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This paper investigated the possibilities of implementing inclusive education in the tertiary-level language classrooms and suggests new teaching methodologies adhering to the guidelines of multicultural education (MCE) framework. It explored how Indian teachers fostered social inclusivity in ESP (English for Specific Purposes) classrooms and documented the methods used by the language teachers to sustain a socially inclusive environment in the classroom.

This qualitative study undertaken with 17 faculty members using online interviews and surveys as tools revealed the challenges faced by the teachers.

The results have implications towards teacher training as there is a clear dearth of teacher strategies to foster an equitable and inclusive learning environment inside the classroom.

Classrooms are the sources of values and perspectives, and teachers are responsible for providing equal opportunities to students who are otherwise marginalised in society.

Inclusive education aims at providing equal opportunities to people despite the differences in terms of race, class, caste, region, religion, gender, sexuality, ethnicity and disabilities. India being a multilingual and multicultural country, inculcating values in students to enable them to reflect beyond these differences becomes important.

Farmers producer organisations (FPOs) play the most crucial role in the agriculture supply chain system, aiming to redress the balance between farming and marketing activities of agricultural produce. The purpose of this study is to assess the performance of FPOs using data envelopment analysis (usually referred to as DEA) on 34 FPO units selected from the state of Rajasthan.

One of the most commonly used techniques to examine business performance is the application of DEA. The application of DEA requires the selection of inputs and outputs. This study takes three inputs and three outputs based on the insights drawn from the field survey. While the input variables consist of total assets, paid-up capital and the number of economic activities, the three output variables are turnover, net profit and number of members benefitted. Broadly, these variables encapsulate the operational performance of the business units.

This study’s findings reveal that the estimated relative efficiency score of the input-oriented CCR (Charnes, Cooper, and Rhodes) model ranges from 0.06 to 1. Interestingly, only one FPO has reported a relative efficiency (RE) score of one, whereas the remaining FPOs fall below the efficiency frontier. However, 15 FPOs report an RE score of one in the output-oriented CCR approach. Considering the estimates obtained in the input- and output-oriented BCC (Banker, Charnes and Cooper) models, this study found that about 20% of the FPOs report an efficiency score greater than 0.80. Moreover, three FPOs are on the frontier line. An examination of the scale efficiency score in the input-oriented model, 45% of the FPOs have an efficiency score greater than 0.80, whereas almost all FPOs achieve a scale efficiency score greater than 0.80 in the output-oriented model. Overall, the results imply that the FPOs should place greater emphasis on the efficient utilisation of the inputs to enhance the overall business performance and productivity.

The findings of this study provide vital insights into the specific inputs and outputs that determine the performance efficiency of FPOs and identify the potential areas for improving the existing inefficient FPOs.

This study contributes to the repository of the existing empirical studies in three distinct ways. First, the authors hardly found any previous studies that quantitatively assess the business performance of FPOs using the DEA technique. Second, the effort to identify the slacks associated with each input and output variable in input- and output-oriented models gives insights on improvable areas for inefficient FPOs. Third, the authors attempt to demystify the empirical obfuscations by highlighting the major challenges FPOs face in the state of Rajasthan.

The present study aimed to assess performance of Industry 4.0 (I4.0) in case organization by considering potential performance measures and analysis using scoring approach.

50 performance measures grouped into five dimensions namely manufacturing management, manufacturing economics, manufacturing strategy, manufacturing technology and workforce were considered for the analysis. The study had been done with relevance to automotive component manufacturing organization. Further, questionnaire for each performance measure was developed to gather expert inputs regarding different performance aspects of I4.0 in case organization. Reliability of the expert responses towards questionnaire was assessed by computing Cronbach's alpha (a) using Statistical Package for the Social Sciences (SPSS) software.

Findings of the study revealed overall I4.0 performance index (OIPI) of 0.71, i.e. 71% signifying improvement scope of 29% pertaining to I4.0 adoption. Gap analysis was performed across dimensions and performance measures to realize the weaker areas. Gap analysis revealed workforce dimension with highest gap and manufacturing management with lowest gap. The gaps that obstruct performance of I4.0 are being recognized and proposals for improvement were provided to the industrial practitioners. Based on further analysis, dimensions and performance measures found to be weaker.

The study helped industrial practitioners and managers to create the foundation for evaluating performance of I4.0-focused organization. Industry practitioners can employ the study to understand different performance measures with respect to different dimensions and realize the significance of I4.0 adoption.

The identification of performance dimensions and measures for I4.0 performance measurement and assessment using scoring approach is the original contribution of the authors.

This study aims to reveal the influences of three-dimensional (3D) printing parameters such as layer heights (0.1 mm, 0.2 mm and 0.4 mm), infill rates (40, 70 and 100%) and geometrical property as tapered angle (0, 0.25 and 0.50) on vibrational behavior of 3D-printed polyethylene terephthalate glycol (PET-G) tapered beams with fused filament fabrication (FFF) method.

