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The apparel and textile sector poses a significant environmental challenge due to its substantial contribution to pollution in the form of air, water and soil pollution. To combat these issues, the adoption of sustainable practices is essential. This study aims to identify and analyse the barriers that hinder the progress of sustainability in the apparel and textile industry. By consulting experts in the field, critical barriers were identified and given special attention.

To achieve the research objective, an integrated approach involving Interpretive Structural Modelling (ISM) and fuzzy MICMAC decision-making techniques was employed. The results were further validated through the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method.

The findings highlight that barrier related to clothing disposal, inadequate adaptation to modern technology, challenges affecting sector efficiency and issues related to fashion design are crucial in influencing the remaining six barriers. Based on the outcomes of the DEMATEL method, a comprehensive cause-and-effect diagram was constructed to gain a deeper understanding of these challenges.

This research provides valuable insights for policymakers and stakeholders in the apparel and textile industry. It offers a strategic framework to address and overcome sustainability barriers, promoting the development of a more environmentally responsible and resilient sector.

The purpose of this research is to conduct an in-depth investigation of the barriers apparel and textile sectors. It is feasible that both the management team and the medical experts who provide direct patient care could benefit from this research.

Idea of circular economy defies the classical “make-use-dispose” approach of linear economic model. In the context of health-care industry, it relies heavily on the supply chain practices implemented by industry stakeholders. The purpose of this study is to explore such relationships, study their structure and put it across for attaining sustainability at large.

This study is an empirical research conducted on 145 health-care firms. The collected data is analysed to develop structural and measurement model. The five constructed hypotheses are examined and tested through structural equation modelling.

The study illustrates the latent relationships that exist among the stakeholders involvement, sustainable supply chain practices, sustainable performance and circular economy for health-care industry. It is found that the adoption of sustainable supply chain practices improves health-care performance, which, in turn, have positive influence on circular economy.

The structural and measurement model is developed in the context of circular health-care economy. It can be validated or improvised by conducting similar research in other industry using different methods. This research work fulfils the long existing gap in research by offering a linkage between various constructs to achieve health-care circular economy. Based on the research results, future researchers can build theories of circular economy and sustainability for health-care industry.

The study attempts to study the supply chain ways to achieve circular economy for Indian health-care sector. It considered latent relationships among the set of constructs, which are needed for theory building at later stage.

The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches.

The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking.

Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization.

This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach.

According to regulations, aircraft must be in an airworthy condition before they can be operated. To ensure airworthiness, they must be maintained by an approved component maintenance organisation. This study is aimed to identify potential errors that may arise during the final inspection and certification process of aircraft components, categorise them, determine their consequences and quantify the associated risks. Any removed aircraft components must be sent to an approved aircraft component maintenance organisation for further maintenance and issuance of European Union Aviation Safety Agency (EASA) Form 1. Thereafter, a final inspection and certification process must be conducted by certifying staff to receive an EASA Form 1. This process is crucial because any errors during this stage can result in the installation of unsafe components in an aircraft.

The Systematic Human Error Reduction and Prediction Approach (SHERPA) method was used to identify potential errors. This method involved a review of the procedures of three maintenance organisations, individual interviews with ten subject matter experts and a consensus group of 14 certifying staff from different maintenance organisations to achieve the desired results.

In this study, 39 potential errors were identified during the final inspection and certification process. Furthermore, analysis revealed that 48.7% of these issues were attributed to checking errors, making it the most common type of error observed.

This study pinpoints the potential errors in the final inspection and certification of aircraft components. It offers maintenance organisations a roadmap to assess procedures, implement preventive measures and reduce the likelihood of these errors.

Several graphs, streamlines, isotherms and 3D plots are illustrated to enlighten the noteworthy fallouts of the investigation. Embedding flow factors for velocity, induced magnetic field and temperature have been determined using parametric analysis.

Ternary hybrid nanofluids has outstanding hydrothermal performance compared to classical mono nanofluids and hybrid nanofluids owing to the presence of triple tiny metallic particles. Ternary hybrid nanofluids are considered as most promising candidates in solar energy, heat exchangers, electronics cooling, automotive cooling, nuclear reactors, automobile, aerospace, biomedical devices, food processing etc. In this work, a ternary hybrid nanofluid flow that contains metallic nanoparticles over a wedge under the prevalence of solar radiating heat, induced magnetic field and the shape factor of nanoparticles is considered. A ternary hybrid nanofluid is synthesized by dispersing iron oxide (Fe3O4), silver (Ag) and magnesium oxide (MgO) nanoparticles in a water (H₂O) base fluid. By employing similarity transformations, we can convert the governing equations into ordinary differential equations and then solve numerically by using the Runge–Kutta–Fehlberg approach.

There is no fund for the research work.

This kind of study may be used to improve the performance of solar collectors, solar energy and solar cells.

