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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.

This paper presents the influence of beam incidence angle on austenitic stainless steel sheet subjected to a high density laser beam having Gaussian power density distribution. Bead‐on trials are conducted on 3.15 mm thick commercial AISI 304 austenitic stainless steel sheet using a Nd:YAG laser source with a maximum output of 2kW in the continuous wave mode. The effects of beam incident angle on the weld bead geometry are studied using finite element analysis. Experiments are conducted with 600, 1000 and 1400W laser power and 800, 1400 and 2000mm/min welding speed. A three dimensional finite element model is developed for the simulation of non‐linear transient thermal analysis of the weld bead geometry for different beam incident angles using the finite element code ANSYS. The result reveals that by increasing the beam incident angle with constant beam power and welding speed, there is a considerable reduction in the depth of penetration‐to‐width ratio (d/w). Further, it is noticed that the process enters into conduction mode of welding from the keyhole mode of welding as the beam angle is increased beyond 10o. The comparison of the simulation results and the experimental data for weld bead geometry with different beam incident angles show good agreement.

This study empirically explores the intraday price discovery mechanism and volatility transmission effect between the dual-listed Indian Nifty index futures traded simultaneously on the onshore Indian exchange, National Stock Exchange (NSE) and offshore Singapore Exchange (SGX) and its spot market by using high-frequency data.

This study applies the vector error correction model to analyze the lead-lag relationship in price discovery among three markets. The contributions of individual markets in assimilating new information into prices are measured using various measures, Hasbrouck's (1995) information share, Lien and Shrestha's (2009) modified information share and Gonzalo and Granger's (1995) component share. Additionally, the Granger causality test is conducted to determine the causal relationship. Lastly, the BEKK-GARCH specification is employed to analyze the volatility transmission.

This study provides robust evidence that Nifty futures lead the spot in price discovery. The offshore SGX Nifty futures consistently ranked first in contributing to price discovery, followed by onshore NSE Nifty futures and finally by the spot. Empirical results also show unidirectional causality and volatility transmission from Nifty futures to spot, as well as bidirectional causal relationship and volatility spillovers between NSE and SGX Nifty futures. These novel findings provide fresh insights into the informational efficiency of the dual-listed Indian Nifty futures, which is distinct from previous literature.

These findings can potentially help market participants, policymakers, stock exchanges and regulators.

Unlike previous studies in this area, this is the first study that empirically examines the intraday price discovery mechanism and volatility spillover between the dual-listed futures markets and its spot market using 5-min overlapping price data and trivariate econometric models.

This study examines the dynamic linkages between the Indian Nifty index futures traded on the offshore Singapore Exchange (SGX) and US stock indices (DJIA, NASDAQ and S&P 500) under the closure of the spot market for Nifty futures.

With high-frequency 5-min overlapping price data, the authors employ the Johansen cointegration test to investigate long-run relationships, the Granger causality test to assess short-run dynamics and the BEKK-GARCH model for volatility spillover investigation.

The empirical findings reveal that the SGX Nifty futures market is cointegrated with the US DJIA market. The US DJIA stock index strongly influences the price discovery of SGX Nifty futures and past innovations in the US markets strongly impact the current volatility of SGX Nifty futures.

Findings from this study have significant implications for market participants, particularly foreign investors and portfolio managers. These findings might be helpful for market participants to improve the prediction power of expected SGX Nifty futures price and volatility, especially under the closure of the spot market. Also, SGX market participants can take the significant role of the US market into account when formulating hedging and trading strategies with Indian Nifty futures. Besides, our findings have significant implications for policymakers in evaluating market stability.

This article adds to the very limited research on offshore or international stock index futures; it is the first study that empirically examines the international linkages of offshore SGX Nifty futures under the closure of its underlying spot market and also the driving force behind the linkages.

The objective of this paper is to evaluate the role of consumers’ perceived risks and benefits of agro‐biotechnology in shaping the purchase pattern for organic food among UK consumers.

An on‐line household survey of UK consumers was conducted using household panels maintained by the National Panel Diary (NPD) group. The data included organic food purchase pattern, perceived risks and benefits of agro‐biotechnology, and socio‐demographic information about the respondents. A regression model was used to examine the impact of consumers’ general purchase behavior, perceived risks and benefits of GM technology, and socio‐demographic on organic food purchase.

Only 4 percent of the respondents purchased organic foods all the time, while 26 percent never purchased. Perceived risks of agro‐biotechnology played a dominant role in influencing organic food purchase decisions. As the risk perception increased consumers were likely to buy organic food more often. Although premium prices of organic foods were of concern to many consumers, food safety was the most important consideration when making organic food purchase decisions. Household income positively influenced consumers’ likelihood of buying organic food. Female respondents were likely to purchase organic foods more often than their male counter parts. Older respondents were less likely to buy organic foods compared to younger respondents.

The results of this study provide valuable information in formulating short and long‐term marketing programs for organic producers. Following the study results, food safety concern and perceived risks of GM food products need to be the overall theme of marketing programs for organic products.

