The Effect of Lubricant and Nanofiller Additives on Drilling Temperature in GFRP Composites

Glass fiber-reinforced polymer (GFRP) composites are highly susceptible to thermal damage during machining, which can compromise their structural integrity and final quality. This study examines the efficacy of graphene and wax additives in reducing drilling temperatures in GFRP composites. Nine unique samples were manufactured with varying weight percentages of wax (0%, 1%, 2%) and graphene (0%, 0.25%, 2%). Drilling experiments were performed on a CNC milling center under a range of cutting parameters, with temperature monitoring carried out using an infrared thermal camera. A hierarchical cubic response surface model was employed to analyze thermal behavior. The results indicate that cutting speed is the dominant factor, accounting for 67.28% of temperature generation. The formulation containing 2% wax and 0% graphene achieved the lowest average drilling temperature (64.64 °C), underscoring wax’s superior performance as both a lubricant and heat sink. Although graphene alone slightly elevated median temperatures, it substantially reduced thermal variability. The optimal condition for minimizing thermal damage was identified as 2% wax combined with a high cutting speed (200 mm/min), providing actionable insights for industrial process optimization.

Authors

Institutions

Publication Details

Journal
Journal of Composites Science
Published
2025-10-12
DOI
https://doi.org/10.3390/jcs9100558
Citations
2
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
1.43

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Effect of Lubricant and Nanofiller Additives on Drilling Temperature in GFRP Composites

Mohamed Slamani, Jean-François Châtelain, Siwar Jammel
2 citations
Journal of Composites Science
Advanced machining processes and optimization
1.43
article

The Effect of Lubricant and Nanofiller Additives on Drilling Temperature in GFRP Composites

Mohamed Slamani, Jean-François Châtelain, Siwar Jammel
article en
2 citations

Abstract

Glass fiber-reinforced polymer (GFRP) composites are highly susceptible to thermal damage during machining, which can compromise their structural integrity and final quality. This study examines the efficacy of graphene and wax additives in reducing drilling temperatures in GFRP composites. Nine unique samples were manufactured with varying weight percentages of wax (0%, 1%, 2%) and graphene (0%, 0.25%, 2%). Drilling experiments were performed on a CNC milling center under a range of cutting parameters, with temperature monitoring carried out using an infrared thermal camera. A hierarchical cubic response surface model was employed to analyze thermal behavior. The results indicate that cutting speed is the dominant factor, accounting for 67.28% of temperature generation. The formulation containing 2% wax and 0% graphene achieved the lowest average drilling temperature (64.64 °C), underscoring wax’s superior performance as both a lubricant and heat sink. Although graphene alone slightly elevated median temperatures, it substantially reduced thermal variability. The optimal condition for minimizing thermal damage was identified as 2% wax combined with a high cutting speed (200 mm/min), providing actionable insights for industrial process optimization.

Journal of Composites ScienceVol. 9(10)
University Mohamed Boudiaf of M'sila (DZ), École de Technologie Supérieure (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 17%
Advanced machining processes and optimization
1.43
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.