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Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in Manufacturing Industries.

This study formulated a framework of six factors and twenty-eight variables (explored in the literature). A hybrid approach of Multi-Criteria Decision-Making Technique (MCDM) was employed in the framework to prioritize, rank and establish interrelationships between factors and variables grouped under them.

The research findings reveal that the “Manufacturing Process” is the most essential factor, while “Integration Manufacturing with Maintenance” is highly impactful on the other factors to eliminate the flaws that may cause system breakdown. The findings of this study also provide a ranking order for variables to increase the performance of factors that will assist manufacturers in reducing maintenance efforts and enhancing process efficiency.

The ranking order developed in this study may assist manufacturers in reducing maintenance efforts and enhancing process efficiency. From the manufacturer’s perspective, this research presented MAT as a key aspect in dealing with the complexity of manufacturing operations in manufacturing organizations. This research may assist industrial management with insights into how they can lower the probability of breakdown, which will decrease expenditures, boost productivity and enhance overall efficiency.

This study is an original contribution to advancing MAT’s theory and empirical applications in manufacturing organizations to decrease breakdown probability.

This exploratory study aims to discover the different forms of challenges encountered by school stakeholders, including students, teachers, parents and management due to the coronavirus disease 2019 (COVID-19) pandemic.

Qualitative methodology was deployed for the study. A purposive sampling technique was used to select the respondents for a semi-structured interview. Data were examined using interpretative phenomenological analysis (IPA).

It was found that each stakeholder faced four different challenges: mental distress, physical immobility, financial crunches and technological concerns. Findings suggest that teachers are experiencing higher financial, technological and physical challenges as compared to other stakeholders followed by parents.

This paper discusses the major challenges faced by each stakeholder along with the opportunities. These findings will be useful for educationists, regulatory authorities, policymakers and management of educational institutions in developing countries to revisit their policy frameworks to develop new strategies and processes for the smooth implementation of remote learning during a period of uncertainty.

The purpose of this study is to perform comprehensive investigation to assess the mechanical properties of nano-modified ternary cement concrete blend. Nano silica (NS) (1%, 2% and 3%) and waste marble dust powder (MD) (5%, 10% and 15%) was incorporated as a fractional substitution of cement in the concrete matrix.

In this experimental study, 10 cementitious blends were prepared and tested for compressive strength, flexural strength, splitting tensile strength and static modulus of elasticity. The microstructural characteristics of these blends were also explored using a scanning electron microscope along with energy dispersive spectroscopy and X-ray reflection.

The results indicate an enhancement in mechanical properties and refinement in pore structure due to improved pozzolanic activities of NS and the filling effect of MD.

To the best of the authors’ knowledge, no study has reported the mechanical and microstructural behavior of concrete containing marble and NS.

This paper aims to evaluate the progress made in achieving sustainable development goal-2 (SDG 2) in India, with a focus on ending hunger, ensuring food security, improving nutrition and promoting sustainable agriculture. The assessment uses data from SDG Index reports, which offer a comprehensive overview of the advancements made by 28 states and 8 union territories (UTs) in India.

The evaluation is based on information derived from three editions of the SDG Index reports, initially published in 2018 and subsequently in 2019 and 2020. These reports provide a detailed analysis of the status and achievements of different states and UTs in relation to SDG 2. The categorization of states and UTs into aspirant, performer, front runner and achiever categories serves as a crucial framework for assessing the progress.

Despite concerted efforts by India, the majority of states and UTs are positioned in the aspirant and performer categories, suggesting that significant challenges persist in achieving SDG 2 targets. The results emphasize the necessity for stronger measures to elevate states and UTs to the categories of front-runners and achievers. The persistent challenges of malnutrition, hunger and their economic ramifications require immediate and strategic interventions to address these pressing concerns.

This paper contributes to the existing literature by providing a comprehensive analysis of the progress towards SDG 2 in India, using the insights from the SDG Index reports. The categorization framework used in this assessment offers a nuanced understanding of the challenges faced by different regions, highlighting the original contribution of this study. The findings underscore the urgency of targeted efforts to address malnutrition, hunger and related issues, emphasizing the importance of sustained commitment to achieving SDG 2 for the overall well-being of vulnerable populations.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

The utilisation of renewable energy sources for generating electricity and potable water is one of the most sustainable approaches in the current scenario. Therefore, the current research aims to design and develop a novel co-generation system to address the electricity and potable water needs of rural areas.

The cogeneration system mainly consists of a solar parabolic dish concentrator (SPDC) system with a concentrated photo-voltaic module at the receiver for electricity generation. It is further integrated with a low-temperature thermal desalination (LTTD) system for generating potable water. Also, a novel corn cob filtration system is introduced for the pre-treatment to reduce the salt content in seawater before circulating it into the receiver of the SPDC system. The designed novel co-generation system has been numerically and experimentally tested to analyse the performance at Karaikal, U.T. of Puducherry, India.

