Optimization of input parameters during drilling of glass fiber reinforced polymer composite using grey relational analysis
Glass fiber-reinforced polymer (GFRP) composites are extensively used in many sectors because of their high strength, low weight, and resistance to corrosion properties. Drilling operations are needed to make holes for the joining of the components. Various defects were reported during the drilling,...
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| Veröffentlicht in: | International journal on interactive design and manufacturing 2024-08, Vol.18 (6), p.4075-4091 |
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| creator | Pathak, Shashi Ranjan Malik, Anup Mali, Harlal Singh |
| description | Glass fiber-reinforced polymer (GFRP) composites are extensively used in many sectors because of their high strength, low weight, and resistance to corrosion properties. Drilling operations are needed to make holes for the joining of the components. Various defects were reported during the drilling, and the authors in this study tried to provide an approach to minimize the drilling defects. Selection of the optimum level of the input parameters can reduce defects generated during drilling. This study used grey relational analysis to optimize input parameters during glass fiber-reinforced composite drilling. Three tools (T1, T2, T3) with point angles (118°, 135°, 140°), feed rate in mm/min (10, 20, 30), and spindle speed in rpm (1000, 2000, 3000) were taken as input parameters. Taguchi L
27
orthogonal arrays were selected for the three factors at three levels. Machining force (F
m
), surface roughness (R
a
), peel-up delamination factor (DF1), push-out delamination factor (DF2), hole size error, and circularity error were taken as output responses. Drilling GFRP composite by considering these input parameters combined with all these output responses using grey relational analysis was not explored before. The effect of input parameters on individual output response was analyzed using Taguchi and analysis of variance. Feed rate influenced machining force the most (65.34%), tool geometry influenced surface roughness the most (38.32%), and spindle speed influenced the push-out delamination factor the most (18.11%). SEM analysis was done to explain the aftereffects of drilling.
Graphical abstract |
| doi_str_mv | 10.1007/s12008-024-01900-4 |
| format | Article |
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27
orthogonal arrays were selected for the three factors at three levels. Machining force (F
m
), surface roughness (R
a
), peel-up delamination factor (DF1), push-out delamination factor (DF2), hole size error, and circularity error were taken as output responses. Drilling GFRP composite by considering these input parameters combined with all these output responses using grey relational analysis was not explored before. The effect of input parameters on individual output response was analyzed using Taguchi and analysis of variance. Feed rate influenced machining force the most (65.34%), tool geometry influenced surface roughness the most (38.32%), and spindle speed influenced the push-out delamination factor the most (18.11%). SEM analysis was done to explain the aftereffects of drilling.
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27
orthogonal arrays were selected for the three factors at three levels. Machining force (F
m
), surface roughness (R
a
), peel-up delamination factor (DF1), push-out delamination factor (DF2), hole size error, and circularity error were taken as output responses. Drilling GFRP composite by considering these input parameters combined with all these output responses using grey relational analysis was not explored before. The effect of input parameters on individual output response was analyzed using Taguchi and analysis of variance. Feed rate influenced machining force the most (65.34%), tool geometry influenced surface roughness the most (38.32%), and spindle speed influenced the push-out delamination factor the most (18.11%). SEM analysis was done to explain the aftereffects of drilling.
Graphical abstract</description><subject>CAE) and Design</subject><subject>Computer-Aided Engineering (CAD</subject><subject>Content analysis</subject><subject>Corrosion resistance</subject><subject>Corrosion tests</subject><subject>Defects</subject><subject>Delamination</subject><subject>Density</subject><subject>Drilling</subject><subject>Electronics and Microelectronics</subject><subject>Engineering</subject><subject>Engineering Design</subject><subject>Error analysis</subject><subject>Experiments</subject><subject>Feed rate</subject><subject>Fiber composites</subject><subject>Fiber reinforced polymers</subject><subject>Glass fiber reinforced plastics</subject><subject>Heat</subject><subject>Hole size</subject><subject>Industrial Design</subject><subject>Instrumentation</subject><subject>Literature reviews</subject><subject>Machining</subject><subject>Mechanical Engineering</subject><subject>Optimization</subject><subject>Original Article</subject><subject>Orthogonal arrays</subject><subject>Parameters</subject><subject>Performance evaluation</subject><subject>Polymer matrix composites</subject><subject>Polymers</subject><subject>Software</subject><subject>Spindles</subject><subject>Surface