There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

The general manufacturing problem can be described as the achievement of a predefined product quality with given equipment, cost and time constraints. Unfortunately, for some quality characteristics of a product such as surface roughness it is hard to ensure that these requirements will be met. This paper aims at presenting the various methodologies and practices that are being employed for the prediction of surface roughness. The resulting benefits allow for the manufacturing process to become more productive and competitive and at the same time to reduce any re-processing of the machined workpiece so as to satisfy the technical specifications. Each approach with its advantages and disadvantages is outlined and the present and future trends are discussed. The approaches are classified into those based on machining theory, experimental investigation, designed experiments and artificial intelligence (AI).

Predicting surface roughness in machining: a review

Fundamentals of Modern Manufacturing: Materials, Processes and Systems

The fifth edition of "Numerical Methods for Engineers" continues its tradition of excellence. Instructors love this text because it is a comprehensive text that is easy to teach from. Students love it because it is written for them--with great pedagogy and clear explanations and examples throughout. The text features a broad array of applications, including all engineering disciplines. The revision retains the successful pedagogy of the prior editions. Chapra and Canale's unique approach opens each part of the text with sections called Motivation, Mathematical Background, and Orientation, preparing the student for what is to come in a motivating and engaging manner. Each part closes with an Epilogue containing sections called Trade-Offs, Important Relationships and Formulas, and Advanced Methods and Additional References. Much more than a summary, the Epilogue deepens understanding of what has been learned and provides a peek into more advanced methods. Approximately 80% of the end-of-chapter problems are revised or new to this edition. The expanded breadth of engineering disciplines covered is especially evident in the problems, which now cover such areas as biotechnology and biomedical engineering. Users will find use of software packages, specifically MATLAB and Excel with VBA. This includes material on developing MATLAB m-files and VBA macros.

Numerical methods for engineers

Due to the widespread use of highly automated machine tools in the industry, manufacturing requires reliable models and methods for the prediction of output performance of machining processes. The prediction of optimal machining conditions for good surface finish and dimensional accuracy plays a very important role in process planning. The present work deals with the study and development of a surface roughness prediction model for machining mild steel, using Response Surface Methodology (RSM). The experimentation was carried out with TiN-coated tungsten carbide (CNMG) cutting tools, for machining mild steel work-pieces covering a wide range of machining conditions. A second order mathematical model, in terms of machining parameters, was developed for surface roughness prediction using RSM. This model gives the factor effects of the individual process parameters. An attempt has also been made to optimize the surface roughness prediction model using Genetic Algorithms (GA) to optimize the objective function. The GA program gives minimum and maximum values of surface roughness and their respective optimal machining conditions.

A genetic algorithmic approach for optimization of surface roughness prediction model

The difficulty and cost involved in the abrasive machining of hard and brittle ceramics are among the major impediments to the widespread use of advanced ceramics in industries these days. It is often desired to increase the machining rate while maintaining the desired surface integrity. The success of this approach, however, relies in the understanding of mechanism of material removal on the microstructural scale and the relationship between the grinding characteristics and formation of surface/subsurface machining-induced damage. In this paper, grinding characteristics, surface integrity and material removal mechanisms of SiC ground with diamond wheel on surface grinding machine have been investigated. The surface and subsurface damages have been studied with scanning electron microscope (SEM). The effects of grinding conditions on surface/subsurface damage have been discussed. This research links the surface roughness, surface and subsurface damages to grinding parameters and provides valuable insights into the material removal mechanism and the dependence of grinding-induced damage on grinding conditions.

Experimental investigation of surface/subsurface damage formation and material removal mechanisms in SiC grinding

An experimental investigation was conducted to determine the effects of cutting conditions and tool geometry on the surface roughness in the finish hard turning of the bearing steel (AISI 52100). Mixed ceramic inserts made up of aluminium oxide and titanium carbonitride (SNGA), having different nose radius and different effective rake angles, were used as the cutting tools. This study shows that the feed is the dominant factor determining the surface finish followed by nose radius and cutting velocity. Though, the effect of the effective rake angle on the surface finish is less, the interaction effects of nose radius and effective rake angle are considerably significant. Mathematical models for the surface roughness were developed by using the response surface methodology.

A surface roughness prediction model for hard turning process

Application of sustainable techniques in metal cutting for enhanced machinability: a review

Nanofluid, fluid suspensions of nanometer sized particles are revolutionizing the field of heat transfer area. Addition of nano-particles to the base fluid also alters the lubricating properties by reducing the friction. In grinding process, friction between the abrasive grains and the workpiece is a key issue governing the main grinding output. It has a direct influence on grinding force, power, specific energy and wheel wear. Moreover, high friction force increases the heat generation and lead to thermal damage in the surface layer of the ground work. Hence, any effort towards the friction control will enhance the component quality significantly. In this study, nanofluid as metal working fluid (MWF) is made by adding 0.05, 0.1, 0.5 and 1% volume concentration of Al2O3 and CuO nano-particles to the water during the surface grinding of Ti–6Al–4V in minimum quantity lubrication (MQL) mode. Surface integrity of ground surface, morphology of the wheel, and chip formation characteristics are studied using surface profilometer, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and stereo zoom microscopy (SZM). Coefficient of friction was estimated On-Machine using the measured forces. The results showed that the type of nanoparticle and its concentration in base fluid and the MQL flow rate play a significant role in reducing friction. Application of nanofluid leads to the reduction of tangential forces and grinding zone temperature. The cooling effect is also evident from the short C-type chip formation. MQL application with Al2O3 nanofluid helps in effective flushing of chip material from the grinding zone, thereby solving the main problem during the grinding of Ti–6Al–4V.

P. Venkateswara Rao

Papers

A genetic algorithmic approach for optimization of surface roughness prediction model

Experimental investigation of surface/subsurface damage formation and material removal mechanisms in SiC grinding

A surface roughness prediction model for hard turning process

Application of sustainable techniques in metal cutting for enhanced machinability: a review

Performance evaluation of Ti–6Al–4V grinding using chip formation and coefficient of friction under the influence of nanofluids