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This thesis work is explaining about the parameter optimization of chipboard manufacturing process from
eucalyptus and water hyacinth. Chipboard is a panel material manufactured under pressure from particles
of wood and other lingo-cellulosic material with or without addition of additive(s). Eucalyptus and water
hyacinth chips are being reinforced with resin in different contents of 20%, 25% and 30% by applying
120, 140, and 160degree Celsius with pressure of 5, 6, and 7MPa for 2, 3, and 4 minutes duration. It
presents an effective approach for the optimization of process parameters for chipboard production using
Minitab 19 and Taguchi-Grey Relational Analysis method in varying condition. An experimental study
has to be conducted to come out with an optimum outcome. The chipboard production parameters namely
material, resin, temperature, pressure, and press time are optimized with multiple performance
characteristics, such as high modulus of elasticity and modulus of rupture, and low thickness swelling and
water absorption. Analysis of variance (ANOVA), Taguchi and Grey Relational Analysis were carried out
to obtain the significant factors. The response table and response graph for each level of chipboard
production parameters are obtained from the Taguchi method and the optimum levels of manufacturing
parameters are being selected. From the analysis, it was observed that eucalyptus material, pressure, and
resin are consecutively the best significant parameters. From the experimental result, the thickness
swelling at 2hours is 1.38% and 2.31% at 24hours. The value of water absorption of chipboard at 2hours
and 24 hours are 10.32% and 12.45% respectively. The result of MOE is 2962.57MPa and 20.74MPa for
MOR. All experiments are performed at 95% confidence level. A confirmation test was carried out to
validate the optimized results and there have approximate results in S/N ratios from the initial to the
optimal setting.
Key words: resin based composite, eucalyptus and water hyacinth chips, Taguchi method, ANOVA, Grey
Relational Analysis, and Optimization. |
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