set of sensors was created to collect real-time, in situ data from p...
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| Veröffentlicht in: | Rapid prototyping journal 2024-01, Vol.30 (1), p.124-133 |
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| creator | Jilludimudi, Veera Harsha Vardhan Zhou, Daniel Rubstov, Eric Gonzalez, Alexander Daknis, Will Gunn, Erin Prawel, David |
| description | Purpose
This study aims to collect real-time, in situ data from polymer melt extrusion (ME) 3D printing and use only the collected data to non-destructively identify printed parts that contain defects.
Design/methodology/approach
A set of sensors was created to collect real-time, in situ data from polymer ME 3D printing. A variance analysis was completed to identify an “acceptable” range for filament diameter on a popular desktop 3D printer. These data were used as the basis of a quality evaluation process to non-destructively identify spatial regions of printed parts in multi-part builds that contain defects.
Findings
Anomalous parts were correctly identified non-destructively using only in situ collected data.
Research limitations/implications
This methodology was developed by varying the filament diameter, one of the most common reasons for print failure in ME. Numerous other printing parameters are known to create faults in melt extruded parts, and this methodology can be extended to analyze other parameters.
Originality/value
To the best of the authors’ knowledge, this is the first report of a non-destructive evaluation of 3D-printed part quality using only in situ data in ME. The value is in improving part quality and reliability in ME, thereby reducing 3D printing part errors, plastic waste and the associated cost of time and material. |
| doi_str_mv | 10.1108/RPJ-04-2023-0122 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_emera</sourceid><recordid>TN_cdi_emerald_primary_10_1108_RPJ-04-2023-0122</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2907034570</sourcerecordid><originalsourceid>FETCH-LOGICAL-c264t-60b3aa834577468b20db6e838b336e6624584b2c6c69fc8a4c61b6d213a34e973</originalsourceid><addsrcrecordid>eNptkEtLAzEUhYMoWKt7lwHXsTePSdKlFN9FRXQdMjMZmTKdafMo9t-boW4EV_fCPefcw4fQJYVrSkHP3t-eCAjCgHEClLEjNKGq0ERJBcd550VBWCHkKToLYQVZIgqYoOeXoSe1C9GnKrY7h93OdsnGdujx0OC16yJx3_lauxpvrI94m2zXxj1Ooe2_cNvj0MaEaxvtOTppbBfcxe-cos-724_FA1m-3j8ubpakYlJEIqHk1mouCqWE1CWDupROc11yLp2UuZgWJatkJedNpa2oJC1lzSi3XLi54lN0dcjd-GGbcnezGpLv80vD5qBgTIasgoOq8kMI3jVm49u19XtDwYzITEZmQJgRmRmRZcvsYHFr521X_-f4A5n_AEVEbAc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2907034570</pqid></control><display><type>article</type><title>Non-destructive evaluation of melt-extruded part quality using in situ data</title><source>Standard: Emerald eJournal Premier Collection</source><creator>Jilludimudi, Veera Harsha Vardhan ; Zhou, Daniel ; Rubstov, Eric ; Gonzalez, Alexander ; Daknis, Will ; Gunn, Erin ; Prawel, David</creator><creatorcontrib>Jilludimudi, Veera Harsha Vardhan ; Zhou, Daniel ; Rubstov, Eric ; Gonzalez, Alexander ; Daknis, Will ; Gunn, Erin ; Prawel, David</creatorcontrib><description>Purpose
This study aims to collect real-time, in situ data from polymer melt extrusion (ME) 3D printing and use only the collected data to non-destructively identify printed parts that contain defects.
Design/methodology/approach
A set of sensors was created to collect real-time, in situ data from polymer ME 3D printing. A variance analysis was completed to identify an “acceptable” range for filament diameter on a popular desktop 3D printer. These data were used as the basis of a quality evaluation process to non-destructively identify spatial regions of printed parts in multi-part builds that contain defects.
Findings
Anomalous parts were correctly identified non-destructively using only in situ collected data.
Research limitations/implications
This methodology was developed by varying the filament diameter, one of the most common reasons for print failure in ME. Numerous other printing parameters are known to create faults in melt extruded parts, and this methodology can be extended to analyze other parameters.
