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Article
Publication date: 2 May 2019

Shankar Chakraborty, Prasenjit Chatterjee and Partha Protim Das

To meet the requirements of high-dimensional accuracy and surface finish of various advanced engineering materials for generating intricate part geometries…

Abstract

Purpose

To meet the requirements of high-dimensional accuracy and surface finish of various advanced engineering materials for generating intricate part geometries, non-traditional machining (NTM) processes have now become quite popular in manufacturing industries. To explore the fullest machining capability of these NTM processes, it is often required to operate them while setting their different controllable parameters at optimal levels. This paper aims to present a novel approach for selection of the optimal parametric mixes for different NTM processes in order to assist the concerned process engineers.

Design/methodology/approach

In this paper, design of experiments (DoE) and technique for order preference by similarity to ideal solution (TOPSIS) are combined to develop the corresponding meta-models for identifying the optimal parametric combinations of two NTM processes, i.e. electrical discharge machining (EDM) and wire electrical discharge machining (WEDM) processes with respect to the computed TOPSIS scores.

Findings

For EDM operation on Inconel 718 alloy, lower settings of open circuit voltage and pulse-on time and higher settings of peak current, duty factor and flushing pressure will simultaneously optimize all the six responses. On the other hand, for the WEDM process, the best machining performance can be expected to occur at a parametric combination of zinc-coated wire, lower settings of pulse-on time, wire feed rate and sensitivity and intermediate setting of pulse-off time.

Practical implications

As the development of these meta-models is based on the analysis of the experimental data, they are expected to be more practical, being immune to the introduction of additional parameters in the analysis. It is also observed that the derived optimal parametric settings would provide better values of the considered responses as compared to those already determined by past researchers.

Originality/value

This DoE–TOPSIS method-based approach can be applied to varieties of NTM as well as conventional machining processes to determine the optimal parametric combinations for having their improved machining performance.

Details

Journal of Modelling in Management, vol. 14 no. 2
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 5 February 2018

Shankar Chakraborty, Partha Protim Das and Vidyapati Kumar

The purpose of this paper is to exploit the fullest potential and capability of different non-traditional machining (NTM) processes, it is often recommended to operate…

Abstract

Purpose

The purpose of this paper is to exploit the fullest potential and capability of different non-traditional machining (NTM) processes, it is often recommended to operate them at their optimal parametric combinations. There are several mathematical tools and techniques that have been effectively deployed for identifying the optimal parametric mixes for the NTM processes. Amongst them, grey relational analysis (GRA) has become quite popular due to its sound mathematical basis, ease to implement and apprehensiveness for multi-objective optimization of NTM processes.

Design/methodology/approach

In this paper, GRA is integrated with fuzzy logic to present an efficient technique for multi-objective optimization of three NTM processes (i.e. abrasive water-jet machining, electrochemical machining and ultrasonic machining) while identifying their best parametric settings for enhanced machining performance.

Findings

The derived results are validated with respect to technique for order preference by similarity to ideal solution (TOPSIS), and analysis of variance is also performed so as to identify the most significant control parameters in the considered NTM processes.

Practical implications

This grey-fuzzy logic approach provides better parametric combinations for all the three NTM processes with respect to the predicted grey-fuzzy relational grades (GFRG). The developed surface plots help the process engineers to investigate the effects of various NTM process parameters on the predicted GFRG values.

Originality/value

The adopted approach can be applied to various machining (both conventional and non-conventional) processes for their parametric optimization for achieving better response values.

Details

Grey Systems: Theory and Application, vol. 8 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 18 October 2018

Subhamita Chakraborty, Prasun Das, Naveen Kumar Kaveti, Partha Protim Chattopadhyay and Shubhabrata Datta

The purpose of this paper is to incorporate prior knowledge in the artificial neural network (ANN) model for the prediction of continuous cooling transformation (CCT…

Abstract

Purpose

The purpose of this paper is to incorporate prior knowledge in the artificial neural network (ANN) model for the prediction of continuous cooling transformation (CCT) diagram of steel, so that the model predictions become valid from materials engineering point of view.

Design/methodology/approach

Genetic algorithm (GA) is used in different ways for incorporating system knowledge during training the ANN. In case of training, the ANN in multi-objective optimization mode, with prediction error minimization as one objective and the system knowledge incorporation as the other, the generated Pareto solutions are different ANN models with better performance in at least one objective. To choose a single model for the prediction of steel transformation, different multi-criteria decision-making (MCDM) concepts are employed. To avoid the problem of choosing a single model from the non-dominated Pareto solutions, the training scheme also converted into a single objective optimization problem.

Findings

The prediction results of the models trained in multi and single objective optimization schemes are compared. It is seen that though conversion of the problem to a single objective optimization problem reduces the complexity, the models trained using multi-objective optimization are found to be better for predicting metallurgically justifiable result.

Originality/value

ANN is being used extensively in the complex materials systems like steel. Several works have been done to develop ANN models for the prediction of CCT diagram. But the present work proposes some methods to overcome the inherent problem of data-driven model, and make the prediction viable from the system knowledge.

Details

Multidiscipline Modeling in Materials and Structures, vol. 15 no. 1
Type: Research Article
ISSN: 1573-6105

Keywords

Book part
Publication date: 9 March 2021

Abstract

Details

Global Tariff War: Economic, Political and Social Implications
Type: Book
ISBN: 978-1-80071-314-7

Book part
Publication date: 9 March 2021

Ujjal Protim Dutta, Lipika Kankaria and Partha Pratim Sengupta

The US–China conflicts surrounding the imposition of tariffs have caused a stir in the global markets. Various attempts have been made to understand the rationale and…

Abstract

The US–China conflicts surrounding the imposition of tariffs have caused a stir in the global markets. Various attempts have been made to understand the rationale and causes as well as its impact on the various ­aspects of the international market. There are many unanswered questions pertaining to China’s emergence as a global superpower and the ­possible threats that it poses to the Western dominated market. Based on this background, the chapter is an attempt to investigate the impacts of the Economic Policy Uncertainty (EPU) of the United States and China on three most important global markets, namely, crude oil, credit market, and commodity ­market. To attain the objectives of the chapter, the study has utilized Vector Auto Regressive model and has analyzed the results. The study concludes that China’s EPU has lesser impact on the global market as compared to the US EPU. On the basis of the results obtained, few policy implications have been proposed.

Details

Global Tariff War: Economic, Political and Social Implications
Type: Book
ISBN: 978-1-80071-314-7

Keywords

Content available
Book part
Publication date: 25 May 2022

Abstract

Details

Globalization, Income Distribution and Sustainable Development
Type: Book
ISBN: 978-1-80117-870-9

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