Optimization using taguchi robust technique Research Papers (original) (raw)

Membrane distillation is a developing thermally
driven membrane separation technology used for water
desalination. The air gap membrane distillation (AGMD)
is one of the important basic configurations for applying
this technology. The performance of AGMD system is
experimentally investigated at different operating and design
variables, including feed temperature, feed flow rate, coolant
temperature, coolant flow rate, and air gap width. Taguchi
method and applied regression were employed to model and
optimize the performance of the AGMD system, by obtaining
the best parameters combination based on three different
levels of significant variables. Analysis of variance was performed
to determine the effect of each factor on the system’s
performance. A regression model was subsequently generated
for calculating the performance of the AGMD system.
Feed temperature and the air gap width are the most effective
parameters on the performance of AGMD system. The
measured and calculated optimal fluxes were found to be
76.0457 and 74.5916 kg/m2 hr; respectively. The percentage
difference between model calculations and the experimental
results at optimum conditions is 1.95%.

The influence of Approach angle of face milling cutter is investigated by conducting experiments with
different approach angles in order to evaluate the effect of approach angle on productivity. The cartridges
are designed, modeled and manufactured for having different approach angles when mounted on face
milling cutter. The cutting forces, surface finish are measured in order to evaluate the performance of the
cutter. The experiments are conducted on En31 steel material and optimized by using Taguchi technique.
Taguchi method, a powerful tool to design optimization for quality, is used to find the optimal cutting
parameters for milling operations. An orthogonal array signal to noise (S/N) ratio and analysis of variance
(ANOVA) are employed to investigate the cutting characteristics of EN 31 steel using tungsten carbide
cutting tools. In this paper, not only the optimal cutting parameters for face milling operation are obtained,
but also main cutting parameters that affect the cutting performance in machining operations can be found.

The present work makes an attempt to analyzevarious parameters of end milling in order to minimize the surface roughness and to maximize the material removal rate (MRR) of Al 2024-SiC composite. Al2024-SiC is generally used in manufacturing high strength parts of aircrafts and machinery, fuselage structural wing tension members, wing skins, engine parts subjected to high temperaturesincluding gears and bolts and for security vans where strength is critical. The quality of the machined surface, i.e., surface finish and texture affects the function, appearance and reliability of a product. On the other hand higher production rate is possible when MRR is maximum. But higher MRR leads to lower surface finish, so a tradeoff between Surface finish and MRR is needed. In this work, the optimal selection of process parameters have been done in order to obtain optimized response output parameters namely surface roughness and MRR by using Taguchi's technique. And ANOVA analysis. In machining operations, achieving desired surface quality is a bit difficult as these quality structures are influenced by the effect of process parameters and their interactions. However, the amounts of influence of the process parameters vary for different processes. Therefore, optimization of surface roughness and MRR is a multi-factor and multi-objective optimization which is carried out successfully by the help of Taguchi optimization technique.

In today's competitive world, the industries should have production systems which are capable of versatility, high production rate, precision and ability to produce highly finished goods. Due to this the value of input machining parameters responsible for the desired surface finish & material removal rate becomes critical. Present paper presents a study on parametric optimization of the End Milling machining of Al2024-SiC metal matrix composite on quality characteristics namely surface roughness and material removal rate using Taguchi Technique. The end milling parameters selected is speed, feed, depth of cut and number of flutes. How these parameters influence the response outputs like MRR and surface roughness is analysed with the help of Taguchi Technique and ANOVA. At the same time various statistical plots are generated with the help of MiniTab software like residual plots, contour plots and surface plots. Twenty seven experimental runs based on design of experiments and L27 orthogonal array of Taguchi method are performed and data so obtained is used to subsequently applied to determine an optimal end milling parameter combination. Finally, confirmation tests carried out at optimum cutting conditions to make a comparison between the experimental results and developed model. The predicted results are found to be closer to experimental results by confirmation test. After this the results of Taguchi optimization are compared with the statistical plots found to be in close conformity with each other.

