Staff publications (MMD)

Browse

Now showing 1 - 20 of 71

Open Access
Unveiling the role of stakeholder involvement for digital transformation of Indian food SMEs
(Springer, 2025-07-01) Gupta, Sumit; Joshi, Deepika; Jagtap, Sandeep; Trollman, Hana; Verma, Virendra Kumar
With the advent of digitalization, the economy of the world is quickly changing itself and Indian Small and Medium Enterprises (SMEs) are the front runners. This study sheds light on how digital transformation is crucial to support the growth, competitiveness, and sustainability in the present business environment, and how digital transformation is important to the SMEs in India. To encourage SMEs to take up digital technologies, the Government of India has been creating an environment that encourages such moves by launching several initiatives including Digital India, Make in India and Startup India. This paper studies the role of stakeholder involvement in digital transformation in Indian food SMEs. Structural Equation Modeling (SEM) is used on survey responses from 103 food SMEs using the Statistical Package for the Social Sciences (SPSS). From the findings, there is a close relationship between stakeholder involvement and technological advancement (β = 0.595, p < 0.001) and organizational and political factors (β = 0.709, p < 0.001) as viewed by leadership, which reflects multidimensional factors leading to digital adoption. However, stakeholder involvement does not have any significant effect on financial factors (β = 0.018, p = 0.87), financial constraints being a major barrier to transformation. Moreover, although technological advancement results in a positive effect towards digital transformation (β = 0.694, p < 0.001), organizational and financial challenges act as stumbling blocks altogether. In the case of managers, this study indicates proactive involvement of stakeholders, investment in employees upskilling and alignment of organizational goals with digital initiatives for the support of technology adoption. This information assists decision makers in estimating government incentives and public private partnerships to overcome financial constraints. Digital transformation for food sector SMEs depends on a coordinated support of stakeholders, policy and technological readiness as preconditions for long term competitiveness.
Open Access
Reinforcement learning for UAV path planning under complicated constraints with GNSS quality awareness
(MDPI, 2025-06-25) Alyammahi, Abdulla; Xu, Zhengjia; Petrunin, Ivan; Peng, Bo; Grech, Raphael
Requirements for Unmanned Aerial Vehicle (UAV) applications in low-altitude operations are escalating, which demands resilient Position, Navigation and Timing (PNT) solutions incorporating global navigation satellite system (GNSS) services. However, UAVs often operate in stringent environments with degraded GNSS performance. Practical challenges often arise from dense, dynamic, complex, and uncertain obstacles. When flying in complex environments, it is important to consider signal degradation caused by reflections (multipath) and obscuration (Non-Line of Sight (NLOS)), which can lead to positioning errors that must be minimized to ensure mission reliability. Recent works integrate GNSS reliability maps derived from pseudorange error estimations into path planning to reduce loss-of-GNSS risks with PNT degradations. To accommodate multiple constraint conditions attempting to improve flight resilience against GNSS-degraded environments, this paper proposes a reinforcement learning (RL) approach to feature GNSS signal quality awareness during path planning. The non-linear relations between GNSS signal quality in the form of dilution of precision (DoP), geographic locations, and the policy of searching sub-minima points are learned by the clipped Proximal Policy Optimization (PPO) method. Other constraints considered include static obstacle occurrence, altitude boundary, forbidden flying regions, and operational volumes. The reward and punishment functions and the training method are designed to maximize the success criteria of approaching destinations. The proposed RL approach is demonstrated using a real 3D map of Indianapolis, USA, in the Godot engine, incorporating forecasted DoP data generated by a Geospatial Augmentation system named GNSS Foresight from Spirent. Results indicate a 36% enhancement in mission success rates when GNSS performance is included in the path planning training. Additionally, the varying tensor size, representing the UAV’s DoP perception range, exhibits a positive proportion relation to a higher mission rate, despite an increment in computational complexity.
