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Exploring sustainable purchasing and supply chain management through an institutional change lens: a systematic literature review
Get PDFThe notion of sustainability within purchasing and supply chain management (PSCM) is not a recent development, as it has been evolving over the past few decades (Hoejmose & AdrienKirby, 2012; Johnsen et al., 2017; Miemczyk et al., 2012). Early discussions in PSCM focused primarily on environmental concerns, such as reducing carbon emissions, minimising waste, and improving energy efficiency within supply chains (Carter & Liane Easton, 2011; Seuring & Müller, 2008). Over time, the scope of sustainability expanded to include social and ethical
dimensions, such as ensuring fair labour practices, promoting diversity and inclusion, and supporting local communities through procurement decisions (Yawar & Seuring, 2017; Zorzini et al., 2015).International Purchasing & Supply Education & Research Association (IPSERA) 202
Routine replication and embodying process: an ethnographic study on the impact of the body
No full textWe examine how embodiment shapes routine replication through an ethnographic study of the Royal Air Force’s replication of a demanding loaded march ('tabbing') from Ground Combat Training into Initial Officer Training. Adopting a novel enactive ethnography over 30 months, we reveal how bodily differences among trainees prompted adaptations while maintaining routine recognisability. Three bodily mechanisms emerged—playing with rhythm, coping with injuries, and dealing with emotions— highlighting the central role of embodiment. Our research contributes to Routine Dynamics by advancing embodied understandings of replication and responding to methodological calls for innovative ethnographic approaches to studying routines.85th Annual Meeting of the Academy of Management (AOM 2025
From raw data to monotonic and trendable features reflecting degradation trends in turbofan engines
Get PDFThe performance of prognostic models relies heavily on the form and trend of the extracted features. However, the raw data collected from physical systems are inherently noisy, large in volume, and exhibit significant variability, which makes them unsuitable for direct use in prognostics. These characteristics poorly reflect the degradation behavior of physical systems and contribute to the uncertainty of prognostic outcome. Hence, transforming this data into relevant features and carefully selecting them is crucial for meeting the specific needs of prognostic models. This paper aims to address data processing challenges by focusing on extraction and selection of high-quality monotonic features which clearly reflect the degradation and can reduce prognostics uncertainty. The proposed framework comprises three main stages: Data pre-processing, feature extraction, and feature selection. It includes a fitness analysis to evaluate the monotonicity and trendability of features supplemented by visual inspections to identify relevant features. Applied to the Commercial Modular Aero-Propulsion System Simulation (CMAPSS) dataset from the NASA Ames Prognostics Data Repository, the framework reduces noise, improves feature monotonicity and trendability, and facilitates the selection of useful features - essential aspects for effective prognostic methods.This research was supported by the Centre for Digital Engineering and Manufacturing, Cranfield University, United Kingdom, 10.13039/5011000008592024 IEEE 3rd Industrial Electronics Society Annual On-Line Conference (ONCON
Optimization of printing parameters for self-lubricating polymeric materials fabricated via fused deposition modelling
Get PDFThis study investigated the feasibility of fabricating self-lubrication material using fused deposition modelling (FDM) technology, focusing on the influence of printing parameters on tribological performance. Experiments were conducted using PA and ABS materials, with varying printing speed, infill density, and layer height across four levels. The research established regression equations and fitted curves to describe the relationship between printing parameters and the coefficient of friction (CoF). Validation experiments demonstrated the reliability of the models, with errors within 10%. The results indicate that reducing printing speed and increasing infill density enhance surface quality, with infill density exerting a more significant effect. The influence of layer height on surface quality depends on the printer characteristics, making precise quantification challenging. Additionally, this study confirms that resin-based samples produced via FDM exhibit self-lubricating potential. These findings contribute to the optimization of FDM-printed structures by balancing surface quality and tribological performance.Polymer
Development and design of applications for UAV-based satellite communication terminal antenna evaluation using deep-reinforcement learning
Get PDFTsourdos, Antonios - Associate SupervisorIn recent years, satellites are launched almost on a daily basis and most of them are to
be operated in Non-Geostationary Orbit (NGSO). The number of user terminals communicating
with satellites is rapidly increasing. The interference has become a serious
issue due to the crowded communication environment and the increased popularity
of NGSO. Utilization of NGSO adds more complexity for operating user terminals
since it requires tracking the satellite which is not static from the terminals’ points
of view. Also, the risk of interference has escalated due to the greater demand for