The study uses a large sample size in examining the relationship between perceived risks of agro‐biotechnology and organic food purchase. The results are more robust and representative.

The purpose of this paper is to determine the factors affecting the consumers' willingness to pay higher prices for genetically unmodified products.

Tomato was selected as a model crop. Data used in this study were gathered from questionnaires conducted in Tokat province of Turkey in April 2006. Questionnaires were accomplished via face‐to‐face interviews over 262 households. “Ordered logit model” was used in determining the factors that affect the willingness of consumers for higher prices for genetically unmodified products. Ordered models are those that limit dependent variables to certain intervals. According to the results, variables of household size, monthly household income, household's monthly food consumption expenditure and level of consumers' sensitivity over the issue affected the willingness to pay higher prices for genetically unmodified products.

Results of the study indicated that household size and monthly household income had negative effects on the willingness to pay extra, while monthly food expenditure and concern had positive effects.

The results of the study will be beneficial for the policy makers, producers, consumers and those conducting research in this area alike. Carrying out studies aimed at determining consumer preference, such as this, will help form consumer consciousness, especially in Turkey, to protect consumer health.

This paper aims to investigate the influence of “BroncoCut-X” (copper core-ZnCu50 coating) electrode on the machining of Ti-3Al-2.5V in view of its extensive use in aerospace and medical applications. The machining parameters are selected as Spark-off Time (ST_off), Spark-on Time (ST_on), Wire-speed (S_w), Wire-Tension (WT) and Servo-Voltage (S_v) to explore the machining outcomes. The response characteristics are measured in terms of material removal rate (MRR), average kerf width (KW) and average-surface roughness (SA).

Taguchi’s approach is used to design the experiment. The “AC Progress V2 high precision CNC-WEDM” is used to conduct the experiments with ϕ 0.25 mm diameter wire electrode. The machining performance characteristics are examined using main effect plots and analysis of variance. The grey-relation analysis and fuzzy interference system techniques have been developed to combine (called grey-fuzzy reasoning grade) the experimental response while Rao-Algorithm is used to calculate the optimal performance.

The hybrid optimization result is obtained as ST_off = 50µs, ST_on = 105µs, S_w = 7 m/min, WT = 12N and S_v=20V. Additionally, the result is compared with the firefly algorithm and improved gray-wolf optimizer to check the efficacy of the intended approach. The confirmatory test has been further conducted to verify optimization results and recorded 8.14% overall machinability enhancement. Moreover, the scanning electron microscopy analysis further demonstrated effectiveness in the WEDMed surface with a maximum 4.32 µm recast layer.

The adopted methodology helped to attain the highest machinability level. To the best of the authors’ knowledge, this work is the first investigation within the considered parametric range and adopted optimization technique for Ti-3Al-2.5V using the wire-electro discharge machining.

Since, wear is the one of the most commonly encountered industrial problems leading to frequent replacement of components there is a need to develop metal matrix composites (MMCs) for achieving better wear properties. The purpose of this paper is to fabricate aluminum MMCs to improve the dry sliding wear characteristics. An effective multi-response optimization approach called the principal component analysis (PCA) was used to identify the sets of optimal parameters in dry sliding wear process.

The present work investigates the dry sliding wear behavior of graphite reinforced aluminum composites produced by the molten metal mixing method by means of a pin-on-disc type wear set up. Dry sliding wear tests were carried on graphite reinforced MMCs and its matrix alloy sliding against a steel counter face. Different contact stress, reinforcement percentage, sliding distance and sliding velocity were selected as the control variables and the response selected was wear volume loss (WVL) and coefficient of friction (COF) to evaluate the dry sliding performance. An L25 orthogonal array was employed for the experimental design. Optimization of dry sliding performance of the graphite reinforced MMCs was performed using PCA.

Based on the PCA, the optimum level parameters for overall principal component (PC) of WVL and COF have been identified. Moreover, analysis of variance was performed to know the impact of individual factors on overall PC of WVL and COF. The results indicated that the reinforcement percentage was found to be most effective factor among the other control parameters on dry sliding wear followed by sliding distance, sliding velocity and contact stress. Finally the wear surface morphology of the composites has been investigated using scanning electron microscopy.

Various manufacturing techniques are available for processing of MMCs. Each technique has its own advantages and disadvantages. In particular, some techniques are significantly expensive compared to others. Generally the manufacturer prefers the low cost technique. Therefore stir casting technique which was used in this paper for manufacturing of Aluminum MMCs is the best alternative for processing of MMCs in the present commercial sectors. Since the most important criteria of a dry sliding wear behavior is to provide lower WVL and COF, this study has intended to prove the application of PCA technique for solving multi objective optimization problem in wear applications like piston rings, piston rods, cylinder heads and brake rotors, etc.

Application of multi-response optimization technique for evaluation of tribological characteristics for Aluminum MMCs made up of graphite particulates is a first-of-its-kind approach in literature. Hence PCA method can be successfully used for multi-response optimization of dry sliding wear process.