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Nowadays, ample industries are fascinated to look for high strength and light weight materials for the development of robust parts. Because of light weight and high stiffness to weight ratio; usage of aluminum parts is growing rapidly, especially in automotive engineering. Process improvement of Al alloys and their grain structure refinement is the current area of interest in casting companies. In this research work, an investigation has been carried out to enhance the process improvement of die casting by optimization of various significant parameters and their refinement of grains by the effect of Nb-C novel grain refiner.

L27 orthogonal array (OA) has been considered to optimize the preferred casting input parameters such as molten metal temperature (°C), die temperature (°C), injection pressure (bar), Al-3.5Nb-1.5 C novel grain refiner and Ni alloying additions as key process parameters in order to increase the quality and efficiency of Al-9Si-3Cu aluminum alloy die casting by reducing the porosity formation.

It was observed that the porosity values have significantly decreased from 0.88% to 0.25% particularly at 0.1 wt.% of new grain refiner and 0.5 wt. % of Al-6Ni master alloy. As per the ANOVA results, it was observed that Al-3.5FeNb-1.5 C grain refiner (F value 2609.22), Al-6Ni alloying addition (F value 1329.13), molten metal temperature (F value 1002.43) and, injection pressure (F value 448.06) are the factors that significantly affects the porosity, whereas die temperature was found to be insignificant. The results show that new grain refiner is one the most significant factor among the other selected parameters. The contribution of the new grain refiner to the variation of mean casting porosity is around 57.74%. confidence interval (CI) has also been estimated as 0.013 for 95% consistency level to validate the predicted range of optimum casting porosity of aforesaid alloy.

To the best of the authors' knowledge, no study has been conducted in the past to investigate the combined effect of these die casting parameters and composition factors for the development of Al-Si robust cast parts. The paper represents original research and provides new information for the fabrication of die casting parts.

Road accidents, an inadvertent mishap can be detected automatically and alerts sent instantly with the collaboration of image processing techniques and on-road video surveillance systems. However, to rely exclusively on visual information especially under adverse conditions like night times, dark areas and unfavourable weather conditions such as snowfall, rain, and fog which result in faint visibility lead to incertitude. The main goal of the proposed work is certainty of accident occurrence.

The authors of this work propose a method for detecting road accidents by analyzing audio signals to identify hazardous situations such as tire skidding and car crashes. The motive of this project is to build a simple and complete audio event detection system using signal feature extraction methods to improve its detection accuracy. The experimental analysis is carried out on a publicly available real time data-set consisting of audio samples like car crashes and tire skidding. The Temporal features of the recorded audio signal like Energy Volume Zero Crossing Rate 28ZCR2529 and the Spectral features like Spectral Centroid Spectral Spread Spectral Roll of factor Spectral Flux the Psychoacoustic features Energy Sub Bands ratio and Gammatonegram are computed. The extracted features are pre-processed and trained and tested using Support Vector Machine (SVM) and K-nearest neighborhood (KNN) classification algorithms for exact prediction of the accident occurrence for various SNR ranges. The combination of Gammatonegram with Temporal and Spectral features of the validates to be superior compared to the existing detection techniques.

Temporal, Spectral, Psychoacoustic features, gammetonegram of the recorded audio signal are extracted. A High level vector is generated based on centroid and the extracted features are classified with the help of machine learning algorithms like SVM, KNN and DT. The audio samples collected have varied SNR ranges and the accuracy of the classification algorithms is thoroughly tested.

Denoising of the audio samples for perfect feature extraction was a tedious chore.

The existing literature cites extraction of Temporal and Spectral features and then the application of classification algorithms. For perfect classification, the authors have chosen to construct a high level vector from all the four extracted Temporal, Spectral, Psycho acoustic and Gammetonegram features. The classification algorithms are employed on samples collected at varied SNR ranges.

Aluminium matrix composites are subjected to wear as well as higher temperature applications such as pistons, cylinder heads and blocks for car engines. Therefore, it is important to evaluate the performance of aluminium metal matrix composite at elevated temperature.

In the present work wear performance of Al-TiC composite with 7.5% reinforcement of TiC powder is carried out at elevated temperature. The composite specimens are prepared with the help of centrifugal casting method to get the large segregation of reinforcement on the outer layer of the composite which is subjected to wear. Taguchi method is used for preparing design of experiments.

