Optimization and Modelling of Performance Parameters in Turning Aisi 1029 Steel Using Hybridized Shea Butter and Baobab Seed Oil Based Cutting Fluids (Published)
This research Optimization and Modelling of performance parameters in turning AISI 1029 steel using hybridized Shea butter and baobab seed oil cutting fluids used the blends of Shea butter (SB) and Baobab seed oil (BSO) in the ratio of 70%SB: 30%BSO (SBBSOCFI), 60%SB:40%BSO (SBBSOCFII) and 50%SB:50%BSO (SBBSOCFIII as base oils to formulate cutting fluids to be used in turning operation. Cutting speed (CS), depth of cut (DC), feed rate (FR) and cutting fluids (FT) were the machining parameters while temperature and metal removal rate (MRR) were the response variables (performance parameters). The experiment was designed using Taguchi OA Design of experiment (DoE)) taking four (4) factors at three (3) levels. Optimization of the performance parameters was done from Design Expert version 11, ANOVA was used to determine the statistical difference between mean of the variables and Signal-to-Noise ratio (SNR) was used to analyze the results. Besides, mathematical models for the process parameters were developed to predict values of the response variables. From the results obtained SBBSOCFIII produced the least tool-work interface temperature of 39.81OC at cutting conditions 50mpm, 1.00mm and 0.750mm/rev. Similarly, SBBSOCF1 achieved the highest MRR of 69993.7mm3/min at 90mpm, 1.0mm and 0.75mm/rev. It can now be said that these hybrid cutting fluids which are bio oils based cutting fluids that have good prospect for cutting fluids developments and some other industrial applications.
Keywords: cutting fluids, design of experiment, optimization, performance parameters, process parameters, turning operation
Optimized Production of Saponins from Locally Available Plants Using Response Surface Methodology (Published)
Saponins are biodegradable, surface active glycosides, commonly distributed in some indigenous plants were extracted using various solvents such as Methanol, Ethanol and Acetone. The relationship between the response (extract yield) and three independent process variables (mass, time and temperature) were optimized and evaluated using the response surface methodology (RSM) and statistical design. A three factor, five levels central composite design (CCD) were employed to determine the optimum extraction conditions. The fit model to describe the effects of mass (A), time (B), and temperature (C) for the extraction was quadratic. A, B, and C gave significant contribution to saponin (response) yield. The different plots of model adequacy recommended that the predicted values of saponin yield in the model were in conformity with the experimental values. The model developed to obtain the maximum yield of extract had a coefficient of determination (R2) of 0.9997. The model adequacy was further checked using the adjusted (adj-R2) which gave a value of 0.9994. Using the numerical optimization, the optimal extraction conditions of mass (2.895g), temperature (72.83oC) and time (224.46mins), gave yield of 62.29% and mass (4.82g), temperature (52.85oC) and time (152.55mins) gave the yield of 63.22% and for yellow yam and wild yam respectively.
Citation: Emmanuel Ehimhantie Aluola (2021) Optimized Production of Saponins from Locally Available Plants Using Response Surface Methodology, International Journal of Engineering and Advanced Technology Studies, Vol. 9, No.2, pp.53-73
Keywords: Yield, glycosides, optimization