Statistical Optimization Transesterification Of Waste Cooking Oil (WCO) Towards High Quality Polyols

Yunos, Siti Nurfadillah (2020) Statistical Optimization Transesterification Of Waste Cooking Oil (WCO) Towards High Quality Polyols. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Over these recent years, awareness of potential in waste cooking oil as a valuable waste product are confirmed when most of the previous research evaluating waste product of cooking oil into wealth product such as biodiesel by different types resources of waste cooking oil such as waste of vegetables oils, rap seeds oil or (RBDPO) Refined Bleached Deodorized Palm Oil. Utilizing of waste cooking oil is starting to develop due to the issue on depletion of the natural resources and waste disposal issue of waste cooking oil where it significantly contributed into environmental pollution and a long-term effect. Furthermore, realizing that the potential of WCO in producing a natural based resources polyol led this research to manipulated the dependent variables in transesterification process to produce a high-quality polyol which can be defined by the presence of the (OH-) hydroxyl group in the molecular structure due to the higher the quantity of hydroxyl group in the molecular structure, the higher the quality of the polyols. However, this study implementing a statistical analysis by using data from previous literature with specifically from transesterification process to introduce OH- group in triglyceride structure of WCO until a valid equation was form. The valid equation was used for manipulating three parameter which is NaOH concentration, Methanol to oil ratio and temperature to get a high-quality polyol. Based on the result from the valid equation, a statistical analysis on two level full factorial design were perform to evaluate the effect of the parameter and the presence of OH- group by (DOE) Design of Expert statistical software. The significant of the modelling simulation from two level factorial design was confirm via the ANOVA testing analysis and since it was significant, it proceeds with the evaluation of interaction among the parameter. Last but not least, this study also conducting an optimization of the parameter through the effect and interaction analysis among the independent variable.

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