Open Access
An innovative digital liquid metal manufacturing method for aerospace applications: incorporating life cycle assessment for sustainability
(Springer, 2024-10-09) Karadimas, Georgios; Pagone, Emanuele; Salonitis, Konstantinos
The Ultra Clean Cast (UCC) system presents an innovative approach to aerospace manufacturing by prioritizing component quality and manufacturing repeatability. It incorporates a cradle-to-gate life cycle assessment to highlight its additional environmental benefits, with a greater focus on enhancing sustainability. This novel approach improves upon traditional shape-casting by maintaining the high cleanliness of melt metal, critical for aluminum alloys, and difficult to achieve in general for aerospace parts, under varied conditions. By providing a sustainable, cost-efficient route for fabricating complex components, UCC is adaptable across aerospace platforms and evaluates the use of recycled aluminum, supporting the sector’s shift towards a circular economy. This paper outlines the UCC system’s integration of technological advancements with environmental responsibility, incorporating recycled aluminium raw material, material manufacturing, and product manufacturing stages. This system provides a new benchmark for environmentally friendly aircraft manufacturing by outlining process improvements and their implications for industry sustainability and efficiency. The findings highlight UCCs potential to affect aerospace manufacturing in the future, combining high-quality output with environmental considerations.
Open Access
Random wavelet kernels for interpretable fault diagnosis in industrial systems
(Elsevier, 2025) Deng, Haoxuan; Khan, Samir; Erkoyuncu, John Ahmet
Deep learning is a powerful method for fault diagnosis, but its "black-box" nature raises concerns in critical applications. This paper presents an interpretable, lightweight method combining random convolution kernel transformation (ROCKET) with wavelet kernels, which offer systematic time-frequency analysis and intuitive insights. Principal component analysis (PCA) is used to extract relevant patterns, forming a health indicator that guides maintenance decisions. A case study on linear actuator fault diagnosis demonstrates the method's balance of interpretability and computational efficiency, making it a valuable tool for reliable asset health monitoring in resource-limited settings.
Open Access
Sim2Know: new paradigm of digital twins to design and inform human-centric knowledge system
(Elsevier, 2025) Li, Bingbing; Fan, Haolin; Fan, Zhen; Erkoyuncu, John Ahmet; Zhang, Hong-Chao; Huang, Haihong
The novel framework, Sim2Know, tackles two major challenges in adaptively designing and informing a human-centric knowledge system: the lack of labeled real-world training data and the difficulty of capturing implicit knowledge. First, a digital twin demonstrator is developed to generate high-quality synthetic training data. Next, we propose a hybrid training approach that combines transfer learning from pre-trained self-supervised models with synthetic data augmentation, achieving a precision rate of 90.31 % in identifying 11 essential human action patterns in metal additive manufacturing. Finally, the human-centric knowledge system is designed to capture implicit knowledge through contextualizing human machine interaction beyond explicit domain knowledge.
Open Access
Enabling sustainability-by-design with multi-disciplinary computer aided systems
(Elsevier, 2025) Ituarte, Iñigo Flores; Pagone, Emanuele; Daareyni, Amirmohammad; Thayapararajah, Samniroshan; Tosello, Guido
Sustainability-by-Design requires information and communication technologies (ICTs) capable of integrating design engineering, manufacturing processes, materials, and sustainability considerations. Currently, methodologies for assessing environmental sustainability, such as product life cycle assessment, are often implemented too late in the design process, reducing opportunities for early intervention. Integrating environmental sustainability modeling in computer-aided systems (CAx) allows engineers to concurrently evaluate trade-offs between technical performance and environmental impact, facilitating informed decision-making during embodiment design stages. Using a prosthetic device produced via material jetting additive manufacturing as case study, we demonstrate the transformative role of advanced CAx tools capable of analyzing trade-offs among competing objectives.
Open Access
Cost-effective sensor-based digital twin for fused deposition modeling 3D printers
(Taylor & Francis, 2025-12-31) Shomenov, Kemel; Ali, Md. Hazrat; Jyeniskhan, Nursultan; Al-Ashaab, Ahmed; Shehab, Essam
In a highly digitalized world, Digital Twin (DT) technology is becoming vital in manufacturing, especially in additive manufacturing. This research work presents cost-effective digital twin development and implementation for Fused Deposition Modeling (FDM) 3D printers. This developed system enhances real-time process monitoring, anomaly detection, and autonomous control through a logical approach. Sensor data that measures and tracks filament flow, vibrations, and nozzle position are processed in real-time for the detection of anomalies such as layer shifting, under- and over-extrusion, and excessive vibrations. Magnetic encoders enable monitoring the filament flow with 0.73% error, position sensors identify nozzle displacement to monitor layer shifts. The sensor data are stored in the Firebase and visualized in the Unity interface with a 500- 700 ms data lag. In contrast to traditional systems, this developed system works independently without the need for external hosts, providing a very low-cost, modular solution (less than $50) appropriate for small-scale applications. This research also addresses the gap in FDM 3D printers and sensor-based DT by demonstrating practical, real-time interventions for quality assurance in FDM processes.
