Amitabha Ghosh

Bio: Amitabha Ghosh is an academic researcher from Indian Institute of Engineering Science and Technology, Shibpur. The author has contributed to research in topics: Fuzzy logic & Inertial frame of reference. The author has an hindex of 12, co-authored 38 publications receiving 827 citations. Previous affiliations of Amitabha Ghosh include Indian National Science Academy & Indian Institute of Technology Kharagpur.

A thermo-electric model of material removal during electric discharge machining

Abstract: In Electro Discharge Machining (EDM), melting is the main process for metal removal. However, for short pulses (discharge duration 100 μs), this electrostatic force becomes very small and does not play a significant role in the removal of metal. In the model proposed, the electrostatic force acting on the metal surface and the stress distribution inside the metal due to this electrostatic force have been estimated. The variation of the yield strength with depth inside the metal has also been found out and finally the 'crater depth' due to this electrostatic force has been calculated.

State of the art electrical discharge machining (EDM)

Abstract: Electrical discharge machining (EDM) is a well-established machining option for manufacturing geometrically complex or hard material parts that are extremely difficult-to-machine by conventional machining processes. The non-contact machining technique has been continuously evolving from a mere tool and die making process to a micro-scale application machining alternative attracting a significant amount of research interests. In recent years, EDM researchers have explored a number of ways to improve the sparking efficiency including some unique experimental concepts that depart from the EDM traditional sparking phenomenon. Despite a range of different approaches, this new research shares the same objectives of achieving more efficient metal removal coupled with a reduction in tool wear and improved surface quality. This paper reviews the research work carried out from the inception to the development of die-sinking EDM within the past decade. It reports on the EDM research relating to improving performance measures, optimising the process variables, monitoring and control the sparking process, simplifying the electrode design and manufacture. A range of EDM applications are highlighted together with the development of hybrid machining processes. The final part of the paper discusses these developments and outlines the trends for future EDM research.

A Gentle Introduction to Memetic Algorithms

Abstract: The generic denomination of ‘Memetic Algorithms’ (MAs) is used to encompass a broad class of metaheuristics (i.e. general purpose methods aimed to guide an underlying heuristic). The method is based on a population of agents and proved to be of practical success in a variety of problem domains and in particular for the approximate solution of NP Optimization problems. Unlike traditional Evolutionary Computation (EC) methods, MAs are intrinsically concerned with exploiting all available knowledge about the problem under study. The incorporation of problem domain knowledge is not an optional mechanism, but a fundamental feature that characterizes MAs. This functioning philosophy is perfectly illustrated by the term “memetic”. Coined by R. Dawkins [52], the word ‘meme’ denotes an analogous to the gene in the context of cultural evolution [154]. In Dawkins’ words:

Dynamic multi-objective optimization and decision-making using modified NSGA-II: a case study on hydro-thermal power scheduling

Abstract: Most real-world optimization problems involve objectives, constraints, and parameters which constantly change with time Treating such problems as a stationary optimization problem demand the knowledge of the pattern of change a priori and even then the procedure can be computationally expensive Although dynamic consideration using evolutionary algorithms has been made for single-objective optimization problems, there has been a lukewarm interest in formulating and solving dynamic multi-objective optimization problems In this paper, we modify the commonly-used NSGA-II procedure in tracking a new Pareto-optimal front, as soon as there is a change in the problem Introduction of a few random solutions or a few mutated solutions are investigated in detail The approaches are tested and compared on a test problem and a real-world optimization of a hydro-thermal power scheduling problem This systematic study is able to find a minimum frequency of change allowed in a problem for two dynamic EMO procedures to adequately track Pareto-optimal frontiers on-line Based on these results, this paper also suggests an automatic decision-making procedure for arriving at a dynamic single optimal solution on-line

Adaptive Locomition of a Multilegged Robot over Rough Terrain

Abstract: Although the off-road mobility characteristics of wheeled or tracked vehicles are generally recognized as being inferior to those of man and cursorial animals, the complexity of the joint-coordination control problem has thus far frustrated attempts to achieve improved vehicular terrain adaptability through the application of legged locomotion concepts. Nevertheless, the evident superiority of biological systems in this regard has motivated a number of theoretical studies over the past decade which have now reached a state of maturity sufficient to permit the construction of experimental computer-controlled adaptive walking machines. At least two such vehicles are known to have recently demonstrated legged locomotion over smooth hard-surfaced terrain. This paper is concerned with an extension of the present theory of limb coordination for such machines to the case in which the terrain includes regions not suitable for weight-bearing and which must consequently be avoided by the control computer in deciding when and where to successively place the feet of the vehicle. The paper includes a complete problem formalization, a heuristic algorithm for solution of the problem thus posed, and a preliminary evaluation of the proposed algorithm in terms of a computer simulation study.