Satellite-communication-On-The-Move (SOTM), which involves the need to keep terminals
constantly pointing toward the target satellite while they are installed on a moving
object. To ensure a safe communication environment, the terminal antenna must
be verified based on set requirements. However, the test process at conventional test
facilities is inefficient and does not have a solution to test antennas in the new communication
scenarios. Therefore, this thesis aims to develop in-situ Unmanned Aerial
Vehicle (UAV) -based measurement applications that are autonomously guided to enhance
the efficiency of the measurement and to propose novel measurement methods
to verify the antennas operated in new environments. Utilizing UAVs and performing
measurements onsite is challenging due to the additional error sources and uncertainties
in measurements and sensor positioning. In this work, a new deep-reinforcement
learning algorithm is developed which can adapt to the dynamic environment under
the presence of disturbances. Using this algorithm, the applications to verify the
boresight angle offset of terminal antennas and to evaluate SOTM terminal antennas
are proposed. The proposed applications are tested based on the numerical simulations
and the results showed that the developed applications improved the efficiency
of measurements and satisfied the required measurement accuracy. The thesis investigates
novel measurement approaches for a new generation of satellite communication
aiming to respond to the measurement demands that currently have no solution.PhD in Aerospac
Factorial analysis of the influence of both water and oxygen on extruded double base rocket propellant decomposition
Get PDFThe decomposition mechanisms of double base rocket propellants are well known and reported, but the influence of atmospheric conditions such as water and oxygen is poorly understood. In this work, the influence of water and oxygen on an extruded double base (EDB) rocket propellant aged between 70 and 100°C was examined using heat flow calorimetry. The results show that increased water content and higher oxygen concentration both lead to elevated heat flow. The activation energy (Ea), which was determined using the Friedman differential isoconversional method, showed that Ea decreases with higher water content, suggesting water acts as a catalyst, while lower oxygen concentration increases Ea, indicating slower decomposition. Factorial design analysis confirmed that both factors negatively impact Ea, with oxygen being the more significant factor while the water/oxygen interaction (AB) on the Ea is negligible. This research provides critical insight into the factors affecting the stability and shelf life of rocket propellants, which can lead to improved formulations and storage conditions, augmenting the safety and performance of EDB rocket propulsion systems. This research provides critical insight into the factors affecting the stability and shelf life of rocket propellants, which can lead to improved formulations and storage conditions, augmenting the safety and performance of EDB rocket propulsion systems.Propellants, Explosives, Pyrotechnic
Degradation mechanisms effect on the mechanical properties of pultruded CFRPS: a review
No full textEnvironmental factors such as ultraviolet (UV) radiation, moisture, and temperature can promote degradation mechanisms in pultruded carbon fibre composites. It has been shown that UV radiation coupled with moisture accelerates chemical reactions, leading to molecular bond breakage and chalking, compromising the surface and the matrix. UV radiation and temperature have been shown to significantly impact durability when combined with mechanical loading. While some studies have provided valuable insights into the single degradation processes associated with UV radiation, moisture, and mechanical loading, a comprehensive understanding of their concurrent effects, particularly under conditions representative of open-field exposure, remains limited. This gap is largely attributed to key limitations in the existing body of research, including over generalised experimental protocols, a lack of standardised test methods for any simultaneous application, wide variability in material compositions and a predominant focus on single or sequential rather than simultaneous exposure scenarios. This review covers degradation mechanisms due to single, sequential and combined environmental effects with related testing approaches used to predict residual life. This review emphasises the need for a deeper understanding of the synergistic effects in the design and application of pultruded CFRP composite and for more realistic environmental conditions during testing to mimic real-world scenarios. In particular, the inclusion of mechanical loading within environmental chambers is essential for capturing the interactive effects of simultaneous environmental and mechanical stress.This work was supported by Network Rail and Furrer & Frey at Cranfield University.Discover Polymer
Chitosan and its derivatives-based nanostructures in conjunction with their versatile applications in bio-medicine for alleviating contiguous diseases