Originality/value
To the best of the authors’ knowledge, this is the first report of a non-destructive evaluation of 3D-printed part quality using only in situ data in ME. The value is in improving part quality and reliability in ME, thereby reducing 3D printing part errors, plastic waste and the associated cost of time and material.</description><identifier>ISSN: 1355-2546</identifier><identifier>EISSN: 1758-7670</identifier><identifier>EISSN: 1355-2546</identifier><identifier>DOI: 10.1108/RPJ-04-2023-0122</identifier><language>eng</language><publisher>Bradford: Emerald Publishing Limited</publisher><subject>3-D printers ; Data acquisition systems ; Data collection ; Data transmission ; Defects ; Design defects ; Electromagnetism ; Extrusion ; Humidity ; Manufacturing ; Methodology ; Nondestructive testing ; Parameters ; Polymers ; Printers (data processing) ; Process controls ; Quality assessment ; Rapid prototyping ; Real time ; Sensors ; Three dimensional printing ; Variance analysis</subject><ispartof>Rapid prototyping journal, 2024-01, Vol.30 (1), p.124-133</ispartof><rights>Emerald Publishing Limited</rights><rights>Emerald Publishing Limited.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c264t-60b3aa834577468b20db6e838b336e6624584b2c6c69fc8a4c61b6d213a34e973</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/RPJ-04-2023-0122/full/html$$EHTML$$P50$$Gemerald$$H</linktohtml><link.rule.ids>314,776,780,21674,27901,27902,53219</link.rule.ids></links><search><creatorcontrib>Jilludimudi, Veera Harsha Vardhan</creatorcontrib><creatorcontrib>Zhou, Daniel</creatorcontrib><creatorcontrib>Rubstov, Eric</creatorcontrib><creatorcontrib>Gonzalez, Alexander</creatorcontrib><creatorcontrib>Daknis, Will</creatorcontrib><creatorcontrib>Gunn, Erin</creatorcontrib><creatorcontrib>Prawel, David</creatorcontrib><title>Non-destructive evaluation of melt-extruded part quality using in situ data</title><title>Rapid prototyping journal</title><description>Purpose
This study aims to collect real-time, in situ data from polymer melt extrusion (ME) 3D printing and use only the collected data to non-destructively identify printed parts that contain defects.
Design/methodology/approach
A set of sensors was created to collect real-time, in situ data from polymer ME 3D printing. A variance analysis was completed to identify an “acceptable” range for filament diameter on a popular desktop 3D printer. These data were used as the basis of a quality evaluation process to non-destructively identify spatial regions of printed parts in multi-part builds that contain defects.
Findings
Anomalous parts were correctly identified non-destructively using only in situ collected data.
Research limitations/implications
This methodology was developed by varying the filament diameter, one of the most common reasons for print failure in ME. Numerous other printing parameters are known to create faults in melt extruded parts, and this methodology can be extended to analyze other parameters.
Originality/value
To the best of the authors’ knowledge, this is the first report of a non-destructive evaluation of 3D-printed part quality using only in situ data in ME. The value is in improving part quality and reliability in ME, thereby reducing 3D printing part errors, plastic waste and the associated cost of time and material.</description><subject>3-D printers</subject><subject>Data acquisition systems</subject><subject>Data collection</subject><subject>Data transmission</subject><subject>Defects</subject><subject>Design defects</subject><subject>Electromagnetism</subject><subject>Extrusion</subject><subject>Humidity</subject><subject>Manufacturing</subject><subject>Methodology</subject><subject>Nondestructive testing</subject><subject>Parameters</subject><subject>Polymers</subject><subject>Printers (data processing)</subject><subject>Process controls</subject><subject>Quality assessment</subject><subject>Rapid prototyping</subject><subject>Real time</subject><subject>Sensors</subject><subject>Three dimensional printing</subject><subject>Variance analysis</subject><issn>1355-2546</issn><issn>1758-7670</issn><issn>1355-2546</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNptkEtLAzEUhYMoWKt7lwHXsTePSdKlFN9FRXQdMjMZmTKdafMo9t-boW4EV_fCPefcw4fQJYVrSkHP3t-eCAjCgHEClLEjNKGq0ERJBcd550VBWCHkKToLYQVZIgqYoOeXoSe1C9GnKrY7h93OdsnGdujx0OC16yJx3_lauxpvrI94m2zXxj1Ooe2_cNvj0MaEaxvtOTppbBfcxe-cos-724_FA1m-3j8ubpakYlJEIqHk1mouCqWE1CWDupROc11yLp2UuZgWJatkJedNpa2oJC1lzSi3XLi54lN0dcjd-GGbcnezGpLv80vD5qBgTIasgoOq8kMI3jVm49u19XtDwYzITEZmQJgRmRmRZcvsYHFr521X_-f4A5n_AEVEbAc</recordid><startdate>20240102</startdate><enddate>20240102</enddate><creator>Jilludimudi, Veera Harsha Vardhan</creator><creator>Zhou, Daniel</creator><creator>Rubstov, Eric</creator><creator>Gonzalez, Alexander</creator><creator>Daknis, Will</creator><creator>Gunn, Erin</creator><creator>Prawel, David</creator><general>Emerald Publishing Limited</general><general>Emerald Group Publishing Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>7TB</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>F~G</scope><scope>HCIFZ</scope><scope>K6~</scope><scope>L.