Lino Costa, Deepak Rajput, Kathleen Lansford, Wenqiang Yue, Alexander Terekhov and William Hofmeister
The purpose of this paper is to develop a simple, easy to implement powder delivery strategy for solid freeform fabrication (SFF) processing.
Abstract
Purpose
The purpose of this paper is to develop a simple, easy to implement powder delivery strategy for solid freeform fabrication (SFF) processing.
Design/methodology/approach
A specially designed “tower nozzle” located at the center of the processing area dispenses the feedstock powders continuously and uniformly onto the processing area, where powders accumulate progressively as a flat powder bed. During the dispensing, powders are selectively consolidated by melting and solidification using a laser beam which was scanned in a predefined pattern using a galvo‐mirror scan head.
Findings
Experiments performed with AISI H13 steel show that the tower nozzle powder delivery strategy is suitable for SFF processing.
Practical implications
Both powder delivery and laser consolidation are performed simultaneously and without interruption with simple apparatus. No powder delivery scrapers or rollers are used.
Originality/value
The main characteristics of a prototype tower nozzle and the typical processing conditions used to form thin wall AISI H13 steel shapes are presented.
Details
Keywords
Deepak Byotra and Sanjay Sharma
This study aims to investigate the performance improvement of journal bearing by applying the arc-shaped textures on various regions of bearing expressly full, second half and…
Abstract
Purpose
This study aims to investigate the performance improvement of journal bearing by applying the arc-shaped textures on various regions of bearing expressly full, second half and pressure increasing regions operating with and without nanoparticles in the lubricant.
Design/methodology/approach
The Reynolds equation is solved numerically by using the finite element method to obtain static performance parameters such as load-carrying capacity (LCC) and coefficient of friction (COF), which are then compared with untextured bearing at eccentricity ratios of 0.2 to 0.8. Aluminum oxide (Al2O3) and copper oxide (CuO) nanoparticles additives are used, and viscosity variation due to the addition of additives in the base lubricant is computed for considering the range of temperatures 50 to 90°C at a weight fraction of 0.1 to 0.5% by using an experimentally validated regression model.
Findings
The results indicate that the maximum LCC and the lower COF are found in the pressure-increasing region. A maximum increase of 34.42% is observed in the pressure-increasing region without nanoparticles, and furthermore, with the addition of Al2O3 and CuO nanoparticles in lubricants in the same region, the LCC increased to 21 and 24%, respectively.
Originality/value
Designers should use optimal parameters from the present work to achieve high bearing performance.
Details
Keywords
Thamaraiselvan Natarajan, P. Pragha, Krantiraditya Dhalmahapatra and Deepak Ramanan Veera Raghavan
The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and…
Abstract
Purpose
The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and uncovers a deeper understanding of user opinions and trends within this digital realm. Further, sentiments signify the underlying factor that triggers one’s intent to use technology like the metaverse. Positive sentiments often correlate with positive user experiences, while negative sentiments may signify issues or frustrations. Brands may consider these sentiments and implement them on their metaverse platforms for a seamless user experience.
Design/methodology/approach
The current study adopts machine learning sentiment analysis techniques using Support Vector Machine, Doc2Vec, RNN, and CNN to explore the sentiment of individuals toward metaverse in a user-generated context. The topics were discovered using the topic modeling method, and sentiment analysis was performed subsequently.
Findings
The results revealed that the users had a positive notion about the experience and orientation of the metaverse while having a negative attitude towards the economy, data, and cyber security. The accuracy of each model has been analyzed, and it has been concluded that CNN provides better accuracy on an average of 89% compared to the other models.
Research limitations/implications
Analyzing sentiment can reveal how the general public perceives the metaverse. Positive sentiment may suggest enthusiasm and readiness for adoption, while negative sentiment might indicate skepticism or concerns. Given the positive user notions about the metaverse’s experience and orientation, developers should continue to focus on creating innovative and immersive virtual environments. At the same time, users' concerns about data, cybersecurity and the economy are critical. The negative attitude toward the metaverse’s economy suggests a need for innovation in economic models within the metaverse. Also, developers and platform operators should prioritize robust data security measures. Implementing strong encryption and two-factor authentication and educating users about cybersecurity best practices can address these concerns and enhance user trust.
Social implications
In terms of societal dynamics, the metaverse could revolutionize communication and relationships by altering traditional notions of proximity and the presence of its users. Further, virtual economies might emerge, with virtual assets having real-world value, presenting both opportunities and challenges for industries and regulators.
Originality/value
The current study contributes to research as it is the first of its kind to explore the sentiments of individuals toward the metaverse using deep learning techniques and evaluate the accuracy of these models.