Because of the pre-treatment with a corn cob, the scale formation in the pipes of the SPDC system is significantly reduced, which enhances the efficiency of the system. It is observed that the conductivity, pH and TDS of seawater are reduced significantly after the pre-treatment by the corncob filtration system. Also, the integrated system is capable of generating 6–8 litres of potable water per day.

The integration of the corncob filtration system reduced the scaling formation compared to the general circulation of water in the hoses. Also, the integrated SPDC and LTTD systems are comparatively economical to generate higher yields of clean water than solar stills.

The purpose of this paper is to develop an organized structure for damage detection of a cracked cantilever beam using finite element method and experimental method technique.

Due to presence of cracks the dynamic characteristics of structure change. The change in dynamic behavior has been used as one of the criteria of fault diagnosis for structures. Major characteristics of the structure which undergo change due to presence of crack are: natural frequencies, the amplitude responses due to vibration and the mode shapes. Therefore, an attempt has been made to formulate a smart technique for minimizing the amplitude of vibration for crack cantilever beam structures. In the analysis both single and double cracks are taken into account.

The results of the active vibration control experiments proved that piezoelectric sensor/actuator pair is an effective sensor and actuator configuration for active vibration control to reduce the amplitude of vibration for closed-loop system.

It is necessary that structures must safely work during its service life, but damages initiate a breakdown period on the structures which directly affect the industrial growth. It is a recognized fact that dynamic behavior of structures changes due to presence of crack. It has been observed that the presence of cracks in structures or in machine members leads to operational problem as well as premature failure.

The conflicting results on the corrosion characteristics of aluminium matrix composites reinforced with agrarian waste have stimulated an investigation on the hardness and corrosion rate of sugar palm fibre ash (SPFA) reinforced LM26 Al/alloy composite by varying the SPFA from 0 to 10 wt% in an interval of 2 wt%. This paper aims to discuss the aforementioned issue.

The composites were produced via stir-casting and the hardness was determined using a Vickers hardness testing machine, corrosion rate was examined through the weight loss method by immersion in 0.5, 1.0 and 1.5 M hydrochloric acid (HCl) at temperatures of 303, 318, and 333 K for the maximum duration of 120 h. The morphological study was conducted using a scanning electron microscope (SEM) on the samples before and after immersion in HCl.

The incorporation of SPFA improved the hardness of the alloy from 58.22 to 93.62 VH after 10 wt% addition. The corrosion rate increases with increased content of SPFA, the concentration of HCl and temperature. The least corrosion rate of 0.0272 mpy was observed for the LM26 Al alloy in 0.5 M after 24 h while the highest corrosion rate of 0.8511 mpy was recorded for LM26 Al/10 wt% SPFA in 1.5 M HCl acid after 120 h. The SEM image of corroded samples revealed an increased number of pits with increased SPFA content.

The work is limited to SPFA up to 10 wt% as reinforcement in LM26 Al alloy, the use of HCl as corrosion medium, temperatures in the range of 303–333 K, and a weight loss method were used to evaluate the corrosion rate.

The corrosion rate was determined for LM26 Al/SPFA composites with various amounts of SPFA in 0.5, 1.0 and 1.5 M HCl at 303, 318 and 333 K and compared with the matrix alloy.

This study examined the relationship between adult respondents' COVID-19 risk perception and its impact on changes in eating habits, physical activity, alcohol consumption, and smoking.

A cross-sectional online questionnaire was used to collect data during the first wave of the pandemic, in the European spring and summer of 2020. Kruskal–Wallis and Pearson chi-squared tests were used to determine the associations between the consumers' COVID-19 risk perception and the respondents' country of origin. The respondents were primarily university employees and students from four European countries (the Czech Republic, France, the United Kingdom, and Italy).

The study showed significant changes in lifestyle behaviours of the respondents during the COVID-19 pandemic compared with the pre-outbreak period. Approximately half of all respondents reported a decrease in alcohol consumption, smoking, and physical activity, while eating habits among European consumers showed trends towards both healthier and less healthy dietary patterns. The most significant changes were recorded in reducing alcohol consumption, smoking, and physical activity among almost half of the respondents. Positive COVID-19 test experience, age, and country of the respondents had a negative influence, whereas healthy food consumption and alcohol consumption had a positive influence on the COVID-19 related risk perception.

The fear of the COVID-19 outbreak together with the restrictions imposed by national governments in response to the pandemic fundamentally affected the respondents' lifestyles. Understanding these changes can help establish interventions to alleviate the adoption of negative lifestyles and attitudes in subsequent waves of the COVID-19 pandemic or other similar situations.

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.

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.

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.

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.

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.