Multi objectives optimization of cutting parameters in machining cellulose based hybrid composites
Cellulose based hybrid (CBH) composites is gaining popularity in the growing green communities. People are progressively inventing greener and sustainable alternatives. With extensive studies and increasing number of applications for future advancement, the need for accurate and reliable guide in ma...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2014
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| Online Access: | http://eprints.utem.edu.my/id/eprint/14845/1/Multi%20Objectives%20Optimization%20Of%20Cutting%20Parameters%20In%20Machining%20Gellulose%20Based%20Hybrid%20Composites%2024pages.pdf http://eprints.utem.edu.my/id/eprint/14845/2/Multi%20objectives%20optimization%20of%20cutting%20parameters%20in%20machining%20cellulose%20based%20hybrid%20composites.pdf |
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| Summary: | Cellulose based hybrid (CBH) composites is gaining popularity in the growing green communities. People are progressively inventing greener and sustainable alternatives. With extensive studies and increasing number of applications for future advancement, the need for accurate and reliable guide in machining this type of composites has increased enormously. Smooth and defect free machined surface are always the ultimate objectives. The present work, deals with the study of machining parameters (i.e. spindle speed, feed rate and depth of cut) and its effects against machining performance (i.e. surface roughness, delamination and cutting forces) in due to establish an optimized setup of machining parameters in achieving multi objectives machining performance. CBH composites that is made in combination of jute (bast fiber) and glass fiber embedded in polyester resins were fabricated using Vacuum Infusion Process (VIP). Mechanical properties test demonstrates that jute-glass hybrid laminate has higher specific modulus as compared to glass and jute laminates alone. Through Response Surface Methodology (RSM), Box-Behnken Design (BBD) is chose as the design of experiment and subsequently 17 runs are devised. Next, mathematical model for each response is developed. Adequacy of models is analyzed statistically using analysis of variance (ANOVA) in determination of significant input variables and possible interactions. Various diagnostic plots are evaluated to check the model effectiveness. Multi objectives optimization is performed through numerical optimization and predicted results are validated. The agreement between experimental and selected solution are found to be strong in between 89% and 96%, thus validating the solution as optimal run condition. The findings suggest that feed rate is the main factor affecting surface roughness and delamination factor, whereas depth of cut, feed rate and followed by spindle speed are found to have significant effects on the cutting forces. Increase of feed rate and/ or depth of cut will increase the cutting forces. When this condition is coupled with low spindle speed, the cutting forces increase substantially. Similar to synthetic FRP, high cutting forces is proven to have proportional effects on the surface roughness and delamination. Therefore it is recommended to couple high spindle speed with low feed rate and depth of cut to minimize cutting forces and subsequently improving the machining surface quality. |
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