TY - JOUR
T1 - Optimizing drilling parameters for minimizing delamination in polypropylene-date palm fiber bio-composite materials
AU - Nassar, Mahmoud M.A.
AU - Alzebdeh, Khalid I.
AU - Alsafy, Mahmoud M.M.
AU - Piya, Sujan
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive licence to The Brazilian Society of Mechanical Sciences and Engineering.
PY - 2023/11
Y1 - 2023/11
N2 - This study examines the ability to machine a type of bio-composite material made up of polypropylene reinforced with date palm fibers. The focus is on how drilling affects the delamination of the material at the entry and exit points of the hole. The impact of three drilling parameters (spindle speed, drill size, and feed rate) on the quality of the holes, as measured by the delamination factor, is analyzed. The research was conducted experimentally based on the design of experiment method, and data were analyzed using statistical techniques such as analysis of variance (ANOVA), response surface modeling (RSM), fuzzy logic (FL), and artificial neural network (ANN). The design expert software was also used to identify the optimal values for the machining parameters that minimize delamination. The results indicate that delamination caused by drilling is primarily influenced by drill bit diameter, with a threefold greater impact than feed rate. This bio-composite material may have potential for use in industrial applications where joining parts is necessary for product design and assembly.
AB - This study examines the ability to machine a type of bio-composite material made up of polypropylene reinforced with date palm fibers. The focus is on how drilling affects the delamination of the material at the entry and exit points of the hole. The impact of three drilling parameters (spindle speed, drill size, and feed rate) on the quality of the holes, as measured by the delamination factor, is analyzed. The research was conducted experimentally based on the design of experiment method, and data were analyzed using statistical techniques such as analysis of variance (ANOVA), response surface modeling (RSM), fuzzy logic (FL), and artificial neural network (ANN). The design expert software was also used to identify the optimal values for the machining parameters that minimize delamination. The results indicate that delamination caused by drilling is primarily influenced by drill bit diameter, with a threefold greater impact than feed rate. This bio-composite material may have potential for use in industrial applications where joining parts is necessary for product design and assembly.
KW - Artificial neural network
KW - Bio-composites
KW - Delamination
KW - Drilling
KW - Fuzzy logic
KW - Response surface methodology
UR - http://www.scopus.com/inward/record.url?scp=85175691897&partnerID=8YFLogxK
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UR - https://www.mendeley.com/catalogue/057c160e-f66c-3625-8842-c206d5a194c3/
U2 - 10.1007/s40430-023-04528-9
DO - 10.1007/s40430-023-04528-9
M3 - Article
AN - SCOPUS:85175691897
SN - 1678-5878
VL - 45
JO - Journal of the Brazilian Society of Mechanical Sciences and Engineering
JF - Journal of the Brazilian Society of Mechanical Sciences and Engineering
IS - 11
M1 - 609
ER -