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An electrorheological (ER) fluid comprises dielectric particles suspended in an insulating viscous medium. ER lubricants are considered smart lubricants. They have been applied in hydraulic valves, power transmission devices and damping systems. The purpose of this study is to investigate the performance of hydrostatic thrust bearing operating with ER lubricant.

Reynold’s equation was used to model the flow of the ER lubricant in the bearing. The continuous Bingham model was used to express the viscosity of the ER lubricant as a function of yielding stress, applied electric field and shear strain rate. The Reynolds equation is solved using the finite element method (weighted residual approach) to compute the film pressure as a primary variable and the lubricant flow rate, load-carrying capacity, stiffness and damping parameters as associated performance indices.

The effects of the pocket shape, compensating elements and ER lubricant on the bearing performance were investigated. The application of ER lubricant significantly enhanced the load-carrying capacity (48.2%), stiffness (49.8%) and damping (4.95%) of the bearings. Circular and triangular pocket bearings with constant-flow valves have been reported to provide better steady-state and rotor-dynamic performances, respectively.

This study presents the effect of an ER lubricant on the rotor-dynamic performance of hydrostatic thrust bearings with different pocket shapes.

This paper aims to investigate the effect of misalignment on wear of spur gears and on oil degradation using online sensors.

The misalignment effect on gears is created through a self-alignment bearing, and is measured using laser alignment system. Several online sensors such as Fe-concentration sensor, moisture sensor, oil condition sensor, oil temperature sensor and metallic particle sensor are installed in the gear test rig to monitor lubricant quality and wear debris in real time to assess gearbox failure.

Offset and angular misalignments are detected in both vertical and horizontal planes. The failure of misaligned gear is observed at both the ends and on both the surfaces of the gear teeth. Larger-size ferrous and non-ferrous particles are traced by metallic particle sensor due to gear and seal wear caused by misalignment. Scanning electron microscope (SEM) images examine chuck, spherical and flat platelet particles, and confirm the presence of fatigue (pitting) and adhesion (scuffing) wear mechanism. Energy-dispersive X-ray spectroscopy analysis of SEM particles traces carbon (C) and iron (Fe) elements due to gear failure.

Gear misalignment is one of the major causes of gearbox failure and the lubricant analysis is as important as wear debris analysis. A reliable online gearbox condition monitoring system is developed by integrating wear and oil analyses for misaligned spur gear pair in contact.

The purpose of this paper is to explore the nature of rural energy transition in cooking options in India. Although India is aiming to achieve a double-digit economic growth, a large share of rural households still rely on firewood for cooking which not only has serious repercussions of increasing indoor pollution but also has a concomitant adverse effect on women and child morbidity and mortality. However, transition to clean energy options like improved cookstoves for these households may not be necessarily linear. It is often driven or resisted by latent factors such as caste, trust, social capital, information flow, social positioning of clusters that are deeply embedded in the social and cultural norms and values specific to local rural contexts. This has been shown in the present case study that pertains to eight villages in the remote and deprived Purnea district of Bihar and the need for internalizing them in the macro energy policymaking has been established in the paper.

The paper applies a macro foundation research that is complemented by micro foundation tools of fuzzy cognitive mapping-based mental model framework to achieve the purpose of the study. Focused-group discussions and interviews are also conducted to establish the narrative of the paper.

Caste, socio-political position, asset structure, remoteness, culture and technology access affect rural households’ decision making capability that is related to shifting from using the traditionalmeans of firewood and biomass based traditional cookstoves for cooking to adopting improved clean cooking stoves which will enable the transition toward the use of clean rural energy in the eight villages in Bihar chosen for this study.

The findings of the paper have larger implications for the broader macro energy policymaking in the country by taking into account the non-linear, latent factors of village contexts.

The research will help energy policymakers in decision-making and will guide the implementation process of national- and state-level policies on rural energy transition in India.

The findings of the paper will help the smoother implementation of national- and state-level rural energy transition policies for cooking, creating developmental dividends for rural Indian households.

The research is new with regard to the application of non-deterministic fuzzy cognitive mapping-based mental model approach to contribute to the country’s national- and state-level rural energy transition policies.

The use of smart electronic gadgets is proportionately increased during last decades as these gadgets are crafting coziness and relief to the society by making their work easier, effective, etc. These gadgets are the need of today’s working environment for effective planning and work execution. Today, people pertaining to almost every corner of the world are addicted to smart mobile phones, and nowadays, these mobile handsets have become very essential and it is not possible to survive without using them. On the other hand, these smart mobile handsets become inefficient and obsolete over time due to which there is a need to replace the old phones by the new ones, thus creating e-waste. The purpose of this paper is to recognize the significant enablers which are responsible for replacing the existing working mobile phones with the new ones by the end consumers.