Membrane distillation (MD) is a developing thermally driven membrane desalination technology that has been applied in four different basic configurations. In membrane distillation, a hot, saline feed stream is passed over a hydrophobic membrane. The temperature difference between the two sides of the membrane leads to a vapour pressure difference that causes water vapour to permeate through the membrane pores, and then condensed on the cold side of the membrane. The hydrophobicity of the membrane prevents the liquid from passing through the pores, while the water vapour is allowed to pass through. The technique offers the attractiveness of operation at atmospheric pressure and low temperature (40– 90oC), and has the theoretical ability to achieve 100% salt rejection. Thus, low-grade energy like solar and waste energy can be used for desalination.
In this work, an experimental investigation of the performance of Air Gap Membrane Distillation (AGMD) system was performed for seawater and laboratory prepared salt feed water solutions. The influences of system operating parameters such as feed temperature, feed flow rate, coolant temperature, coolant flow rate and air gap width on permeate flux were studied. The effects of membrane pore size as well as the concentration of feed solution on permeate flux were also investigated. The performance of the AGMD unit was statistically optimized using design of experiment (DOE) and Taguchi technique. Furthermore, theoretical model describing heat and mass transfer analysis in AGMD was developed and discussed in detail.
The permeate flux was found to increase with increasing feed temperature and feed flow rate. However, it decreased with increasing air gap width and coolant temperature. The system performance tends to increase marginally with increasing coolant flow rate. The system performance is mostly dominated by the effect of both feed temperature and air gap width. Feed flow rate and coolant temperature have relatively considerable effect on flux. Increasing the membrane pore size from PTFE 0.22µm to PTFE 0.45µm leads to about 10% increment in flux production. While increasing the feed concentration from 0.075g/L to 60g/L lead to about 11% drop in permeate flux. The tested double-stage AGMD design was capable of achieving a maximum permeate flux of 128.46kg/m2hr, which is almost twice that of single stage unit, under the same experimental conditions.
In general, the theoretical model results were found to be in good agreement with the experimental data as the maximum deviation of model results was within 15%. The model was also used to predict thermal efficiency and temperature polarization of the AGMD system.
Regarding system optimization using Taguchi methodology, the developed model proved to be in good agreement with the experimental data with a maximum deviation of about 10%. According to Taguchi orthogonal arrays, the experimental and model optimum system performance was found to be 76.0457 kg/m2h, and 74.5916 kg/m2h respectively. The conditions for the optimum performance are 80oC feed temperature, 5 L/min feed flow rate, air gap width of 3mm and coolant temperature of 20oC.

This paper studies the effect of process parameters like melt temperature, mold temperature,packing
pressure, sprue diameter and gate diameter on product quality responses like fill time of cavity and
volumetric shrinkage of electrical switch board.In the first part an experimental methodology was
developed using DOE (Design of experiment)technique. Taguchi method was used to design an orthogonal
array of five factors having three levels. Second part is developing FEM simulation using MFA software
provided by Autodesk Company. Main results are based on S/N ratio and ANOVA analysis. It is found that
most critical parameter in this study is sprue diameter and less effective parameter is packing pressure.
Model equations are also developed in this study.

Recovery of fine coals from coal preparation tailings and recycle of processing water are of both economic and environmental incentives, not only preserving natural resources but also reducing environmental consequences of discharging large volume of tailings. Recent developments in the use of various gravity equipments in fine-coal beneficiation have been discussed and their relative merits have been compared. In this study, the application of multiple linear regressions and Taguchi experimental design method for modeling and optimizing of some operations variables of Multi-Gravity Separator (MGS) and Falcon concentrator for lignite coal cleaning was discussed. The variables considered in this study include the pulp solid ratio, drum speed, tilt angle, shaking amplitude, wash water rate, feed rate for MGS, and the gravity force, solids rate, flow rate, water pressure for Falcon concentrator. The positive and negative effects of variables and the interaction between variables ash content and recovery of clean coal were determined. The predicted values were found to be in good agreement with experimental values (R2 values of 0.807 and 0.944 for ash content and combustible recovery of clean coal, respectively) for MGS. However, the match of predicted values with the actual data points indicates a poor fit (R2 value of 0.577 and 0.399 for ash content and combustible recovery values, respectively) of the equation for Falcon concentrator.

- by Eyüp SABAH and +1
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- Clean Coal Technologies, Modelling, Taguchi Methods, Optimization method using Taguchi Method