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Keywords
Ashutosh Samadhiya, Rajat Agrawal, Sunil Luthra, Anil Kumar, Jose Arturo Garza-Reyes and Deepak Kumar Srivastava
The purpose of this research is to establish a conceptual model to understand the impact of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) on the transition of a…
Abstract
Purpose
The purpose of this research is to establish a conceptual model to understand the impact of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) on the transition of a Circular Economy (CE). Also, the paper explores the combined impact of TPM, I4.0 and CE on the sustainability performance (SP) of manufacturing firms.
Design/methodology/approach
The conceptual model is proposed using the dynamic capability view (DCV) and empirically validated by partial least squares-structural equation modelling (PLS-SEM) using 304 responses from Indian manufacturing firms.
Findings
The results suggest that I4.0 positively impacts TPM, CE and SP, also showing TPM's positive impact on CE and SP. In addition, CE has a positive influence on the SP of manufacturing firms. Furthermore, CE partially mediates the relationship between I4.0 and SP with TPM and SP. The study also identifies TPM, I4.0 and CE as a new bundle of dynamic capabilities to deliver SP in manufacturing firms.
Originality/value
The present research adds to the knowledge and literature on DCV by identifying the importance of CE in the settings of I4.0 and TPM, especially in the context of sustainability. Also, the current study offers a new set of dynamic capabilities and provides some significant future recommendations for researchers and practitioners.
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Anupama Panghal, Priyanka Vern, Rahul S Mor, Deepak Panghal, Shilpa Sindhu and Shweta Dahiya
3D food printing technology is an emerging smart technology, which because of its inbuilt capabilities, has the potential to support a sustainable supply chain and environmental…
Abstract
Purpose
3D food printing technology is an emerging smart technology, which because of its inbuilt capabilities, has the potential to support a sustainable supply chain and environmental quality management. This new technology needs a supportive ecosystem, and thus, this paper identifies and models the enablers for adopting 3D printing technology toward a sustainable food supply chain.
Design/methodology/approach
The enablers were identified through an extensive literature review and verified by domain experts. The identified enablers were modelled through the hybrid total interpretive structural modelling approach (TISM) and the decision-making trial and evaluation laboratory (DEMATEL) approach.
Findings
It emerged that stakeholders need technical know-how about the 3D printing technology, well supported by a legal framework for clear intellectual property rights ownership. Also, the industry players must have focused and clear strategic planning, considering the need for sustainable supply chains. Moreover, required product innovation as per customer needs may enhance the stakeholders' readiness to adopt this technology.
Practical implications
The framework proposed in this research provides managers with a hierarchy and categorization of adoption enablers which will help them adopt 3D food printing technology and improve environmental quality.
Originality/value
This research offers a framework for modelling the enablers for 3D food printing to develop a sustainable food supply chain using the TISM and DEMATEL techniques.
Details
Keywords
Pankaj Kumar, Bhavna Bajpai, Deepak Omprakash Gupta, Dinesh C. Jain and S. Vimal
The purpose of this study/paper To focus on finding COVID-19 with the help of DarkCovidNet architecture on patient images.
Abstract
Purpose
The purpose of this study/paper To focus on finding COVID-19 with the help of DarkCovidNet architecture on patient images.
Design/methodology/approach
We used machine learning techniques with convolutional neural network.
Findings
Detecting COVID-19 symptoms from patient CT scan images.
Originality/value
This paper contains a new architecture for detecting COVID-19 symptoms from patient computed tomography scan images.
Details
Keywords
Rahul Nilakantan, Deepak Iyengar and Shashank Rao
Financial inclusion remains one of the most promising avenues to bring about development for the poorest segments of society. A substantial body of work has looked into financial…
Abstract
Purpose
Financial inclusion remains one of the most promising avenues to bring about development for the poorest segments of society. A substantial body of work has looked into financial inclusion, especially in terms of microfinance, but much of it has been anecdotal and case-based. There is little scholarship that broadly investigates how microfinance-funded businesses choose to use the loans, especially given the ever-present competition for resources that such businesses face regarding which investment priority to pursue. In addition, the efficacy of these investments in terms of subsequent profitability remains unexplored, and so too does the influence of the entrepreneur’s embeddedness in the local community. The paper aims to discuss these issues.
Design/methodology/approach
This study reports the results from a field investigation of 927 women entrepreneurs who received a microfinance loan from a leading Indian microfinance institution. Logit and OLS regression models are employed in a moderation analysis by way of hierarchical regression.
Findings
Results indicate that access to microfinance increases the likelihood that the enterprise invests in marketing infrastructure and operational scale. In addition, structural embeddedness has a weakening effect on this relationship for operational scale while having a strengthening effect on the relationship for marketing infrastructure. Finally, operational scale is related to enterprise profitability, while marketing infrastructure is not. These findings suggest that embeddedness in the community is associated with the entrepreneur making sub-optimal choices regarding microfinance utilization.
Originality/value
To our knowledge, this is the first study to investigate the simultaneous marketing and operational impacts of microfinance access. It is also the first study to relate these measures to the profitability of the enterprise, especially in the context of structural embeddedness in the network.