The Grey-DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach is proposed by the authors to compute the decision results. The present work is supported by the structural modeling equations for supporting sustainability throughout and recognizes the most significant enablers responsible for creating e-waste by replacing the working mobile phones with the new ones.

The implication for reducing e-waste using a qualitative approach is presented by easy computation steps for collaborating green issues in the present work. The authors explained numerous enablers, which are responsible for handsets replacement by the consumers. The work can aid the companies as well as the government legislations to identify the significant enablers, drivers, factors, attributes, etc., in moving toward green environmental issue; the generation of e-waste by the obsolete existing working handsets due to non-identification of deficient enablers can be insignificant to the society.

The implication of developed Grey-DEMATEL techniques is presented by its integration with the application field of e-waste generation by mobile handsets. The authors attempt to devise a conceptual framework linked with knowledge-based theory. The work is illustrated by the case research to understand its applicability and validity in the present scenario.

The authors attempt to propose a decision model, which will aid in identifying the most significant factorial condition responsible for replacing the existing mobile phones with the new ones by the end consumers. The proposed appraisement module can be used as an investigative tool to build and fabricate a planned environmental progress map for overall business considering environmental domain by the companies.

This study delves into the challenges obstructing the integration of blockchain-enabled smart contracts (BESC) in the construction industry. Its primary objective is to identify these barriers and propose a roadmap to streamline BESC adoption, thereby promoting sustainability and resilience in building engineering.

Employing a unique approach, this study combines the Technology-Organization-Environment-Social (TOE + S) framework with the IF-Delphi-HF-DEMATEL-IFISM methodology. Data is collected through surveys and expert interviews, enabling a comprehensive analysis of BESC implementation barriers.

The analysis reveals significant hindrances in the construction industry’s adoption of BESC. Key obstacles include economic and market conditions, insufficient awareness and education about blockchain technology among stakeholders, and limited digital technology integration in specific cultural and societal contexts. These findings shed light on the complexities faced by the industry in embracing blockchain solutions.

The research makes a significant contribution by combining the TOE + S framework with the IF-Delphi-HF-DEMATEL-IFISM methodology, resulting in a comprehensive roadmap to address barriers in implementing BESC in Sustainable Construction Projects. Noteworthy for its practicality, this roadmap provides valuable guidance for construction stakeholders. Its impact extends beyond the industry, influencing both academic discourse and practical applications.

In the presented research, the authors have conducted the literature review and organised real interviews of fruit retailers (FRs) to construct the advanced hierarchical structural (AHS) chain of macro-micro parameters for measuring the performances of defined fruit supply bazaars (FSBs). Apart from this, the purpose of this paper is to develop the grey set-based scorecard model for solving the proposed AHS chain of macro-micro parameters.

The performance of FSBs is linked with the supply of fruits towards clients under a feasible rate, which circuitously depends upon the evaluation of the economic locality of FSBs. The authors developed an advanced hierarchical structure of macro-micro parameters via a literature survey and considered these parameters based on the sampling score of FRs corresponding to select feasible FSBs/alternatives. Furthermore, the authors developed a grey set-based scorecard model for undertaking the incomplete information of FRs against the hierarchical structure.

It is found that the work is well suited for FRs as they can measure the performances of defined FSBs in accordance with their own opinions under the proposed AHS of macro-micro parameters. Apart from this, the work is useful for benchmarking the vegetable supply bazaars (VSBs) on the replacement of AHS. The proposed hierarchical structure with a grey-based scorecard model is flexible in its nature and can undertake more than 1,000 macro-micro parameters and FRs to access potential decision.

The conducted research work has a precise value for evaluating the economic FSB locality. The overall performance scores of considered FSB localities are computed as (∂₁)=1.991, (∂₂)=2.567 and (∂₃)=2.855, where (∂₃) is found to be more significant than available FSBs. This work can be used for opting the economic locality of VSB too.

Based on the existing literature in the field of green supply chain management (GSCM), the purpose of this paper is to find essential to conceptualize and develop an efficient appraisement platform for the purpose of benchmarking green alternative in supply chain network.

The authors explored multiple approaches, i.e. Višekriterijumsko kompromisno rangiranje (VIKOR), simple additive weighting (SAW) and grey relational analysis (GRA) by amalgamating fuzzy sets theory to select the most appropriate alternative for GSCM. The work is supported by triangular fuzzy number sets to choose the green alternative industry among available industries, while dealing with the uncertainty and vagueness in GSCM. A case study is exposed to identify strong and weak indices and to exhibit the feasibility of the proposed work.