In this performance, all test specimens were modeled in AutoCAD 2020 software and then 3D-printed by FFF. The effects of printing parameters on the natural frequencies of 3D-printed PET-G beams with different tapered angles were also analyzed experimentally, and numerically (finite element analysis) via Ansys APDL 16 program. In addition to vibrational properties, tensile strength, elasticity modulus, hardness, and surface roughness of the 3D-printed PET-G parts were examined.

It can be stated that average surface roughness values ranged between 1.63 and 6.91 µm. In addition, the highest and lowest hardness values were found as 68.6 and 58.4 Shore D. Tensile strength and elasticity modulus increased with the increase of infill rate and decrease of the layer height. In conclusion, natural frequency of the 3D-printed PET-G beams went up with higher infill rate values though no critical change was observed for layer height and a change in tapered angle fluctuated the natural frequency values significantly.

The influence of printing parameters on the vibrational properties of 3D-printed PET-G beams with different tapered angles was carried out and the determination of these effects is quite important. On the other hand, with the addition of glass or carbon fiber reinforcements to the PET-G filaments, the material and vibrational properties of the parts can be examined in future works.

As a result of this study, it was shown that natural frequencies of the 3D-printed tapered beams from PET-G material can be predicted via finite element analysis after obtaining material data with the help of mechanical/physical tests. In addition, the outcome of this study can be used as a reference during the design of parts that are subjected to vibration such as turbine blades, drone arms, propellers, orthopedic implants, scaffolds and gears.

It is believed that determination of the effect of the most used 3D printing parameters (layer height and infill rate) and geometrical property of tapered angle on natural frequencies of the 3D-printed parts will be very useful for researchers and engineers; especially when the importance of resonance is known well.

When the literature efforts are scanned in depth, it can be seen that there are many studies about mechanical or wear properties of the 3D-printed parts. However, this is the first study which focuses on the influences of the both 3D printing parameters and tapered angles on the vibrational behaviors of the tapered PET-G beams produced with material extrusion based FFF method. In addition, obtained experimental results were also supported with the performed finite element analysis.

Sustainable development goals (SDGs) are gaining significant importance in the current environment. Many businesses are keen to adopt SDGs to get a competitive edge. There are certain challenges in realigning the present working scenario for sustainable development, which is a primary concern for society. Various firms are adopting sustainable engineering (SE) practices to tackle such issues. Artificial intelligence (AI) is an emerging technology that can help the ineffective adoption of sustainable practices in an uncertain environment. In this regard, there is a need to review the current research practices in the field of SE in AI. The purpose of the present study is to comprehensive review the research trend in the field of SE in AI.

This work presents a review of AI applications in SE for decision-making in an uncertain environment. SCOPUS database was considered for shortlisting the articles. Specific keywords on AI, SE and decision-making were given, and a total of 127 articles were shortlisted after implying inclusion and exclusion criteria.

Bibliometric study and network analyses were performed to analyse the current research trends and to see the research collaboration between researchers and countries. Emerging research themes were identified by using structural topic modelling (STM) and were discussed further.

Research propositions corresponding to each research theme were presented for future research directions. Finally, the implications of the study were discussed.

This work presents a systematic review of articles in the field of AI applications in SE with the help of bibliometric study, network analyses and STM.

To achieve changing customer demands, organizations are striving hard to embrace cutting-edge technologies facilitating a high level of customization. Industry 4.0 (I4.0) implementation aids in handling big data that could help generate customized products. Lean six sigma (LSS) depends on data analysis to execute complex problems. Hence, the present study aims to empirically examine the key operational characteristics of LSS and I4.0 integration such as principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 technologies and performance measures.

To stay competitive in the market and quickly respond to market demands, industries need to go ahead with digital transformation. I4.0 enables building intelligent factories by creating smart manufacturing systems comprising machines, operators and information and communication technologies through the complete value chain. This study utilizes an online survey on Operational Excellence professionals (Lean/Six Sigma), Managers/Consultants, Managing Directors/Executive Directors, Specialists/Analysts/Engineers, CEO/COO/CIO, SVP/VP/AVP, Industry 4.0 professionals and others working in the field of I4.0 and LSS. In total, 83 respondents participated in the study.

Based on the responses received, reliability, exploratory factor analysis and non-response bias analysis were carried out to understand the biasness of the responses. Further, the top five operational characteristics were reported for LSS and I4.0 integration.

One of the limitations of the study is the sample size. Since I4.0 is a new concept and its integration with LSS is not yet explored; it was difficult to achieve a large sample size.

Organizations can utilize the study findings to realize the top principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 tools and performance measures with respect to LSS and I4.0 integration. Moreover, these operational characteristics will help to assess the organization's readiness before and after the implementation of this integration.