Open Access
The lean and green imperative of manufacturing data
(Springer, 2024-10-09) Patsavellas, John; Haddad, Yousef; Salonitis, Konstantinos
This study introduces a stochastic model-based framework for the prediction and measurement of the environmental impact of manufacturing systems’ digitalization. Utilising a Monte Carlo simulation experimental framework, this paper forecasts the CO2e emissions from the entire lifecycle of manufacturing data over long-term time horizon under different scenarios. The analysis proceeds to estimate the maximum, average, and minimum potential CO2e emissions, under different growth models. Findings reveal that, with the current exponential growth of data that exceeds data centres’ efficiency improvements and carbon intensity decay rates, the environmental footprint associated with the entire lifecycle of data can have a potential adverse impact on the realisation of net-zero goals. The proposed approach provides a viable pathway for manufacturing enterprises aiming to align their data management practices with environmental sustainability and operational efficiency.
Open Access
An innovative digital liquid metal manufacturing method for aerospace applications: incorporating life cycle assessment for sustainability
(Springer, 2024-10-09) Karadimas, Georgios; Pagone, Emanuele; Salonitis, Konstantinos
The Ultra Clean Cast (UCC) system presents an innovative approach to aerospace manufacturing by prioritizing component quality and manufacturing repeatability. It incorporates a cradle-to-gate life cycle assessment to highlight its additional environmental benefits, with a greater focus on enhancing sustainability. This novel approach improves upon traditional shape-casting by maintaining the high cleanliness of melt metal, critical for aluminum alloys, and difficult to achieve in general for aerospace parts, under varied conditions. By providing a sustainable, cost-efficient route for fabricating complex components, UCC is adaptable across aerospace platforms and evaluates the use of recycled aluminum, supporting the sector’s shift towards a circular economy. This paper outlines the UCC system’s integration of technological advancements with environmental responsibility, incorporating recycled aluminium raw material, material manufacturing, and product manufacturing stages. This system provides a new benchmark for environmentally friendly aircraft manufacturing by outlining process improvements and their implications for industry sustainability and efficiency. The findings highlight UCCs potential to affect aerospace manufacturing in the future, combining high-quality output with environmental considerations.
Open Access
Fireside corrosion behavior of thermally sprayed coatings for waste-to-energy power plant applications
(Springer, 2025-12-31) Usman, Ahmad; Arrom, Luis Isern; Nicholls, John R.; Cordero, Mario; Syed, Adnan U.
This study investigates the fireside corrosion behavior of four (Ni-22Cr, Ni-25Cr, Co-25Cr, and NiCo-25Cr) coatings, which were applied using twin wire arc spray technique and subjected to simulated waste-burning environments (a gas composition containing HCl, SO2, CO2, N2, H2O, balance N2, plus a salt deposit of 50wt.% KCl + 50wt.% K2SO4). The coatings deposited on a conventional base steel alloy (E−250) were tested under these conditions at 550 °C for 500 h in a laboratory-scale atmosphere controlled furnace. After the fireside exposure, the samples were studied using optical microscopy, SEM-EDX, and XRD to deduce coatings performance and possible corrosion mechanisms. The results indicated that all coatings, except Ni-22Cr, outperformed the E−250 steel. The Ni-22Cr and NiCo-25Cr coatings showed similar pitting corrosion behavior with more prominent corrosion pits on Ni-22Cr coating’s surface. The Co-25Cr coating showed slightly improved performance to the above two coatings, which can be attributed to the ability of Co to resist corrosion attack under these conditions. Overall, the Ni-25Cr coating composition was conclusively found to be most effective.
Open Access
A behaviourally informed heuristics-framework for net zero transformation in manufacturing
(Springer, 2024-10-09) Kaur, Rashmeet; Patsavellas, John; Salonitis, Konstantinos
Transitioning to net zero emissions in manufacturing is fraught with challenges, from navigating uncertainties and making critical trade-offs, to overcoming biases and information asymmetry. Such behavioural challenges could potentially result in bounded rationality, where decision-makers operate under limited information and cognitive constraints. This paper introduces a framework that employs behaviourally informed heuristics to simplify the complexity of net-zero transformation. By incorporating behavioural model of rational choice and decision-making rules, the framework could help manufacturing decision-makers to manage uncertainties and cognitive limitations, thus broadening the toolkit for navigating the reduction of carbon emissions.
