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Scatter in the outcome of repeated experiments is unavoidable due to measurement errors in addition to the non-linear nature of the output responses with unknown influential input parameters. It is a standard practice to select an orthogonal array in the Taguchi approach for tracing optimum input parameters by conducting a few number of experiments and confirm them through additional experimentation (if necessary). The purpose of this paper is to present a simple methodology and its validation with existing test results in finding the expected range of the output response by suggesting modifications in the Taguchi method.

The modified Taguchi approach is proposed to find the optimum process parameters and the expected range of the output response.

This paper presents a simple methodology and its validation with existing test results in finding the expected range of the output response by suggesting modifications in the Taguchi method.

Adequacy of this methodology should be examined by considering the test data on different materials and structures.

The introduction of Chauvenet’s criterion and opposing the signal-to-noise ratio transformation on repeated experiments of each test run will provide fruitful results and less computation burden.

The purpose of this paper is to analyse the relationship between operational risk management (ORM), size, and ownership of Indian banks. This is important in the context of financial crisis experienced by developed countries due to lax regulation.

ORM practices of Indian banks are proxied by excess capital (over the required minimum capital for operational risk). Size of a bank is measured as deposits plus advances. Our sample includes 61 Indian banks during the period from 2010 to 2013. The authors empirically examine the impact of bank size on excess capital using panel data regression model.

The results suggest that size of Indian banks is inversely related to excess capital held by them for managing operational risk. The inverse relationship implies that smaller banks hold higher excess capital over the required minimum as per Basel norms. There is no significant relationship between ownership (public, private and foreign) and excess capital held by banks for managing operational risk.

The study has implications for Indian banks given the high level of losses due to bad loans, and the implementation of Basel III norms by the central bank, i.e. Reserve Bank of India.

The study has implications for Indian financial system as a large percentage (about 33 per cent) of household savings are deployed in deposits with commercial banks and other financial institutions. The bank failure(s) can have disastrous consequences for the Indian economy as the capacity of the Indian financial system to withstand such shocks is highly doubtful.

There is very little evidence on ORM practices of Indian banks, and its relationship with size and ownership. The study assumes significance in the context of significant changes in the institutional and regulatory framework.

This paper adopts a modified Taguchi approach to develop empirical relationships to the performance characteristics (output responses) in terms of process variables and demonstrated their validity through comparison of test data. The method suggests a few tests as per the orthogonal array and provides complete information for all combinations of levels and process variables. This method also provides the estimated range of output responses so that the scatter in the repeated tests can be assessed prior to the tests.

In order to obtain defect-free products meeting the required specifications, researchers have conducted extensive experiments using powder bed fusion (PBF) process measuring the performance indicators (namely, relative density, surface roughness and hardness) to specify a set of printing parameters (namely, laser power, scanning speed and hatch spacing). A simple and reliable multi-objective optimization method is considered in this paper for specifying a set of optimal process parameters with SS316 L powder. It was reported that test samples printed even with optimal set of input variables revealed irregular shaped, microscopic porosities and improper melt pool formation.

Finally, based on detailed analysis, it is concluded that it is impossible to express the performance indicators, explicitly in terms of equivalent energy density (E_0ˆ*), which is a combination of multiple sets of selective laser melting (SLM) process parameters, with different performance indicators. Empirical relations for the performance indicators are developed in terms of SLM process parameters. Test data are within/close to the expected range.

Based on extensive analysis of the SS316 L data using modified Taguchi approach, the optimized process parameters are laser power = 298 W, scanning speed = 900 mm/s and hatch distance = 0.075 mm, for which the results of surface roughness = 2.77 Ra, relative density = 99.24%, hardness = 334 Hv and equivalent energy density is 4.062. The estimated data for the same are surface roughness is 3.733 Ra, relative density is 99.926%, hardness is 213.64 Hv and equivalent energy density is 3.677.

Even though equivalent energy density represents the energy input to the process, the findings of this paper conclude that energy density should no longer be considered as a dependent process parameter, as it provides multiple results for the specified energy density. This aspect has been successfully demonstrated in this paper using test data.