The wear test is performed on DUCOM pin on disc setup having the heating chamber facility. The results of wear test are analysed with the help of MINITAB 19 software. The results show that temperature has dominant effect on the wear rate. The mathematical model through regression is predicted for wear rate and coefficient of friction. The study of worn-out surface is performed with the help of scanning electron microscope. The micrographs show that the type of wear is changes from abrasive to severe wear and some delamination.

The experiments are conducted as per ASTM standards. The results give the mathematical equation for wear rate and coefficient of friction at elevated temperatures.

Marketing, marketing communication and business strategy.

Graduate level and some core courses in undergraduate level.

The case describes the evolution of a start-up company, Great Sports Infra Pvt Ltd, which had acquired the exclusive dealership of the largest artificial sports surface products company – FieldTurf Tarkett. Great Sports Infra was started as a small business with a capital of INR 5 million, by Mr Anil Kumar who had won the exclusive license to sell the FieldTurf brand of artificial turf in India and the SAARC region. FieldTurf was a well entrenched brand for playing surfaces in several developed countries around the world. The size, scope and consumer base of the Indian market was vastly different from the mature markets in which FieldTurf was a well established brand. Anil had to find a market for the product in India which was a classic context of “existing product entering a new market” – in this case an emerging market. Identifying new markets and targeting them with a relevant marketing mix and communication mix were the dominant challenges faced by Anil. Having developed the market in India, he now faces competition from cheaper manufacturers and limited growth in the sports infrastructure. The students must deliberate on current strategies and suggest strategies for the future growth of the product in this market.

• Challenges of an established brand entering a new market in the emerging economies. Using Ansoff's matrix to identify the nature of challenges.

• Understanding positioning strategy.

• To understand how to extract IMC strategy from business strategy.

• Targeting each segment differently but keeping the message consistent following the principles of principles of IMC, i.e. harmony, consistency and synergy.

• Understanding the role of 6Ms in designing a communication plan.

• Understanding how to identify appropriate media mix.

• Understanding the holistic IMC framework.

Challenges of an established brand entering a new market in the emerging economies. Using Ansoff's matrix to identify the nature of challenges.

Understanding positioning strategy.

To understand how to extract IMC strategy from business strategy.

Targeting each segment differently but keeping the message consistent following the principles of principles of IMC, i.e. harmony, consistency and synergy.

Understanding the role of 6Ms in designing a communication plan.

Understanding how to identify appropriate media mix.

Understanding the holistic IMC framework.

Teaching notes.

The purpose of this paper is to improve the design of a solid square canopy of a parachute. The design improvements are brought out by providing minor slits in the canopy area. Proper designing of the parachute was carried out using theoretical investigation coupled with experimentation. This parachute is designed for launch of sonobuoy from fixed wing aircraft.

Literature review was carried out on the design of such parachutes for the launch of a sonobuoy from a high altitude to the water entry. Computational fluid dynamics (CFD) analysis provided the value of the coefficient of drag for the slit-cut square canopy parachute, with and without sonobuoy for different lengths of the slit. Besides the theoretical investigation, experimentation was also carried out to validate the design.

The experimentation was carried out on 58 and 75 gsm fabric canopies with the slit edge plain-cut with thermally sealed edges, stitched and strengthened. In the case of plain-cut slits on the canopy made of 75 gsm fabric, no tearing of the slit edge was observed in dynamic and flight tests.

The present work has been carried out considering various assumptions and limited trial data specific to precision drop of 9 kg payload. The work can be adopted for bigger parachute for dropping of higher payloads.

Lab strength test, track dynamic and flight trials were conducted to acquire useful data for the present analysis. Besides the theoretical investigations and CFD analysis inherently based on numerous assumptions, experimentation was carried out as the sonobuoy deployment conditions are full of uncertainty. Dynamic and airdrop tests were conducted for this reason to determine design changes in the slits, both at the material level and on improvisations.

Equipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.

The research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.

The findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.

Manufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.

The study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.

