Multi-Objective Optimization of Mustard Oil Biodiesel production parameters using Grey relational analysis with principal component analysis and Taguchi method

Abstract

Biodiesel is a substitute fuel to fossil diesel or customary diesel. It can be delivered from various sources, for instance, straight vegetable oil, animal oil/fats, tallow and waste cooking oil. The way toward changing over oils into biodiesels is Transeaterification. Mustard is the regular name for various species in the Brassica family. The types of which a great many people know is yellow mustard, alluded to as white mustard in Europe, and is developed essentially for fixing mustard seed. Thus, it doesn't have as high oil content as the other generally known Indian mustard alluded reciprocally in commerce as brown or oriental mustard. This present mustard's organic name is Brassica juncea. Juncea varieties are developed for edible leaves or greens or for condiment mustard, and have been and are progressively developed as an oilseed crop. Mustard yields around 181.7 liters of biodiesel per acre.An attempt is made to optimize the process parameters of biodiesel produced using Indian Mustard oil (Brassica juncea). The identification of optimal processing parameters is fundamental in the transformation of Biodiesel from different feedstocks by prudence of the basic impact of such parameters on overall production cost and quality. Production of mustard seed oil ethyl esters (MSOEE) through alkali- catalyzed transesterification with ethanol utilizing potassium hydroxide as an catalyst. The impact of the process parameters, for example, catalyst concentration, ethanol to oil molar ratio, reaction temperature, reaction duration was researched in order to discover the optimal conditions for the transesterification process. This experimentation methodically builds up a hybrid optimization method for various quality attributes by integrating the Taguchi parameter design, grey relational analysis, and principal component analysis. To exhibit the efficiency and validity of the proposed hybrid optimization method in controlling all influential Biodiesel processing parameters amid its production are considered. To maximize the yield, minimize the viscosity; the ideal mix of various process parameters is resolved. Single step group transesterification process is done on Mustard oil with alcohols, within the sight of base catalyst potassium hydroxide (KOH) and methanol as solvent, to get biodiesel. The PCA is used to figure the weight of the responses while the optimization is done. Along these lines, the impacts of each of these input parameters are analyzed and exhibited. These results give the information that how to control the parameters keeping in mind the end goal to get the best yield and review viscosity as low. Yield of biodiesel and viscosity are optimized with consideration of performance characteristics namely reaction temperature, reaction time, Catalyst Concentration & Alcohol %. A grey relational grade obtained from the grey relational analysis is utilized to understand the biodiesel production with the various performance characteristics. Furthermore, the analysis of variance (ANOVA) is to be applied to distinguish the most significant factor. Finally, confirmation tests are performed to make a comparison between the experimental results and developed model. These values of this parameters are observed that optimal values for the input parameters for biodiesel production are Reaction temperature 600C, Reaction time 20 min , Catalyst concentration 1.5 % wt, Alcohol % 10 the yield of Mustard oil biodiesel if increased to 97.12% and viscosity 4.10 cSt. are the desired optimal combination where the GRG value is maximum (0.9998) which are the best combination of this analysis. In this way, the Hybrid Integration of Taguchi Parametric Design, Gray Relational Analysis, and Principal Component Analysis Optimization ends up being extraordinary compared to other strategy for accomplishing parameters that suffice to the future needs of Biodiesel generation.