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This study aims to develop indium-based solders for cryogenic applications.

This paper aims to investigate mechanical properties of indium-based solder formulations at room temperature (RT, 27 °C) as well as at cryogenic temperature (CT, −196 °C) and subsequently to find out their suitability for cryogenic applications. After developing these alloys, mechanical properties such as tensile and impact strength were measured as per American Society for Testing and Materials standards at RT and at CT. Charpy impact test results were used to find out ductile to brittle transition temperature (DBTT). These properties were also evaluated after thermal cycling (TC) to find out effect of thermal stress. Scanning electron microscope analysis was performed to understand fracture mechanism. Results indicate that amongst the solder alloys that have been studied in this work, In-34Bi solder alloy has the best all-round mechanical properties at RT, CT and after TC.

It can be concluded from the results of this work that In-34Bi solder alloy has best all-round mechanical properties at RT, CT and after TC and therefore is the most appropriate solder alloy amongst the alloys that have been studied in this work for cryogenic applications

DBTT of indium-based solder alloys has not been found out in the work done so far in this category. DBTT is necessary to decide safe working temperature range of the alloy. Also the effect of TC, which is one of the major reasons of failure, was not studied so far. These parameters are studied in this work.

Micro, small and medium enterprises (MSMEs) are facing major difficulties with working capital, need of digitalisation and lack of skilled workforce during this crisis situation. Managing resilience post pandemic is again a huge challenge for MSMEs. Therefore, the main objective of the study is to identify the critical barriers for recovery of MSMEs from the pandemic outbreak and recommending potential solutions for avoiding vulnerabilities.

The most significant barriers, which will impact MSMEs resilience issues are extracted from vast literature review, discussed with nine experts from MSMEs and further categorised into organisational, operational and technical barriers. Best–worst method (BWM) has been used to find the importance rating of barriers for developing resilience in MSMEs.

It can be observed that the organisational barriers (0.507) are the most significant, followed by operational barriers (0.300) and then, technological barriers (0.192). Liquidity crunch and inadequate technical skills of employees are the most significant barriers for MSMEs resilience during COVID-19, whereas fluctuation in input cost, unavailability of containers on time and decreased process efficiency are the least significant barriers for recovering MSMEs post COVID-19.

Findings imply that MSMEs should try to overcome major barriers such as resource constraints, lack of skills and knowledge and inefficient inventory planning.

Findings of study will be of immense use for MSMEs in efficient management of operations and in developing resilience during uncertain business environment.

The purpose of this paper is to investigate the relationship between dividend policy and the life cycle of firms in India. In addition, this study intends to examine the variation in dividend behaviour over the life cycle of a firm. The study anticipates that a firm's dividend behaviour varies over its life cycle.

To scrutinize the validity of the proposition, the authors classify 1968 non-financial industrial firms listed at Bombay Stock Exchange (BSE) into growth, mature and stagnant firms over the period 2000–20. Additionally, to check the robustness of the results, they use an array of techniques such as analysis of variance, pooled ordinary least squares, fixed effects models and random effects models.

The empirical findings suggest that dividend behaviour varies over a firm's life cycle. Specifically, stagnant firms are paying significantly higher dividends than growth firms. Mature firms are paying significantly higher dividends than growth firms. The results are consistent after controlling the effects of firm's size, profitability, leverage, operating risk, systematic risk and growth opportunities.

The findings are useful for corporate decision makers in establishing an appropriate dividend policy conditional on firms' life cycle stage and for shareholders in making investment decisions.

The relation between dividend policy and firm life cycle has not been examined before in the context of Indian stock market. Thus, this research bridges this gap in the literature.

With ever-increasing global concerns over environmental degradation and resource scarcity, the need for sustainable manufacturing (SM) practices has become paramount. Industry 5.0 (I5.0), the latest paradigm in the industrial revolution, emphasizes the integration of advanced technologies with human capabilities to achieve sustainable and socially responsible production systems. This paper aims to provide a comprehensive analysis of the role of I5.0 in enabling SM. Furthermore, the review discusses the integration of sustainable practices into the core of I5.0.