Timely access to reasonably priced financing is critical to promote and sustain small and medium sized businesses (SMEs). This study aims to examine the role of the newly constituted SME exchanges in funding the growth of Indian SME firms. The impact of obtaining public equity capital on the firm’s growth prospects, capital structure and credit profile is the focus of this paper. In addition, this study compares the cost and speed of raising capital on specialised SME exchanges to the main board.

To examine the impact of raising public equity capital, this study uses a difference-in-difference (DID) regression analysis. SMEs that raised financing on the SME exchange between 2013 and 2018 make up the treatment sample. This study uses a propensity score matching technique to find the control group from a sample of unlisted enterprises to reduce the likelihood of selection bias.

This study finds that SME profitability drops after an initial public offering (IPO), which is consistent with previous research. This study also discovered that after a company is listed, its total debt falls. This study also shows that after the IPO, there is no change in the borrowing costs of SME enterprises. Finally, this study finds an evidence of a decline in sales growth following the IPO, implying that the firms use the IPO money to rebalance their accounts after a period of heavy investment rather than for growth finance.

A thriving and efficient equity financing market for SMEs has the potential to establish itself as a viable alternative to the existing dominant bank financing option. To the best of the authors’ knowledge, this research is the first to examine the role of SME exchanges in the funding of Indian SME firms.

The purpose of this paper is to examine the impact of credit risk components on the performance of credit risk management and the growth in non-performing assets (NPAs) of commercial banks in India.

The data are obtained from primary and secondary sources. The primary data are collected by administering questionnaire among risk managers of Indian banks. The secondary data on NPAs of Indian banks are from annual reports and Prowess database compiled by the Centre for Monitoring Indian Economy. Multiple linear regression is used to estimate the models for the study.

The results suggest that the identification of credit risk significantly affects the credit risk performance. The results are robust as credit risk identification is negatively related to annual growth in NPAs or loans. There is evidence in support of a priori expectation of better credit risk performance of private banks compared to that of government banks.

The study has implications for Indian banks suffering from a high level of losses due to bad loans. In addition, it will have implications for the implementation of new Basel Accord norms (Basel III) by the Reserve Bank of India.

The high and rising level of NPAs will have adverse consequences for credit flow in the economy in the absence of appropriate intervention by government and central bank in the form of changes in institutional and regulatory infrastructure. The problems in banking and financial services sector will lead to lower industrial and aggregate economic growth, and lower (or negative) growth in employment.

There is little evidence on credit risk management practices of Indian banks, and its relationship with credit risk performance and NPA growth. The need for an effective risk management system to manage credit risk assumes importance and urgency in the context of high and rising NPAs of Indian banks, and the consequences for the Indian economy.

The purpose of this paper is to adopt the multi-objective optimization technique for identifying a set of optimum abrasive water jet machining (AWJM) parameters to achieve maximum material removal rate (MRR) and minimum surface roughness.

Data of a few experiments as per the Taguchi’s orthogonal array are considered for achieving maximum MRR and minimum surface roughness (Ra) of the Inconel718. Analysis of variance is performed to understand the statistical significance of AWJM input process parameters.

Empirical relations are developed for MRR and Ra in terms of the AWJM process parameters and demonstrated their adequacy through comparison of test results.

The signal-to-noise ratio transformation should be applied to take in to account the scatter in the repetition of tests in each test run. But, many researchers have adopted this transformation on a single output response of each test run, which has no added advantage other than additional computational task. This paper explains the impact of insignificant process parameter in selection of optimal process parameters. This paper demands drawbacks and complexity in existing theories prior to use new algorithms.

Taguchi approach is quite simple and easy to handle optimization problems, which has no practical implications (if it handles properly). There is no necessity to hunt for new algorithms for obtaining solution for multi-objective optimization AWJM process.

This paper deals with a case study, which demonstrates the simplicity of the Taguchi approach in solving multi-objective optimization problems with a few number of experiments.

