Additively manufactured carbon fiber reinforced-polyamide component: a study based on statistical modeling and regression analysis

Abstract This paper presents the experimental assessment of the hardness characteristic of additively manufactured polyamide (PA 6) composite reinforced with carbon micro-fibers. The carbon fiber-reinforced polyamide (CFPA) components were manufactured using the additive manufacturing technique—fused deposition modeling (FDM). The experiments were conducted for testing the hardness of the samples using a Shore-D hardness tester. The novel contributions of the work towards the manufacturing fraternity include selecting a scantly researched material like CFPA, and the elaborative investigation of hardness variation with the alteration of the prime parameters pertaining to FDM. The effect of the print-related parameters, namely, layer height (LH), infill density (ID), and raster orientation (RO) on the hardness of the CFPA component was studied, and the results were analyzed using statistical analysis tool ‘analysis of variance (ANOVA)’. Moreover, a regression model was developed to predict the output response, i.e. hardness for different combinations of the input parameters. Considering an ID of 100% and an RO of 0°, the hardness value of 93.89 at 0.1 mm LH reduced to 88.44 at 0.3 mm LH, depicting a reduction of 5.81%. An increasing trend was observed for hardness with the increase in ID for all the levels of LH and RO. The highest value of hardness (93.89) was achieved at an ID of 100%, with the LH and RO values kept at 0.1 mm and 0°, respectively. The ANOVA suggested that the effect of all three parameters is significant in the study, ID being the most affecting parameter with an effect contribution of 37.88%. The fitness of the adopted model was well justified by the high R-sq value of 0.9618 and significantly low error values in the range of 0.002–0.08.

Authors

Institutions

Publication Details

Journal
Engineering Research Express
Published
2024-09-01
DOI
https://doi.org/10.1088/2631-8695/ad7a52
Citations
2
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.70
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Additively manufactured carbon fiber reinforced-polyamide component: a study based on statistical modeling and regression analysis

Hrishikesh Dutta, Murugan Vellaisamy, Dhinakaran Veeman
2 citations
Engineering Research Express
Manufacturing Process and Optimization
0.70
article

Additively manufactured carbon fiber reinforced-polyamide component: a study based on statistical modeling and regression analysis

Hrishikesh Dutta, Murugan Vellaisamy, Dhinakaran Veeman
article en
2 citations

Abstract

Abstract This paper presents the experimental assessment of the hardness characteristic of additively manufactured polyamide (PA 6) composite reinforced with carbon micro-fibers. The carbon fiber-reinforced polyamide (CFPA) components were manufactured using the additive manufacturing technique—fused deposition modeling (FDM). The experiments were conducted for testing the hardness of the samples using a Shore-D hardness tester. The novel contributions of the work towards the manufacturing fraternity include selecting a scantly researched material like CFPA, and the elaborative investigation of hardness variation with the alteration of the prime parameters pertaining to FDM. The effect of the print-related parameters, namely, layer height (LH), infill density (ID), and raster orientation (RO) on the hardness of the CFPA component was studied, and the results were analyzed using statistical analysis tool ‘analysis of variance (ANOVA)’. Moreover, a regression model was developed to predict the output response, i.e. hardness for different combinations of the input parameters. Considering an ID of 100% and an RO of 0°, the hardness value of 93.89 at 0.1 mm LH reduced to 88.44 at 0.3 mm LH, depicting a reduction of 5.81%. An increasing trend was observed for hardness with the increase in ID for all the levels of LH and RO. The highest value of hardness (93.89) was achieved at an ID of 100%, with the LH and RO values kept at 0.1 mm and 0°, respectively. The ANOVA suggested that the effect of all three parameters is significant in the study, ID being the most affecting parameter with an effect contribution of 37.88%. The fitness of the adopted model was well justified by the high R-sq value of 0.9618 and significantly low error values in the range of 0.002–0.08.

Engineering Research ExpressVol. 6(3)
Chennai Mathematical Institute (IN)
Openalex Percentile: Top 26%
Manufacturing Process and Optimization
0.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.