The systematic literature review (SLR) method is adopted to: explore the understanding of I5.0 and SM; understand the role of I5.0 in addressing sustainability challenges, including resource optimization, waste reduction, energy efficiency and ethical considerations and propose a framework for effective implementation of the I5.0 concept in manufacturing enterprises.

The concept of I5.0 represents a progressive step forward from previous industrial revolutions, emphasizing the integration of advanced technologies with a focus on sustainability. I5.0 offers opportunities to optimize resource usage and minimize environmental impact. Through the integration of automation, artificial intelligence (AI) and big data analytics (BDA), manufacturers can enhance process efficiency, reduce waste and implement proactive sustainability measures. By embracing I5.0 and incorporating SM practices, industries can move towards a more resource-efficient, environmentally friendly and socially responsible manufacturing paradigm.

The findings presented in this article have several implications including the changing role of the workforce, skills requirements and the need for ethical considerations for SM, highlighting the need for interdisciplinary collaborations, policy support and stakeholder engagement to realize its full potential.

This article aims to stand on an unbiased assessment to ascertain the landscape occupied by the role of I5.0 in driving sustainability in the manufacturing sector. In addition, the proposed framework will serve as a basis for the effective implementation of I5.0 for SM.

The purpose of this paper is to investigate the optimized setting of wire-cut electrical discharge machining (WEDM) parameters at which material removal rate (MRR) and mean roughness depth (Rz) set a compromise. The problem in the processing of Ti-6Al-4V by conventional processes is a high strength, high hardness, high tool wear. Due to which WEDM is adopted to machine Ti-6Al-4V biomedical alloy. Ti-6Al-4V alloy has a number of applications in the engineering and medical industries due to its high strength biocompatibility.

The effect of control factors (i.e. pulse on-time: Pon; pulse off-time: Poff; servo voltage: SV) on the MRR and Rz is investigated in the present research. The planning of experiments is done using a Taguchi-based L9 orthogonal array. The percentage influence of each factor on responses is also evaluated. The multi-objective optimization is done using the grey approach initially. After that, the results were also calculated using harmony search (HS). Therefore, a hybrid approach of grey and HS is used to find the optimized values of MRR and Rz.

The maximum value of grade calculated by grey-HS is 0.7879, while in the case of the experimental run the maximum value of grey grade is 0.7239. The optimized setting after improvisation at this grade value is Pon: 130 µs; Poff: 45 µs and SV: 70 V for MRR and Rz collectively. The validation of the suggested setting is completed by experimentation. The values of MRR and Rz are coming out to be 6.4 mm³/min and 13.84 µm, which represents improvised results after the implementation of the HS algorithm.

The integration of the grey approach with the HS principle in the manufacturing domain is yet to be explored. Therefore, in the present research hybrid approach of grey-HS is implemented in the manufacturing domain having applications in medical industries.

The purpose of this paper is to consider unsteady free convection flow of a dissipative fluid past an exponentially accelerated infinite vertical porous plate in the presence of Newtonian heating and mass diffusion.

The problem is governed by coupled non-linear partial differential equations with appropriate boundary conditions. A Galerkin finite element numerical solution is developed to solve the resulting well-posed two-point boundary value problem. It is a powerful, stable technique which provides excellent convergence and versatility in accommodating coupled systems of ordinary and partial differential equations.

It is found that the skin friction coefficient increases with increases in either of the Eckert number, thermal Grashof number, mass Grashof number or time whereas it decreases with increases in either of the suction parameter, Schmidt number or the acceleration parameter for both air and water. The skin friction coefficient is also found to decrease with increases in the values of the Prandtl number. In addition, it is found that the rate of heat transfer increases with an increase in the suction parameter and decreases with an increase in the Eckert number for both air and water. Lastly, it is found that the rate of heat transfer increases with increasing values of the Prandtl number and decreases with increasing time for all values of the Prandtl number.

The present study has considered only Newtonian fluids. Future studies will address non-Newtonian liquids.

A very useful source of information for researchers on the subject of free convective flow over the surface when the rate of heat transfer from the surface is proportional to the local surface temperature.

This paper is relatively original and illustrates the effects of viscous dissipation on free convective flow past an exponentially accelerated infinite vertical porous plate with Newtonian heating and mass diffusion.