Gene selection is considered as the fundamental process in the bioinformatics field. The existing methodologies pertain to cancer classification are mostly clinical basis, and its diagnosis capability is limited. Nowadays, the significant problems of cancer diagnosis are solved by the utilization of gene expression data. The researchers have been introducing many possibilities to diagnose cancer appropriately and effectively. This paper aims to develop the cancer data classification using gene expression data.

The proposed classification model involves three main phases: “(1) Feature extraction, (2) Optimal Feature Selection and (3) Classification”. Initially, five benchmark gene expression datasets are collected. From the collected gene expression data, the feature extraction is performed. To diminish the length of the feature vectors, optimal feature selection is performed, for which a new meta-heuristic algorithm termed as quantum-inspired immune clone optimization algorithm (QICO) is used. Once the relevant features are selected, the classification is performed by a deep learning model called recurrent neural network (RNN). Finally, the experimental analysis reveals that the proposed QICO-based feature selection model outperforms the other heuristic-based feature selection and optimized RNN outperforms the other machine learning methods.

The proposed QICO-RNN is acquiring the best outcomes at any learning percentage. On considering the learning percentage 85, the accuracy of the proposed QICO-RNN was 3.2% excellent than RNN, 4.3% excellent than RF, 3.8% excellent than NB and 2.1% excellent than KNN for Dataset 1. For Dataset 2, at learning percentage 35, the accuracy of the proposed QICO-RNN was 13.3% exclusive than RNN, 8.9% exclusive than RF and 14.8% exclusive than NB and KNN. Hence, the developed QICO algorithm is performing well in classifying the cancer data using gene expression data accurately.

This paper introduces a new optimal feature selection model using QICO and QICO-based RNN for effective classification of cancer data using gene expression data. This is the first work that utilizes an optimal feature selection model using QICO and QICO-RNN for effective classification of cancer data using gene expression data.

The purpose of this paper is to examine the effect of the presence of independent board directors on financial performance in India.

This study used panel regression models on large listed Indian firms to investigate the impact on financial performance owing to the presence of independent directors.

The findings suggest that independent board directors in Indian contexts do not significantly affect financial performance.

This study has implications for the formulation of regulation related to appointment of independent directors and the extent of their representation on the board for them to be effective.

The proportion of independent directors on the board of the firm is influenced by the trade-off between the cost of having independent directors on the board versus the benefits to the firm and society.

The impact of the presence of an independent director on financial performance in highly concentrated ownership remains ambiguous.

Finite element analysis (FEA) has been carried out utilizing the ANSYS software package to assess the failure of thick and thin‐walled steel cylindrical pressure vessels. A simple experimental stress analysis (ESA) procedure is described to evaluate the stress components on inner and outer surfaces of the vessels under internal pressure from the measured surface strains. The procedure is validated considering the strain values of FEA for the applied pressure as measured quantities and obtained the corresponding stress components considering the stress‐strain data of the material from ESA and compared with those of FEA results. Failure pressure estimates from FEA (based on the global plastic deformation) were found to be in good agreement with test results of thin as well as thick‐walled cylindrical vessels made of ductile steel materials.

The purpose of this paper is to optimize the fusion zone grain size and hardness using Hooke and Jeeves Algorithm.

Experiments are conducted as per four factors, five levels response surface method based central composite design matrix. Empirical relations for predicting grain size and harness are developed. The effect of welding variables on grain size and hardness are studies. Grain size and hardness are optimised using Hooke and Jeeves Algorithm.

The developed empirical relations can be effectively used to predict grain size and hardness values of micro plasma arc welded Inconel 625 sheets. The values of grain size and hardness obtained by Hooke and Jeeves Algorithm matches with experimental values with great accuracy.

The developed mathematical models are valid for 0.25 mm thick Inconel 625 sheets only.

In the present paper only four important factors namely peak current, back current, pulse rate and pulse width are considered, however one may consider other parameters like plasma gas flow rate, shielding gas flow rate, etc.

The present work is very much useful to sheet metal industries manufacturing metal bellows, diaphragms, etc.