Open Access
Wear modeling and friction-induced noise: a review
(Tsinghua University Press, 2025-05-01) Tian, Yang; Khan, Muhammad; Yuan, Hao; Zheng, Bohao
Wear and friction-induced noise are pivotal tribological phenomena that significantly influence the longevity and efficiency of mechanical systems. This review synthesizes current research on wear modeling and friction-induced noise, exploring their mechanisms, influencing factors, and predictive challenges. Wear modeling encompasses a range of approaches, from traditional methods such as the Archard equation to more advanced numerical and machine learning techniques. These models address diverse mechanisms—adhesive, abrasive, and fatigue wear—which are shaped by material properties, surface roughness, and environmental conditions. Friction-induced noise, arising from stick-slip, sprag-slip, and mode-coupling, is influenced by surface states, damping, and operational parameters. Crucially, wear and noise are interlinked. Wear reshapes surfaces and dynamics, thereby modulating noise, while noise can serve as a diagnostic tool for wear progression. Yet, existing models often isolate these phenomena, neglecting their synergy and impeding accurate system-life predictions. This review highlights this gap and advocates for the development of integrated wear-noise models, harnessing multiscale simulations, advanced computation, and empirical validation. The development of such models has the potential to significantly enhance the accuracy of durability and acoustic performance predictions. They offer a holistic framework that captures the dynamic interplay between surface degradation and noise generation. This framework is essential for advancing non-invasive detection technologies in industries such as automotive, aerospace, and manufacturing. In these sectors, addressing these dual challenges is crucial for enhancing performance, safety, and efficiency.wear
Open Access
Deposition of alginate-oregano nanofibres on cotton gauze for potential antimicrobial applications
(Elsevier, 2025-08-01) Orisawayi, Abimbola Oluwatayo; Lu, Hao; Badruddin, Ishrat Jahan; Venkatraman, Prabhuraj D.; Britten, Nicole S.; Butler, Jonathan A.; Koziol, Krzysztof K. K.; Rahatekar, Sameer S.
In this study, we developed an innovative natural antibacterial medical bandage composed of electrospun nanofibres derived from alginate (SAg) and oregano essential oil (OEO). The nanofibre deposition process was systematically optimised, achieving a controlled evolution of fibre formation at intervals of 1, 2, 3, 4, and 8 h. Over time, fibre morphology has changed from a dispersed network to a densely packed, homogeneous, fibrous, fully embedding cotton gauze nanofibre. Scanning Electron Microscopy (SEM) revealed nanofibres with diameters ranging from 100 to 300 nm, 46 % measuring 100–200 nm, 37 % at 200–300 nm, and 14 % between 300 and 400 nm. Thermogravimetric Analysis (TGA) confirmed improved thermal stability in cross-linked samples. At the same time, Fourier Transform Infrared Spectroscopy (FTIR) shows the incorporation of OEO into the nanofibres shows OEO carvacrol, and thymol. Antibacterial efficacy tested inhibition zone assays against Methicillin-resistant Staphylococcus aureus (MRSA) and Listeria monocytogenes on double-layered bandages is 15 mm and 10 mm, respectively. Statistical analysis results from ANOVA confirmed that multi-layered bandages (TL-BSS) had significantly enhanced antibacterial activity compared to single-layered (SSS) and both-sided spun (BSS) configurations. Unlike conventional wound dressings, this study introduces a bioactive, nanofibre-integrated gauze with sustained antibacterial efficacy.
Open Access
Cost Optimisation to determine ship maintenance schedules for improved operational availability
(Elsevier, 2025-06-16) Gosavi, Pranav; Latsou, Christina; Erkoyuncu, John Ahmet; Sibson, Jim
Complex port maintenance operations face significant challenges due to the dynamic nature of port resource availability, variable task urgency, and downtimes having different priorities. This study proposes a dynamic scheduling approach for ship maintenance that integrates agent-based modelling with multi-objective optimisation. By optimising port resource allocation and reducing ship idle costs, the approach significantly enhances operational efficiency in maritime logistics. Utilising a hybrid simulation-optimisation framework, the proposed method adapts downtime priorities and resource allocations rules arising due to classes of ship and their compatibility with the port resources, and their downtimes. Agent-based modelling simulates interactions between ships, port assets, and maintenance activities while Discrete Event Simulation captures the stages of maintenance process. The model re-evaluates the ship maintenance schedules and facility resource downtime schedules to minimise idle time and maximise efficiency. Comparative analyses reveal improvements over static methods, including an average 45% reduction in idle costs of ship due to unavailable resources, with marginal changes in maintenance costs. This approach not only enhances port operational efficiency but also reduces costs associated with ship waiting times, demonstrating its potential application to other complex industrial scheduling problems requiring adaptive solutions.