Though Indian economy since 1980s has expanded very rapidly, yet the benefits of growth remain very unequally distributed. The purpose of this paper is to provide new evidence about the shape, intensity and decomposition of inequality change between 2005 and 2012. The authors find that Gini, as a measure of income inequality, has increased irrespective of geographic regions.

Based on a recent distribution analysis tool, “ABG,” the paper focuses on local inequality, and summarizes the shape of inequality in terms of three inequality parameters (α, β and γ) to examine how the income distributions have changed over time. Here, the central coefficient (α) measures inequality at the median level, with adjustment parameters at the top (β) and bottom (γ).

The results reveal that at the middle of distribution (α), there is almost the same inequality in both the periods, but the coefficients on the curvature parameters β and γ show that there is increasing inequality in the subsequent period. Finally, an analysis of decomposition of inequality change suggests that though income growth was progressive, however, this equalizing effect was more than offset by the disequalizing effect of income reranking.

This paper shows how it can be possible both for “the poor” to fare badly relatively to “the rich” and for income growth to be pro-poor.

This paper stresses the significance of inequality reduction.

Inequality reduction is very much imperative in ending poverty and boosting shared prosperity.

Perhaps, this research work is first of its kind to examine the shape and decomposition of change in income inequality in India in recent years.

Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. The purpose of this paper is to construct capital procurement decision-making model to optimize supplier selection in the Indian automobile industry.

To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria, although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria.

The results show that the total cost of ownership (TOC) is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, TOC, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier.

The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.

This study aims to investigate the impact of I4.0 technologies and their interoperability on supply chains (SCs) performance and how the integration of such technologies and their interoperability can create pathways for SCs resilience post-COVID-19. This is of paramount importance in the context of COVID-19 as the investigation around I4.0 technologies may provide relevant insights on how SCs may better respond to unexpected situations like the current pandemic with the use of digital technologies.

A survey research method was designed based on some constructs extracted from the literature regarding the main disruptive technologies, interoperability, elements of supply chains processes (SCPs) performance such as integration, collaboration, transparency, efficiency, responsiveness and profitability. The data were collected from March to July 2020 from different regions of the world when the peak of the first wave of the pandemic had occurred. The survey resulted in 115 valid responses. The study used a combination of descriptive, correlation and multiple regression methods to analyse the data.

The study indicates that disruptive technologies significantly impact SCPs performance (integration, collaboration, responsiveness and transparency) and their resilience. The findings did not support the notion that these technologies improve the efficiency of SCs, a significant contrast to the existing literature. Our findings also refute the existing understanding that interoperability moderates the impact of disruptive technologies on SCPs performance and enhancing the resilience of SCs. However, the findings show that the integration of I4.0 technologies and their interoperability has a positive impact on SCPs profitability.

The findings strongly advocate that this integration plays an important role in improving SC performance, and a future pathway of SC resiliency post-COVID-19. Considering that the I4.0 trend will impact SCs in the coming years, this study brings a relevant contribution to researchers and practitioners.

This study makes a unique contribution by investigating a novel causal relationship between the main elements (I4.0 technologies, interoperability, processes performance and strategic outcomes) related to the SC in this new context.

Food loss and wastage is an issue of global concern and the household sector is one of the biggest contributors to this. Solar drying has been explored by many eminent researchers as a solution to this problem but there have been concerns about the lack in designs, higher cost, lower performance, and consumer acceptability. The present research aims to design a small-scale domestic solar dryer by using computer software.

Response surface methodology (RSM) and computational fluid dynamics (CFD) are used to design the domestic solar dryer. Initially, design variables (inlet and outlet vent height) are identified and a design of experiments has been created using RSM for set of experimental runs. The experimental runs suggested by RSM were carried out using CFD simulation in COMSOL Multiphysics software and the results were used for optimization of response variables (outlet velocity and drying chamber temperature) in RSM.

Outlet vent height was found to be most significantly affecting parameter to both the responses. The optimum values of inlet and outlet vent heights were 0.5 and 2.5 cm, respectively with the overall desirability of 0.728. The model accuracy was tested by conducting a confirmation test as post processing in design expert software.

Designing a solar dryer is a complex, costly and time consuming process, this study presents an easy, economic and fast method to design a new solar dryer. It would help researchers to design and develop new domestic as well as large size industrial solar dryer.