This investigation unfolds the hydrothermal changes of radiative water-based Fe₃O₄-Ag-MgO-H₂O ternary hybrid nanofluidic transport past a static and moving wedge in the presence of solar radiating heating and induced magnetic fields. The shape factor of nanoparticles has been considered in this study.

By adopting the “hard” and “soft” project management (PM) approaches from the PM-literature, this paper aims to problematize the expected role of client organizations in driving innovation in the transport infrastructure sector.

Addressing a large public client in Sweden, a case study design was initially applied to provide in-depth insights and perspectives of client project managers’ views and experiences of managing projects expected to drive innovation. In this paper, the concepts of “hard” and “soft” are used to discuss empirical findings on challenges associated with adopting a PM-approach for driving innovation in projects. The empirical material consists of interview data, complemented with observations and archival data.

Findings reveal challenges associated with combining hard and soft approaches, frequently demonstrating difficulties in balancing short-term project expectations with the promotion of innovation. In line with the literature, project managers note that there is a need for soft approaches to promote development and drive innovation. Yet, findings reflect a situation in which operational success criteria predominate, whereas soft approaches are not sufficiently used to create the grounds required for fostering innovation.

Insights are provided into how PM-approaches may impact construction innovation in the infrastructure sector, demonstrating a need for further research on the challenges and implications of applying and combining hard and soft PM-approaches.

Reducing aircraft fuel consumption has become a paramount research area, focusing on optimizing operational parameters like speed and altitude during the cruise phase. However, the existing methods for fuel reduction often rely on complex experimental calculations and data extraction from embedded systems, making practical implementation challenging. To address this, this study aims to devise a simple and accessible approach using available information.

In this paper, a novel analytic method to estimate and optimize fuel consumption for aircraft equipped with jet engines is proposed, with a particular emphasis on speed and altitude parameters. The dynamic variations in weight caused by fuel consumption during flight are also accounted for. The derived fuel consumption equation was rigorously validated by applying it to the Boeing 737–700 and comparing the results against the fuel consumption reference tables provided in the Boeing manual. Remarkably, the equation yielded closely aligned outcomes across various altitudes studied. In the second part of this paper, a pioneering approach is introduced by leveraging the particle swarm optimization algorithm (PSO). This novel application of PSO allows us to explore the equation’s potential in finding the optimal altitude and speed for an actual flight from Algiers to Brussels.

The results demonstrate that using the main findings of this study, including the innovative equation and the application of PSO, significantly simplifies and expedites the process of determining the ideal parameters, showcasing the practical applicability of the approach.

The suggested methodology stands out for its simplicity and practicality, particularly when compared to alternative approaches, owing to the ready availability of data for utilization. Nevertheless, its applicability is limited in scenarios where zero wind effects are a prevailing factor.

The research opens up new possibilities for fuel-efficient aviation, with a particular focus on the development of a unique fuel consumption equation and the pioneering use of the PSO algorithm for optimizing flight parameters. This study’s accessible approach can pave the way for more environmentally conscious and economical flight operations.

This study aims to develop an inclusive, multidisciplinary, flexible and organizationally adaptable safety risk management framework, including diversity management, that will be implemented to ensure safety is and remains at the desired level. If the number of incidents and potential incidents that could lead to accidents and their impact rates are to be reduced operationally and administratively, aviation safety risks and sources of risk must be better understood, sources of risk identified, and the safety risk management framework designed in an organization-specific and organization-wide sustainable way. At this point, it is necessary to draw the conceptual framework well and to define the boundaries of the concepts well. In this study, a framework model that can be adapted to the organization is proposed to optimize the management of risks and provide both efficient and effective resource allocation and organizational structure design in its operations and management functions.

The qualitative research method – triple techniques – was deemed appropriate for this study, which aims to identify, examine, interpret and develop the situations of safety management models. In this context, document analysis, business process modeling technique and Delphi techniques from qualitative research methods were used via integration as the methodology of this research.

To manage dynamic civil aviation management activities and business processes effectively and efficiently, the risk management process is the building block of the “Proposed Process Model” that supports the decision-making processes of aviation organizations and managers. This “Framework Conceptual Model” building block also helps build capacity and resilience by enabling continuous development, organizational learning, and flexible structuring.

This research is limited to air transportation and aviation safety management issues. This research is limited specifically to a safety-based risk management framework for the aviation industry. This research may have social implications as source saving, optimum resource use and capacity building will make a contribution to society and add value besides operational and practical implementation.

This research may contribute to more safe operations and functions in the aviation industry.

Management and academia may gain considerable support from this research to manage their safety risks via a corporate-tailored risk management framework, both improving resilience and developing corporate capacity. With this model presented, decision-makers will have a guiding structure that can optimally manage the main risk types that may be encountered in the safety risk in the fields of suppliers, manufacturers, demand changes, logistics, information management, environmental, legal and regulatory. Existing studies in the literature are generally in the form of algorithms and cannot be used as a decision-making support tool. This model aims to fill the gap in the literature. In addition, added value may be created by applying this model to optimum management safety risks in the real aviation industry and its related sectors.