Open Access
Monitoring framework for physical knowledge exploration in wire-based directed energy additive manufacturing (w-DEDAM)
(Elsevier, 2025-06) Chen, Le; Lasisi, Shakirudeen; Vives, Javier; Bird, Thomas; Narasiah, Hansley; Qin, Jian; Feng, Shuo; Yin, Yi; Diao, Chenglei; Zhao, Yifan; Ding, Jialuo; Williams, Stewart
Monitoring in wire-based directed energy deposition additive manufacturing (w-DEDAM) is crucial for ensuring part quality and process stability. It aids in optimising process control, enhancing efficiency, and minimising material waste. Additionally, monitoring provides valuable documentation for regulatory compliance and supports maintenance by tracking equipment performance. Effective monitoring and relevant control enhance process reliability, reduce scrap, and ensure the production of high-quality components. However, current monitoring systems in w-DEDAM face significant challenges. Key issues include a lack of standardisation in monitored variables, leading to inconsistent data and interpretation. Many existing monitoring systems often focus on the adjustable “knob” variable measurements rather than critical factors that more accurately represent physical process conditions. This narrow focus can fail to capture essential aspects of process explanation and part quality. Furthermore, there is a deficiency in integrating monitoring data with digital modelling and qualification methods, limiting the ability to use real-time data for comprehensive process optimisation and predictive analysis. Addressing these gaps is crucial for advancing system effectiveness. In this research, key process variables will be defined and explained to enhance process understanding. A knowledge-driven monitoring framework will be proposed to tackle the issues of standardisation and relevance of monitored parameters, ensuring that critical variables are accurately captured and utilised. Additionally, the study will introduce a commercial industry monitoring software based on this framework, which is currently used in the industry. This software integrates the proposed approach, offering a robust solution for real-time monitoring and process control, thus addressing existing limitations and supporting improved process optimisation and digital modelling.
Open Access
Capacity and impedance characteristics of the lithium-ion battery and mechanical properties of the battery pack under coupled temperature-vibration conditions: an experimental approach
(Elsevier, 2025-10-01) Li, Ran; He, Feiyang; Vargas, Oscar Rojas; Khan, Muhammad
Since electric vehicles are subject to constant vibration and temperature fluctuations during operation, it is critical to understand the impact of these factors on the performance of batteries and battery enclosures. This study investigates the impact of vibration (random frequencies from 8 Hz to 200 Hz) and temperature (ranging from −20 °C to 60 °C in 10 °C increments) on lithium-ion batteries at varying states of charge (SOC, from 0 % to 100 % in 10 % intervals). A 3D-printed plastic enclosure was used for the battery pack to assess its mechanical performance under operational vibration. Analysis of the experimental data reveals that battery internal resistance shows an upward trend, with increases ranging from 0.1 mΩ to 0.5 mΩ under standard conditions and up to 1 mΩ at low temperatures after vibration. Battery capacity exhibited a slight decline after vibration, typically around 0.5 %, across most conditions. Temperature did not significantly impact the SOC response, with similar resistance and capacity trends observed across the temperature spectrum after vibration. For the battery pack, structural integrity was maintained under thermal and vibrational stress, as indicated by minimal changes in natural frequency (within 0.5 Hz). These results confirm the feasibility and potential of using 3D-printed battery enclosures in practical applications.
Open Access
Developing a supportive organisational culture for continuous improvement in manufacturing firms in Saudi Arabia
(MDPI, 2025-06-24) Algethami, Adel; Assad, Fadi; Patsavellas, John; Salonitis, Konstantinos
Continuous improvement (CI) is vital for Saudi manufacturing firms to remain competitive in the global market. However, cultural factors significantly influence CI adoption. This qualitative study, involving 28 interviews and focus groups with employees from five local manufacturing firms, explored these factors. Seven key cultural themes emerged, including communication, employee wellbeing, talent management, ethics, top management support, organisational learning, and compliance. A conceptual framework was developed to assess a firm’s cultural proximity to an ideal CI state. This framework integrates a diagnostic tool to guide firms in evaluating their cultural landscape and implementing targeted interventions for successful CI adoption. Future research should explore the long-term impacts of cultural shifts on performance and competitiveness.