The authors' original contribution is the empirical investigation of operational characteristics responsible for I4.0 and LSS integration.

Supply chain finance is an emergent research area dealing with the financial performance of a firm throughout its supply chain. It has been drawing significant attention among industrial practitioners and researchers. However, there is need to identify improvements in supply chain finance (SCF) practices to ensure sustainable growth. In recent years, circular economy practices are being adopted worldwide with a motivation to achieve the 17 Sustainable Development Goals (SDGs). Moreover, integration of circular economy practices in the financial aspects of supply chain is still in infant age.

Adoption of circular SCF in firms enhances both restorative and regenerative capacities of the firm. In this regard, this study aims to review articles on circular practices in SCF. The study identified 329 articles related to circular practices and sustainable practices in SCF from the Scopus database. The shortlisted articles were reviewed and discussed.

The findings of the study help to recognize the most influential and productive research in circular SCF in terms of journals and trends. Further research is recommended to explore this area in depth to recognize potential integrating factors that help in smooth acceptance of circular finance in supply chains.

Bibliometric and network analyses were performed to identify research trends and networks in the field of circular SCF. In addition, emerging research themes in the field of circular SCF were identified and discussed, and research propositions are proposed to delineate future research directions.

Industry 4.0 is recognised as a competitive strategy that helps implementers optimise their value chain. However, its adoption poses several challenges. This study investigates and ranks the drivers and barriers to implementing Industry 4.0 in the Thai sugar industry, the world's second-largest sugar exporter. It also evaluates the industry's readiness for Industry 4.0.

The drivers and impediments were identified based on a systematic literature review (SLR) and further investigated using a questionnaire, expert interviews, Pearson's correlation and nonparametric statistical analyses. The IMPULS model was used to assess the industry's readiness.

Most companies expect to minimise costs, develop employees and improve various elements of operational performance and data tracking capability. Thai sugar producers are still at a low readiness level to deploy Industry 4.0. High investment is the major challenge. Small businesses struggle to hire competent employees, collaborate with a highly credible technology provider and adapt to new solutions.

The findings can serve as a benchmark or guide for sugar manufacturers and companies in other sectors, where Industry 4.0 technologies are not yet widely utilised, to overcome existing roadblocks and make strategic decisions. They can also assist governments in developing policies that foster digital transformation and increase national competitiveness.

There is a scarcity of research on Industry 4.0 execution in the sugar industry. This study addresses this gap by investigating the reasons for the hesitancy of sugar producers to pursue Industry 4.0 and proposing solutions.

The manufacturing sector is highly competitive and operationally complex. Therefore, the strategic alignment between operational excellence methodologies and Industry 4.0 technologies is one of the issues that need to be addressed. The main aim of the study is to determine the critical factors of strategic alignment between operational excellence methodologies and Industry 4.0 technologies for manufacturing industries and make comparative analyses between automotive, food and textile industries in terms of strategic alignment between operational excellence methodologies and Industry 4.0 technologies.

First, determining the critical factors based on literature review and expert opinions, these criteria are weighted, and analytical hierarchy process is run to calculate the weights of these criteria. Afterward, the best sector is determined by the grey relational analysis method according to the criteria for the three manufacturing industries selected for the study.

As a result of AHP, “Infrastructure for Right Methodology, Techniques and Tools, is in the first place,” Organizational Strategy, is in the second place, while the third highest critical factor is “Capital Investment”. Moreover, based on grey relational analysis (GRA) results, the automotive industry is determined as the best alternative in terms of strategic alignment between operational excellence (OPEX) methodologies and I4.0 technologies.

This study is unique in that it is primarily possible to obtain the order of importance within the criteria and to make comparisons between three important manufacturing industries that are important for the economies of the world.

The study examines the remote integration process of advanced manufacturing technology (AMT) into the production system and identifies key challenges and mitigating actions for a smoother introduction and integration process.

The study adopts a case study approach to a cyber-physical production system at an industrial technology center using a mobile robot as an AMT.

By applying the plug-and-produce concept, the study exemplifies an AMT's remote integration process into a cyber-physical production system in nine steps. Eleven key challenges and twelve mitigation actions for remote integration are described based on technology–organization–environment theory. Finally, a remote integration framework is proposed to facilitate AMT integration into production systems.

The study presents results purely from a practical perspective, which could reduce dilemmas in early decision-making related to smart production. The proposed framework can improve flexibility and decrease the time needed to configure new AMTs in existing production systems.

The area of remote integration for AMT has not been addressed in depth before. The consequences of lacking in-depth studies for remote integration imply that current implementation processes do not match the needs and the existing situation in the industry and often underestimate the complexity of considering both technological and organizational issues. The new integrated framework can already be deployed by industry professionals in their efforts to integrate new technologies with shorter time to volume and increased quality but also as a means for training employees in critical competencies required for remote integration.