Get PDFDue to its unique properties and inherent biocompatibility, chitosan (CH), a multifunctional biopolymer derived from chitin, has garnered significant interest in deployment in various scientific domains. The Food and Drug Administration (FDA) authorized CH to employ an injury remedy and a nutritional supplement. Furthermore, CH has facilitated advancements in numerous biological applications, particularly nano-carriers and scaffolds for tissue engineering. It is an ideal choice for wound care because of its hemostatic, antioxidant, and antimicrobial properties. The hydrophilic nature of CH makes it a perfect precursor. This review focuses on the advent of chitosan-based nanostructures, highlighting their physicochemical characteristics, methods for structural modification, and the functionalization of chitosan into its derivatives, which may aid in understanding its benefits and cellular significance. It has been demonstrated that CH nanostructures offer remarkable encapsulation efficiency and extended-release patterns in drug delivery, resulting in higher therapeutic efficacy and fewer side effects. Furthermore, due to their mucoadhesive properties, they are particularly well-suited for transdermal drug delivery. Nanostructures based on CH exhibited optimum activity in biosensing and diagnostic imaging. The potential of CH to interact with targeting ligands enhances the early detection of disease and integration of CH in focused imaging modalities. Moreover, CH variable surface chemistry facilitates attachment to biological entities, resulting in improved diagnostic accuracy, rendering the insertion of bioactive substances possible. Furthermore, the degradable nature of CH offers a minimal long-term impact, alleviating challenges related to ecological sustainability. As long as CH-modified nanostructures have become prevalent in healthcare fields and researchers strive to explore novel and more effective uses, medical care will advance, and a range of health problems will be resolved. This review provides a comprehensive overview of the current status of CH-based nanostructures in the bio-medical field, highlighting their potential to revolutionize therapeutic and diagnostic methodologies. In conclusion, several perspectives on its potential are presented, including new approaches to alterations, directed modification through the association between framework and operation, and the path towards growth for activities and implementations.Frontiers in Material
Modeling and simulation of backlash dynamics of worm-wheel system and its gap size estimation using Kalman filters
Get PDFReduced weight, size, and maintenance cost, as well as quieter and eco-friendly operation of electro-mechanical actuators (EMA), gained profound attention in various sectors, particularly aerospace. As a result, hydraulic actuators are being replaced by EMA counterparts. However, EMA comprises mating gear systems used for power transmission, and these gears experience wear through time. Among widely known EMAs variants, worm-wheel gear system is quietest, smoothest, and compact with high gear ratio. Due to these advantages, worm-wheel is utilized in various devices that require high precision such as surgical robotic arms and 3D printers. Nevertheless, worm-wheel systems, alike other variants of mating gear systems in EMA, suffer friction wear that leads to a backlash in the system. Backlash induces non-linearity in the dynamics of the worm-wheel system, resulting in reduced EMA performance and complex control system design. Therefore, as a part of EMA prognostic and health management (PHM) approaches, we develop a mathematical model of the non-linear dynamic behavior of backlash in the worm-wheel system and derived equations from the model for backlash gap size estimation. This backlash gap size estimation can be employed not only for monitoring of worm-wheel system performance and reliability as a proactive measure but also for its compensation control system design. Simulations of backlash dynamic behavior and gap size estimation were conducted using the Matlab/simscape tool. Extended and unscented Kalman filters were implemented to estimate backlash gap size, and their performance was compared using root-mean-square error technique. Results show that both Kalman filters estimate a simulated gap size very well. However, the unscented Kalman filter performs relatively higher than that of the extended Kalman filter around sharp edges during the switching behavior.IEEE Acces
Unmanned aerial vehicles in microgrid defense
Get PDFThe data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.In the evolving landscape of microgrid cybersecurity, this paper introduces a groundbreaking approach using unmanned aerial vehicles (UAVs) integrated with a deep neural network‐robust optimization (DNN‐RO) framework to defend against sophisticated false data injection attacks (FDIAs). Our research pioneers a dynamic UAV‐based defense model, meticulously engineered and simulated across a 50 square kilometer virtual microgrid. The UAVs leverage cutting‐edge path loss models and strategic energy management to optimize their deployment and operational efficiency. Our extensive simulation trials reveal compelling outcomes: a reduction in detection latency by over 50%, classification accuracy improved to 94.7%, and a streamlined response time that robustly counters cyber threats. Furthermore, the operational deployment of UAVs achieves significant cost reductions, showcasing not only the model's enhanced security capabilities but also its economic benefits. This study not only marks a significant advance in microgrid protection strategies but also sets a new standard for integrating UAV technology in critical infrastructure defense, offering scalable and economically feasible solutions for future‐proofing energy systems against cyber threats.Ongoing Research Funding Program (ORF-2025-635), King Saud University, Riyadh, Saudi Arabia.IET Renewable Power Generatio