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Optimization of response parameter is essential in any process .The purpose of this paper is to focus at achieving the optimized parameter for submerged arc welding to furnish the quality welds at direct current electrode positive (DCEP) polarity and direct current electrode negative (DCEN) polarity.

This paper achieves the parameter after extensive trial runs and finally parameters are optimized to acquire the cost effective and quality welds in submerged arc welding using the response surface methodology.

Apart from effect of parameters on weld bead geometry has been identified but optimized parameters has also been achieved for submerged arc welding process for DCEP and DCEN polarities.

As this study is related to practical work it may be useful for any relevant application.

The process parameters used in this experimental work will be basis for job work/industry for submerged arc welding.

This paper identifies the effect of polarity in submerged arc welding.

This experimental study aims to deal with the improvement of process performance of electric discharge drilling (EDD) for fabricating true blind holes in titanium alloy Ti6Al4V. Micro EDD was performed on Ti6Al4V and blind holes were drilled into the workpiece.

The effects of input parameters (i.e. voltage, capacitance and spindle speed) on responses (i.e. material removal rate, tool wear rate and surface roughness [SR]) were evaluated through response surface methodology. The data was analyzed using analysis of variance and multi-optimization was performed for the optimized set of parameters. The optimized process parameters were then used to drill deeper blind holes.

Blind holes have few characteristics such as SR, taper angle and corner radius. The value of corner radius reflects the quality of the hole produced as well as the amount of tool roundness. The optimized process parameters suggested by the current experimental study lower down the response values (i.e. SR, taper angle and corner radius). The process is found very effective in producing finished blind holes.

This experimental study establishes EDD as a feasible process for the fabrication of truly blind holes in Ti6Al4V.

This paper aims to assess the effect of natural antioxidants (Tulsi, Lemon grass and Aloevera) on sensory and microbiological quality as well as on Thiobarbituric acid (TBA) values of Redplum and Sahiwal-based milk smoothies stored under refrigeration.

The smoothies were developed by incorporating optimum level of natural antioxidants, fresh red plum and Sahiwal milk. They were aerobically packaged in low-density polyethylene pouches and stored under refrigeration (4 ± 2°C) till its spoilage. These smoothies were assessed for various storage quality parameters like sensory parameters, microbiological quality and TBA values at regular interval of two days.

Smoothies made without using natural antioxidants were in good condition for four days, and treated smoothies were stored well for six days. The microbial profile showed significant (p < 0.05) increase in SPC and psychrophilic counts on advancement of storage days. However, no coliform and yeast and mould were detected in all variants of smoothies during storage. TBA values were also increased during storage. But microbial counts and TBA both were under the prescribed limit as described by various organizations. Smoothies treated with Tulsi were found best followed by lemongrass- and aloevera-treated products.

Amino acid and fatty acid profiling may be incorporated to known how the exact nutritional value.

Developed milk smoothies using natural antioxidants may serve the purpose of functional food.

As per the authors, today, world is seeking for health providing components with longer product shelf life. Therefore, the product may serve the purpose.

The paper has demonstrated that the Sahiwal milk and red plum-based smoothies were of high acceptability. Their shelf life was found best when treated with Tulsi, Lemon grass and Aloevera natural antioxidants. It was better in all spectrums like lower microbial counts, higher sensory attributes and lower TBA counts as compared to untreated products.

This paper aims to propose fuzzy-regression-particle swarm optimization (PSO) based hybrid optimization approach for getting maximum weld quality in terms of weld strength and bead depth of penetration.

The prediction of welding quality to achieve best of it is not possible by any single optimization technique. Therefore, fuzzy technique has been applied to predict the weld quality in terms of weld strength and weld bead geometry in combination with a multi-performance characteristic index (MPCI). Then regression analysis has been applied to develop relation between the MPCI output value and the input welding process parameters. Finally, PSO method has been used to get the optimal welding condition by maximizing the MPCI value.

The predicted weld quality or the MPCI values in terms of combined weld strength and bead geometry has been found to be highly co-related with the weld process parameters. Therefore, it makes the process easy for setting of weld process parameters for achieving best weld quality, as there is no need to finding the relation for individual weld quality parameter and weld process parameters although they are co-related in a complicated manner.

In this paper, a new hybrid approach for predicting the weld quality in terms of both mechanical properties and weld geometry and optimizing the same has been proposed. As these parameters are highly correlated and dependent on the weld process parameters the proposed approach can effectively analyzing the ambiguity and significance of each process and performance parameter.