roughness</subject><issn>1955-2513</issn><issn>1955-2505</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kMtOwzAQRSMEEqXwA6wssQ6MX2myRBUvCakbWFupM65cJbGxk0Xg53EbBDs2M6PRvfM4WXZN4ZYCrO4iZQBlDkzkQCuAXJxkC1pJmTMJ8vS3pvw8u4hxD1CUUMIi-9r4wXb2sx6s64kzxPZ-HIivQ93hgCGSZgy235Em2LY9FEmza-sYibFbDCSg7Y0LGhviXTt1qaVd5120A5IxHhy7gFPStccddUvqFKZo42V2Zuo24tVPXmbvjw9v6-f8dfP0sr5_zXV6asg5pyAKXVI0VJRCGqqBSk2NwK0ot1JKJotCVgLLVcE411pIbgqGDSIFBL7Mbua5PriPEeOg9m4M6YioOFRVJYRcsaRis0oHF2NAo3ywXR0mRUEdIKsZskqQ1RGyEsnEZ1P0B0oY_kb_4_oGI7GBWg</recordid><startdate>20240801</startdate><enddate>20240801</enddate><creator>Pathak, Shashi Ranjan</creator><creator>Malik, Anup</creator><creator>Mali, Harlal Singh</creator><general>Springer Paris</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-0382-4692</orcidid></search><sort><creationdate>20240801</creationdate><title>Optimization of input parameters during drilling of glass fiber reinforced polymer composite using grey relational analysis</title><author>Pathak, Shashi Ranjan ; Malik, Anup ; Mali, Harlal Singh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c200t-331046c81ef14845f1c015c1f4eb48b5552566594e876233cc453f62edee10e03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>CAE) and Design</topic><topic>Computer-Aided Engineering (CAD</topic><topic>Content analysis</topic><topic>Corrosion resistance</topic><topic>Corrosion tests</topic><topic>Defects</topic><topic>Delamination</topic><topic>Density</topic><topic>Drilling</topic><topic>Electronics and Microelectronics</topic><topic>Engineering</topic><topic>Engineering Design</topic><topic>Error analysis</topic><topic>Experiments</topic><topic>Feed rate</topic><topic>Fiber composites</topic><topic>Fiber reinforced polymers</topic><topic>Glass fiber reinforced plastics</topic><topic>Heat</topic><topic>Hole size</topic><topic>Industrial Design</topic><topic>Instrumentation</topic><topic>Literature reviews</topic><topic>Machining</topic><topic>Mechanical Engineering</topic><topic>Optimization</topic><topic>Original Article</topic><topic>Orthogonal arrays</topic><topic>Parameters</topic><topic>Performance evaluation</topic><topic>Polymer matrix composites</topic><topic>Polymers</topic><topic>Software</topic><topic>Spindles</topic><topic>Surface roughness</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pathak, Shashi Ranjan</creatorcontrib><creatorcontrib>Malik, Anup</creatorcontrib><creatorcontrib>Mali, Harlal Singh</creatorcontrib><collection>CrossRef</collection><jtitle>International journal on interactive design and manufacturing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pathak, Shashi Ranjan</au><au>Malik, Anup</au><au>Mali, Harlal Singh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimization of input parameters during drilling of glass fiber reinforced polymer composite using grey relational analysis</atitle><jtitle>International journal on interactive design and manufacturing</jtitle><stitle>Int J Interact Des Manuf</stitle><date>2024-08-01</date><risdate>2024</risdate><volume>18</volume><issue>6</issue><spage>4075</spage><epage>4091</epage><pages>4075-4091</pages><issn>1955-2513</issn><eissn>1955-2505</eissn><abstract>Glass fiber-reinforced polymer (GFRP) composites are extensively used in many sectors because of their high strength, low weight, and resistance to corrosion properties. Drilling operations are needed to make holes for the joining of the components. Various defects were reported during the drilling, and the authors in this study tried to provide an approach to minimize the drilling defects. Selection of the optimum level of the input parameters can reduce defects generated during drilling. This study used grey relational analysis to optimize input parameters during glass fiber-reinforced composite drilling. Three tools (T1, T2, T3) with point angles (118°, 135°, 140°), feed rate in mm/min (10, 20, 30), and spindle speed in rpm (1000, 2000, 3000) were taken as input parameters. Taguchi L
27
orthogonal arrays were selected for the three factors at three levels. Machining force (F
m
), surface roughness (R
a
), peel-up delamination factor (DF1), push-out delamination factor (DF2), hole size error, and circularity error were taken as output responses. Drilling GFRP composite by considering these input parameters combined with all these output responses using grey relational analysis was not explored before. The effect of input parameters on individual output response was analyzed using Taguchi and analysis of variance. Feed rate influenced machining force the most (65.34%), tool geometry influenced surface roughness the most (38.32%), and spindle speed influenced the push-out delamination factor the most (18.11%). SEM analysis was done to explain the aftereffects of drilling.
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| subjects | CAE) and Design Computer-Aided Engineering (CAD Content analysis Corrosion resistance Corrosion tests Defects Delamination Density Drilling Electronics and Microelectronics Engineering Engineering Design Error analysis Experiments Feed rate Fiber composites Fiber reinforced polymers Glass fiber reinforced plastics Heat Hole size Industrial Design Instrumentation Literature reviews Machining Mechanical Engineering Optimization Original Article Orthogonal arrays Parameters Performance evaluation Polymer matrix composites Polymers Software Spindles Surface roughness |
| title | Optimization of input parameters during drilling of glass fiber reinforced polymer composite using grey relational analysis |
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