Open Access
Enhancing safety performance in UK metal manufacturing: a revised framework to reduce fatal accidents
(MDPI, 2025-06-1) Eggleston, Alexandra; Sarfraz, Shoaib; Salonitis, Konstantinos; Gupta, Sumit; Trollman, Hana; Jagtap, Sandeep
Fatal accidents in UK’s manufacturing sector are expected to remain the same or increase in coming years. This paper has tried to combat this issue by adapting and further developing a previously defined Safety Framework for the Paint Sector, to evaluate the safety performance of a metal manufacturing facility. To achieve this, the original Safety Framework was updated to align with the current British safety legislation outlined by the British Standards Institution. The framework was based on a three-level multi-attribute value theory (MAVT). Upon reviewing BSI 45001, the Safety Framework was founded upon the concept of Deming’s Plan, Do, Check, Act (PDCA) which is the foundation for the original framework, therefore, the first-level attributes remained consistent. The 13 attributes of the second level and 36 attributes of the third level were derived from the literature review and updated to relevant legislation. To develop the Safety Framework, the Delphi method was used. This included interviews that were conducted with employees and managers from either a Safety or Engineering background. The second part of the paper involved the improvement of the Safety Framework, based on the interview feedback. The main findings of the study revealed that the final Safety Framework has been deemed relevant for the Metal Manufacturing Sector by Industry Suitably Qualified and Experienced Personnel (SQEP). The majority of Interviewees deemed the Safety Framework to have a clear layout and easy to understand. The interviews and final Safety Framework suggested the importance of a company’s emphasis on employee welfare and health, in order to reduce accidents in the workplace. The originality of this paper lies in its application and validation of a sector-specific safety framework, contributing to the body of knowledge by offering a replicable methodology for adapting safety frameworks to other manufacturing sectors.
Open Access
From metallic liquids to metallic glasses: in-situ monitoring the atomic structure evolution by synchrotron X-ray diffraction
(Taylor & Francis, 2025-12-31) Stiehler, Martin E.; Georgarakis, Konstantinos
Although ubiquitous in nature and technology, a deep understanding of glass formation and glass transition is still missing. It is assumed that the remarkable slowdown of kinetics towards vitrification can be traced back to structural changes in the undercooled liquid. Therefore, a continuous monitoring of the atomic structure during cooling from the equilibrium liquid to the glass is inevitable. However, the high critical cooling rates usually necessary for vitrification of metallic alloys make this a challenging, but at the same time very exciting, endeavor. Only in recent years, it has been technologically possible to achieve in-situ monitoring of the evolving structure for a small number of metallic-glass-forming alloys. Currently, only high-energy X-rays from synchrotron sources as probes in combination with fast two-dimensional detectors can capture diffraction images from usually containerlessly levitated samples with the necessary scattered intensity as well as resolution in space and time. Here, results for those materials where in-situ monitored vitrification has been experimentally accomplished are reviewed, and approaches to experiment and data processing are compared. Insights into the structural behaviour during vitrification derived from these experiments are discussed. Results from accompanying simulations are also included. In addition to the in-situ observation of vitrification, structural indications of possible liquid-liquid crossovers in the alloys are considered as well.
Open Access
Foraging supply chains: investigating disaster for improved food provisioning
(Springer, 2025-06-18) Trollman, Hana; Jagtap, Sandeep; Tamakloe, Sonia D.; Trollman, Frank
Disasters such as COVID-19 and the Russia–Ukraine war are drawing attention to the provisioning of food during crises. The main concern has been quickly establishing a stable food supply. However, climate change and public health concerns are shifting attention to the critical gap in identifying the minimal considerations that would adequately address ecological disaster food provisioning. A meta-ethnography of 16 disasters in 12 different countries is employed to identify the activities and their supporting strategies that provide benefits to existing actors within food networks. Analysis suggests that public health, resilience, and sustainability stand to benefit from the identified practices. A conceptual model of an ecologically embedded minimum viable ecosystem for disaster food provisioning is proposed. Exemplar applications are provided for Tigray, Gaza, and Ukraine. The findings may be applied to disaster settings for the development of policy for culturally sensitive, equitable, and nutritious food provisioning strategies.

Browse

Recent Submissions