Abstract: The new, polymer composites consisting of e-glass fiber reinforcement with titanium oxide filler in the double bonded unsaturated polyester resin matrix were made. The glass fiber and titanium oxide reinforcement composites were made in three different fiber lengths (3cm, 5cm, and 7cm), filler content (2 wt%, 4 wt%, and 6 wt%) and fiber content (20 wt%, 40 wt%, and 60 wt%). 27 different compositions were fabricated and a sequence of experiments were carried out to determine tensile strength and impact strength. The vital influencing factors fiber length, fiber content and filler content were chosen as 3 factors in 3 levels of Taguchi’s L9 orthogonal array. The influences of parameters were determined for tensile strength and impact strength by Analysis of variance (ANOVA) and S/N ratio. Using Artificial Neural Network (ANN) an expert system was devised to predict the properties of hybrid reinforcement GFRP composites. The predict models were experimentally proved with the maximum coincidence.
Abstract: Determination of optimal conditions of machining parameters is important to reduce the production cost and achieve the desired surface quality. This paper investigates the influence of cutting parameters on surface roughness and natural frequency in turning of aluminum alloy AA2024. The experiments were performed at the lathe machine using two different cutting tools made of AISI 5140 and carbide cutting insert coated with TiC. Turning experiments were planned by Taguchi method L9 orthogonal array.Three levels for spindle speed, feed rate, depth of cut and tool overhang were chosen as cutting variables. The obtained experimental data has been analyzed using signal to noise ratio and analysis of variance. The main effects have been discussed and percentage contributions of various parameters affecting surface roughness and natural frequency, and optimal cutting conditions have been determined. Finally, optimization of the cutting parameters using Taguchi method was verified by confirmation experiments.
Abstract: A new and cost effective RP-HPLC method was
developed and validated for simultaneous analysis of non steroidal
anti inflammatory dugs Diclofenac sodium (DFS), Flurbiprofen
(FLP) and an opioid analgesic Tramadol (TMD) in advanced drug
delivery systems (Liposome and Microcapsules), marketed brands
and human plasma. Isocratic system was employed for the flow of
mobile phase consisting of 10 mM sodium dihydrogen phosphate
buffer and acetonitrile in molar ratio of 67: 33 with adjusted pH of
3.2. The stationary phase was hypersil ODS column (C18, 250×4.6
mm i.d., 5 μm) with controlled temperature of 30 C°. DFS in
liposomes, microcapsules and marketed drug products was
determined in range of 99.76-99.84%. FLP and TMD in
microcapsules and brands formulation were 99.78 - 99.94 % and
99.80 - 99.82 %, respectively. Single step liquid-liquid extraction
procedure using combination of acetonitrile and trichloroacetic acid
(TCA) as protein precipitating agent was employed. The detection
limits (at S/N ratio 3) of quality control solutions and plasma samples
were 10, 20, and 20 ng/ml for DFS, FLP and TMD, respectively.
The Assay was acceptable in linear dynamic range. All other
validation parameters were found in limits of FDA and ICH method
validation guidelines. The proposed method is sensitive, accurate and
precise and could be applicable for routine analysis in
pharmaceutical industry as well as in human plasma samples for
bioequivalence and pharmacokinetics studies.
Abstract: The fluid flow and the properties of the hydraulic
fluid inside a torque converter are the main topics of interest in this
research. The primary goal is to investigate the applicability of
various viscous fluids inside the torque converter. The Taguchi
optimization method is adopted to analyse the fluid flow in a torque
converter from a design perspective. Calculations are conducted in
maximizing the pressure since greater the pressure, greater the torque
developed. Using the values of the S/N ratios obtained, graphs are
plotted. Computational Fluid Dynamics (CFD) analysis is also
conducted.
Abstract: Machining is an important manufacturing process used to produce a wide variety of metallic parts. Among various machining processes, turning is one of the most important one which is employed to shape cylindrical parts. In turning, the quality of finished product is measured in terms of surface roughness. In turn, surface quality is determined by machining parameters and tool geometry specifications. The main objective of this study is to simultaneously model and optimize machining parameters and tool geometry in order to improve the surface roughness for AISI1045 steel. Several levels of machining parameters and tool geometry specifications are considered as input parameters. The surface roughness is selected as process output measure of performance. A Taguchi approach is employed to gather experimental data. Then, based on signal-to-noise (S/N) ratio, the best sets of cutting parameters and tool geometry specifications have been determined. Using these parameters values, the surface roughness of AISI1045 steel parts may be minimized. Experimental results are provided to illustrate the effectiveness of the proposed approach.
Abstract: Automatic determination of blood in less bright or
noisy capsule endoscopic images is difficult due to low S/N ratio.
Especially it may not be accurate to analyze these images due to the
influence of external disturbance. Therefore, we proposed detection
methods that are not dependent only on color bands. In locating
bleeding regions, the identification of object outlines in the frame and
features of their local colors were taken into consideration. The results
showed that the capability of detecting bleeding was much improved.
Abstract: Moulded parts contribute to more than 70% of
components in products. However, common defects particularly in
plastic injection moulding exist such as: warpage, shrinkage, sink
marks, and weld lines. In this paper Taguchi experimental design
methods are applied to reduce the warpage defect of thin plate
Acrylonitrile Butadiene Styrene (ABS) and are demonstrated in two
levels; namely, orthogonal arrays of Taguchi and the Analysis of
Variance (ANOVA). Eight trials have been run in which the optimal
parameters that can minimize the warpage defect in factorial
experiment are obtained. The results obtained from ANOVA
approach analysis with respect to those derived from MINITAB
illustrate the most significant factors which may cause warpage in
injection moulding process. Moreover, ANOVA approach in
comparison with other approaches like S/N ratio is more accurate and
with the interaction of factors it is possible to achieve higher and the
better outcomes.