-</scope><scope>L.0</scope><scope>L6V</scope><scope>M0C</scope><scope>M7S</scope><scope>PQBIZ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>S0W</scope></search><sort><creationdate>20240102</creationdate><title>Non-destructive evaluation of melt-extruded part quality using in situ data</title><author>Jilludimudi, Veera Harsha Vardhan ; Zhou, Daniel ; Rubstov, Eric ; Gonzalez, Alexander ; Daknis, Will ; Gunn, Erin ; Prawel, David</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c264t-60b3aa834577468b20db6e838b336e6624584b2c6c69fc8a4c61b6d213a34e973</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>3-D printers</topic><topic>Data acquisition systems</topic><topic>Data collection</topic><topic>Data transmission</topic><topic>Defects</topic><topic>Design defects</topic><topic>Electromagnetism</topic><topic>Extrusion</topic><topic>Humidity</topic><topic>Manufacturing</topic><topic>Methodology</topic><topic>Nondestructive testing</topic><topic>Parameters</topic><topic>Polymers</topic><topic>Printers (data processing)</topic><topic>Process controls</topic><topic>Quality assessment</topic><topic>Rapid prototyping</topic><topic>Real time</topic><topic>Sensors</topic><topic>Three dimensional printing</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jilludimudi, Veera Harsha Vardhan</creatorcontrib><creatorcontrib>Zhou, Daniel</creatorcontrib><creatorcontrib>Rubstov, Eric</creatorcontrib><creatorcontrib>Gonzalez, Alexander</creatorcontrib><creatorcontrib>Daknis, Will</creatorcontrib><creatorcontrib>Gunn, Erin</creatorcontrib><creatorcontrib>Prawel, David</creatorcontrib><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM Global</collection><collection>Engineering Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>DELNET Engineering & Technology Collection</collection><jtitle>Rapid prototyping journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jilludimudi, Veera Harsha Vardhan</au><au>Zhou, Daniel</au><au>Rubstov, Eric</au><au>Gonzalez, Alexander</au><au>Daknis, Will</au><au>Gunn, Erin</au><au>Prawel, David</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Non-destructive evaluation of melt-extruded part quality using in situ data</atitle><jtitle>Rapid prototyping journal</jtitle><date>2024-01-02</date><risdate>2024</risdate><volume>30</volume><issue>1</issue><spage>124</spage><epage>133</epage><pages>124-133</pages><issn>1355-2546</issn><eissn>1758-7670</eissn><eissn>1355-2546</eissn><abstract>Purpose
This study aims to collect real-time, in situ data from polymer melt extrusion (ME) 3D printing and use only the collected data to non-destructively identify printed parts that contain defects.
Design/methodology/approach
A set of sensors was created to collect real-time, in situ data from polymer ME 3D printing. A variance analysis was completed to identify an “acceptable” range for filament diameter on a popular desktop 3D printer. These data were used as the basis of a quality evaluation process to non-destructively identify spatial regions of printed parts in multi-part builds that contain defects.
Findings
Anomalous parts were correctly identified non-destructively using only in situ collected data.
Research limitations/implications
This methodology was developed by varying the filament diameter, one of the most common reasons for print failure in ME. Numerous other printing parameters are known to create faults in melt extruded parts, and this methodology can be extended to analyze other parameters.
Originality/value
To the best of the authors’ knowledge, this is the first report of a non-destructive evaluation of 3D-printed part quality using only in situ data in ME. The value is in improving part quality and reliability in ME, thereby reducing 3D printing part errors, plastic waste and the associated cost of time and material.</abstract><cop>Bradford</cop><pub>Emerald Publishing Limited</pub><doi>10.1108/RPJ-04-2023-0122</doi><tpages>10</tpages></addata></record> |
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| ispartof | Rapid prototyping journal, 2024-01, Vol.30 (1), p.124-133 |
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| subjects | 3-D printers Data acquisition systems Data collection Data transmission Defects Design defects Electromagnetism Extrusion Humidity Manufacturing Methodology Nondestructive testing Parameters Polymers Printers (data processing) Process controls Quality assessment Rapid prototyping Real time Sensors Three dimensional printing Variance analysis |
| title | Non-destructive evaluation of melt-extruded part quality using in situ data |
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