It is requisite by the managers of many firms to identify the strong and weak indices relating their firms. Thus, the authors presented an approach for measuring and appraising the performance of the selected green alternative by determining the strong and weak indices. The presented work illustrates the performance measurement model that identifies comprehensive GSCM practices of the firms. The presented work incorporates green supply chain activities to support environmental sustainability throughout the supply chain.

GSCM is necessary to the firms, as it considers impact onto the environment due to their supply chain activities. The authors build decision support system to facilitate the managers of various firms for modeling green practices in their decision making. The authors attempt to devise a conceptual framework linked with knowledge-based theory.

The authors conceptualized VIKOR, SAW and GRA methodology to rank and benchmark the green performance of distinguish alternative industries among available industries. Additionally, the performance measurement model for the selected significant green alternative is presented for determining the strong and weak indices.

Today, industrial revolutions demands advanced technologies, means, mediums, tactics and so forth for optimizing their operating behavior and opportunities. It is probed that the effectual results can be seized into system by not only developing advance means and technologies, but also capably adapting these developed technologies, their user interface and their utilization at optimum levels. Today, industrial resources need perfect synchronization and optimization for getting elevated results. Accordingly, present study is furnished with the purpose to expose quality-driven insights to march toward excellence by optimizing existing resources by the industrial organizations. The present study evaluates quality attributes of mechanical machineries for seizing performance opportunities and maintaining competitiveness via synchronizing and reconfiguring firm's resources under quality management system.

In the present study, Kano’s integrated approach is implemented for supporting decision rational concerning industrial assets. The integrative Kano–analytic hierarchy process (AHP) approach is used to reflect the relative importance of quality attributes. Kano and AHP tactics are integrated to define global relative weight and their computational medium is adapted along with ratio analysis, reference point theory and TOPSIS technique for understanding robust decision. The study described an interesting idea for underpinning quality attributes for benchmarking system substitutes. A machine tool selection case is discussed to disclose the significant aspect of decision-making and its virtual qualities.

The decision executives can realize massive benefits by streaming quality data, advanced information, technological advancements, optimum analysis and by identifying quality measures and disruptions for gaining performance deeds. The study determined quality measures for benchmarking machine tool substitute for industrial applications. Momentous machine alternatives are evaluated by means of technical structure, dominance theory and comparative analysis for supporting decision-making of industrial assets based on optimization and synchronization.

The study linked financial, managerial and production resources under sole platform to present a technical structure that may assist in improving the performance of the manufacturing firms. The study provides a decision support mechanism to assist in reviewing the momentous resources to imitate a higher level of productive strength toward the manufacturing firms. The study endeavors its importance toward optimizing resources, which is an evident requirement in industries as the same not only saves money, escalates production, improves profit margins and so forth, but also gratifies the consumption of scarce natural resources.

The study stressed that advance information can be sought from system characteristics in the form of quality measures and attributes, which can be molded for gaining elevated outcomes from existing system characteristics. The same demands decision supports tools and frameworks to utilize data-driven information for benchmarking operations and supply chain activities. The study portrayed an approach for ease of utilizing data-driven information by the decision-makers for demonstrating superior outcomes. The study originally conceptualized multi-attributes appraisement framework associated with subjective cum objective quality measures to evaluate the most significant machine tool choice amongst preferred alternatives.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

Implementing blockchain in sustainable development goals (SDGs) and environmental, social and governance (ESG)-aligned infrastructure development involves intricate strategic factors. Despite technological advancements, a significant research gap persists, particularly in emerging economies. This study aims to address the challenges related to SDGs and ESG objectives during infrastructure delivery remain problematic, identifying and evaluating critical strategic factors for successful blockchain implementation.

This study employs a three-stage methodology. Initially, 13 strategic factors are identified through a literature review and validated by conducting semi-structured interviews with six experts. In the second stage, the data were collected from nine additional experts. In the final stage, the collected data undergoes analysis using interpretive structural modeling (ISM)–cross-impact matrix multiplication applied to classification (MICMAC), aiming to identify and evaluate the independent and dependent powers of strategic factors driving blockchain implementation in infrastructure development for SDGs and ESG objectives.

The study’s findings highlight three significant independent factors crucial for successfully integrating blockchain technology (BT) into infrastructure development for SDGs and ESG goals: data security (F4), identity management (F8) and supply chain management (F7). The study unravels these factors, hierarchical relationships and dependencies by applying the MICMAC and ISM techniques, emphasizing their interconnectedness.

This study highlights critical strategic factors for successful blockchain integration in SDG and ESG-aligned infrastructure development, offering insights for policymakers and practitioners while emphasizing the importance of training and infrastructure support in advancing sustainable practices.