In the last issue, I deliberated on the concerns related to the review of a manuscript received for publication in the The IUP Journal of Mechanical Engineering, and I wish the reviewers will not do a perfunctory job and clear every paper sent to them as ‘good’ for publication without going through it. The authors, on the other side, shall be more meticulous in preparing their manuscripts and read them carefully before submitting. There may be a strong urge to publish—for a variety of reasons like promotion being linked to the number of publications by the policy makers—nonetheless one needs to ethically and accurately present the work done. The tendency to make claims without giving a proper justification or basis for drawing the conclusion or corroborating the conclusion with the findings, is observably increasing. For example, a claim is made that parameter x improves by y%, but the whole paper does not give details as to how y% is obtained. It is left to the reader’s ingenuity to discover it. There are also instances where it is impossible to infer the claims of the authors from the results or statements given in the paper.

This issue has three papers on the use of theory of design of experiments. Taguchi method is a powerful design of experiments tool, which provides a simple, efficient and systematic approach to determine optimal parameters where responses are influenced by multi-variables. Compared to the conventional approach of experimentation, this method decreases the repetition of experiments required for modeling the response function. The results are then corroborated experimentally with focused experiments. These papers reaffirm that Taguchi methodology is an effective tool for predicting the number of experiments and reducing the time and cost of experimentation and that ANN is an effective method for predicting the parameters with accuracy and simplicity.

The first paper, “Performance Evaluation of PCD 1500 Grade Insert on Turning A356 Alloy with 10% Reinforcement of SiC Particles”, by Muthukrishnan and Ramanujam, is an application of Taguchi approach to optimize machining parameters. Three machining parameters at three levels are considered as control factors (cutting speed, feed rate and depth of cut) by the authors. The findings from ANOVA table, like cutting speed has more influence on surface roughness, and the combined effect of cutting speed and feed has more influence on power consumed, are no surprises. The authors have claimed experimental verification of the results for turning A356 matrix metal reinforced with 10% by weight of silicon carbide particles, fabricated in-house by stir casting method. Some of the conclusions—like primary wear mechanism is abrasion between reinforcing particles and cutting tool material, tool wear is more in the flank portion, surface finish improves at higher cutting speeds, tool wear strongly depends on the cutting speed followed by depth of cut, surface roughness strongly depends on the feed rate, the greater the feed rate, the more the surface roughness, etc.—are as expected by a mechanic machining abrasive materials. The conclusion that power consumed is less at higher cutting speeds because of less friction between the tool and workpiece interface, is a very interesting finding and is contrary to common belief: more cutting speed – more material removal rate – more cutting forces – more power. This could have been investigated more over a larger range of cutting parameters to know where the limit is, if any. The second paper, “Performance Evaluation of Karanja Biodiesel Used as a Fuel in Diesel Engine”, by Varun et al., is another application of Taguchi’s orthogonal arrays method to study and evaluate the performance of a diesel engine with blended fuel. Using Artificial Neural Network (ANN) model and experimental data for training and standard back-propagation algorithm for the CI engine, the authors have carried out an experimental study to compare the engine parameters of four different blends of diesel and Karanja biodiesel. Their results show that blending of biodiesel with conventional diesel is a good alternative for CI engines. A good correlation between the predicted results from ANN and those measured experimentally has been shown from the analysis of the experimental data using ANN, thus confirming that the training algorithm of back-propagation is sufficient enough in predicting engine torque, specific fuel consumption and exhaust gas temperature components for different engine speeds and different fuel blends.

The effect of the exit blade angle on the performance of a radial centrifugal pump when the pump handles fluids of varying viscosity has been studied by Rana et al., in their paper, “CFD Analysis of Pump Performance with Fluids Having Different Viscosity at Different Exit Blade Angles”. A model for the centrifugal pump has been prepared in ANSYS and simulated for five blade exit angles and other operating conditions with fluids of different viscosities, to study the effects on pump performance. The authors have found that as blade exit angle increases, the performance of the pump improves. Also, as the viscosity of fluid increases, the efficiency decreases and the power consumption increases. Further, they claim that the best efficiency point is obtained at a higher blade exit angle, because as the exit blade angle increases, the wake/turbulence at the exit of the impeller decreases.

In the last paper, “Modeling of Material Removal Rate in Ultrasonic Machining of Titanium: Buckingham-P Approach”, the authors, Singh and Khamba, have used the outcome of Taguchi-based model for developing a mathematical model using Buckingham’s P theorem for ultrasonic machining of titanium and its alloys. Six input parameters have been selected by the authors to study their effect on Material Removal Rate (MRR). A comparison with experimental results has been claimed by the authors, and interactions among the parameters have been considered for developing the model. Their conclusions—ultrasonic power, slurry type and type of tool have significant effects on the MRR; the SS tool with boron carbide slurry at 450 W of ultrasonic power is found to show the best results for MRR; the other input parameters, namely, grit size, slurry temperature and slurry concentration were found to be insignificant as regards MRR of titanium and its alloys—need a close scrutiny by the readers before using them.

- -R K Mittal
Consulting Editor