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.

The learning outcomes are as follows: to familiarize students with the concept of segmentation, targeting and positioning; to make students understand the need and process of building a brand; to help students to identify the market gap and meet customer’s requirement by delivering the right value proposition; and to examine the feasibility of business opportunity, develop a business plan and run a successful firm.

This case is about the quest of three MBA students who accidentally get into argument about footwear brands. This argument leads them to Punjabi ethnic footwear popularly known as “Punjabi Jutti.” They decide to understand the background of “Punjabi Jutti” and the possibility of developing a brand for the same. An extensive research was carried out through the various online and offline platforms. The research included searching through the existing literature, collecting data from the various online platforms such as e-commerce websites and interviews from the field. The research revealed that this traditional artwork is an unorganized sector. The manufacturers and marketers are two main parts of this business. However, the mainstay of the business is the skilled labors who know the art of making “Punjabi Jutti.” This art has been inherited by them from their previous generations. Also, it was found that there was good demand of the “Punjabi Jutti” in India and it was exported to various countries as well. Customers had a mix response toward these products. This extensive research has now put these students in a dilemma as to what should be the next step. Should they step into this business by creating their own brand? Will this entrepreneurship venture be sustainable? If they created a brand for the “Punjabi Jutti” then what kind of brand it would be?

Post graduate, entrepreneurs.

Teaching Notes are available for educators only.

CSS 3: Entrepreneurship.

The purpose of this paper is to evaluate tourist destinations’ image based on the attributes obtained from the extant literature using correspondence analysis.

This study is aimed at measuring and illustrating destination image of tourism destinations perceived by domestic tourists. Five tourism destinations – Ooty, Shimla, Manali, Mussoorie and Mount Abu were selected as the subject of the study. Based on a representative sample of 800 respondents from the surveys across destinations, correspondence analysis was employed to illustrate an attribute based comparative analysis of the destination image of the tourist destinations.

Findings reveal that the attribute natural attraction was positively perceived by respondents across all destinations and the attribute infrastructure emerged as an area in need of dire attention. Further, the most dominant attributes which marked destinations’ positioning were – local cuisine and food outlets, hotels and restaurants, famous handicraft and parking facilities.

The findings of this study need to be integrated with qualitative studies to explore the underlying reasons for the perceived destination image.

These results provide direction to policy makers and practitioners to visualize their destinations’ competitive standing relative to their competitors’ strengths and weaknesses. This tourist-derived intelligence presents an opportunity to take advantage of its current position, or if necessary, optimally reposition itself.

This paper documents research that was the first to systematically capture and comparatively illustrate the destination image of Indian tourist destinations.

In cultivation, early harvest offers farmers an opportunity to increase production while decreasing the chances of lower crop production rates, ensuring that the economy remains balanced. The significant reason is to predict the disease in plants and distinguish the type of syndrome with the help of segmentation and random forest optimization classification. In this investigation, the accurate prior phase of crop imagery has been collected from different datasets like cropscience, yesmodes and nelsonwisc . In the current study, the real-time earlier state of crop images has been gathered from numerous data sources similar to crop_science, yes_modes, nelson_wisc dataset.

In this research work, random forest machine learning-based persuasive plants healthcare computing is provided. If proper ecological care is not applied to early harvesting, it can cause diseases in plants, decrease the cropping rate and less production. Until now different methods have been developed for crop analysis at an earlier stage, but it is necessary to implement methods to advanced techniques. So, the detection of plant diseases with the help of threshold segmentation and random forest classification has been involved in this investigation. This implemented design is verified on Python 3.7.8 software for simulation analysis.

In this work, different methods are developed for crops at an earlier stage, but more methods are needed to implement methods with prior stage crop harvesting. Because of this, a disease-finding system has been implemented. The methodologies like “Threshold segmentation” and RFO classifier lends 97.8% identification precision with 99.3% real optimistic rate, and 59.823 peak signal-to-noise (PSNR), 0.99894 structure similarity index (SSIM), 0.00812 machine squared error (MSE) values are attained.

The implemented machine learning design is outperformance methodology, and they are proving good application detection rate.