Details
Keywords
Deepak Datta Nirmal, K. Nageswara Reddy and Sujeet Kumar Singh
The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various…
Abstract
Purpose
The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).
Design/methodology/approach
The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.
Findings
The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.
Originality/value
The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.
Details
Keywords
M. Rizwana, Padmalini Singh, N. Ahalya and T. Mohanasundaram
The goal of the present study is to examine the degree of knowledge amongst Indian women about millet grain and its nutritional advantages. Millet is regarded to be five times…
Abstract
Purpose
The goal of the present study is to examine the degree of knowledge amongst Indian women about millet grain and its nutritional advantages. Millet is regarded to be five times more nutritious than rice and wheat. Despite the fact that millet contributes to 10% of India's food grain basket and has an annual production of 18 million tonnes, it is not consumed in the same proportion as mainstream cereals (that is rice and wheat). As a result, the study's primary objective is to determine the level of awareness and consumption pattern of millet amongst Indian women regarding millet grains.
Design/methodology/approach
The research was carried out in the city of Bengaluru in the state of Karnataka, India. For the purpose of study, a sample of 855 female respondents was approached using a non-probability sampling technique known as convenience sampling. The data were gathered through the use of a self-administered structured questionnaire.
Findings
According to the findings of the study, the vast majority of respondents consume millet for preserving overall health. Building self and family immunity is the most important factor with 4.11 mean scores and low standard deviation of 0.985. The results reveal that 80.6% of women in the study are aware of millet but only 62.7% of women are consuming millet. The motivating factors and demotivating factors leading to consumption and non-consumption behaviour, respectively have also been identified. The study also reveals that demographic factors such as age, qualification and income have a direct influence on millet consumption.
Research limitations/implications
The scope of research can be extended to explore the impact of millet consumption on long term health benefits of millet amongst the target respondents. Further, the study can be extended to explore the consumption pattern of millet among different target audience in various parts of India. The media interventions in creating awareness of millet consumption benefits need to be studied for increasing the consumption of millet.
Practical implications
Companies involved in producing Fast Moving Consumer Goods (FMCG) products can be encouraged to produce millet based foods like cereals, biscuits, ready to eat foods etc. Workshops can be organized to raise awareness on how the millet can replace traditional grains in the cooking process.
Social implications
Policy measures may include millet being promoted through technology dissemination, creating awareness about advantages of millet and including millet in the Public Distribution System (PDS). It is also important to promote the cultivation, maintenance and processing of the local variety of millet with competent marketing strategies so as to increase their cultivation comparable to the cash crops. Farmers should be educated on the importance of cultivation of minor millet.
Originality/value
The fast-paced lifestyle of urban Indians has a direct impact on their dietary preferences. The World Health Organization (WHO) recommends that people have a nutritionally balanced diet and engage in regular physical activity to reduce health risks. In India, as a result of women's increased participation in the workforce, women are forced to manage many tasks and obligations, which has detrimental effects on their health. The poor nutritional status of modern-day workers is attributed to a lack of education, lack of awareness and a general disregard for health-related concerns. There is a need to investigate if Indian women are aware of the nutritional benefits of millet grains that are higher in protein.
Details
Keywords
Vanishree Beloor and T.S. Nanjundeswaraswamy
The purpose of this study is to determine the enablers of the quality of work life (QWL) of employees working in the Garment industries.
Abstract
Purpose
The purpose of this study is to determine the enablers of the quality of work life (QWL) of employees working in the Garment industries.
Design/methodology/approach
The study was carried out in a fivefold step. In the first step, the enablers of QWL were identified through an exhaustive literature survey, in the second step identified vital few components through Pareto analysis. Then the third step was followed by exploratory factor analysis (EFA) to further, to identify the precise components and validate the same using confirmatory factor analysis in fourth step. The final step included interpretive structural modeling and Cross-Impact Matrix Multiplication Applied to Classification analysis to model the validated components and determine the interrelationships and linkages.
Findings
Predominant QWL enablers of employees working in the garment industries are training and development, satisfaction in job, compensation and rewards, relation and co-operation, grievance handling, work environment, job nature, job security and facilities.
Research limitations/implications
In this study, the interpretive structural model is designed based on the opinion of the experts who are working in the garment industry considering the responses from employees in garment sectors. The framework can be extended further to the other sectors.
Practical implications
In future, the researchers in QWL may develop a model to quantify the level of employees’ QWL who are working in different sectors. Enablers of QWL are essential, and based on this further statistical analysis can be carried out. This study will provide limelight to the researchers in choosing the valid and reliable set of enablers for the empirical studies. Organizations can get benefit by implementing the outcome of this research for the enhancement of the QWL of employees.
Originality/value
The study was carried out in 133 garment industries where 851 workers constituted the final valid responses that were considered for analysis. The outcomes from the study help administrators, policy and decision-takers in taking decisions to enhance QWL.