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Lean management and industry 4.0 : A dynamic capabilities framework for an integrated transformation
No full textThis study addresses the ongoing challenge of concurrently integrating Lean and Industry 4.0, a critical need for companies striving to enhance operational capabilities in increasingly digital environments. While past research focused on sequential approaches or high-level conceptualizations, this research delves into the level of 'how', applying Dynamic Capabilities theory through a deductive, four-stage mixed-method design, focused on large German manufacturing firms. First, expert interviews underwent thematic analysis to identify strategies and courses of action for integration. Next, an exploratory survey refined these results statistically. Third, the findings were validated and triangulated via a Delphi study, from which a structured integration framework emerged. Finally, confirmatory composite analysis of 236 managerial responses confirmed the reliability and validity of the framework. The study presents 44 validated actions grouped into six dimensions: Initiating, Sensing, Seizing, Transforming, Resources, and Capabilities. Notably, it introduces the new “Initiating” dimension, expanding the Dynamic Capabilities theory. While the study’s focus on large German manufacturers is a limitation, the resulting framework offers practical pathways for companies unable to pursue sequential integration due to time pressures. Ultimately, this research provides both theoretical advancement and practical tools for successfully managing the simultaneous transformation towards Lean and Industry 4.0
Indigenous management practices to reduce pests and pathogens of cash crops in agroforestry systems
No full textIndigenous farming practices (e.g., traditional agroforestry) can sustain high levels of biodiversity and ecosystem services (e.g. natural pest and pathogen control) and can be sustainable in the long term, especially if integrated with innovation and technology. We investigate the factors influencing pests and pathogen impact on agroforestry practices in Indigenous communities in Bali, Indonesia. We collected data via 100 plots with different compositions of crops in both community forests (where the use of agrochemicals is precluded by social rules) and polyculture (with no limitation on the use of agrochemicals). For each plot, we obtained a score of infestation for four cash crops (banana, coffee, cacao, vanilla) by calculating the proportion of plants affected and giving a percentage score of infestation. Analysis was performed via generalised additive models with crop richness, canopy cover, and agroforestry type as factors. The crop with highest damage was cocoa (63.9% plants affected by black pod disease) and we also recorded a widespread incidence of the vascular streak dieback (19.4% plants affected). Fusarium stem rot was the second highest damage in crops, with 30.0% of vanilla plants infected. Fusarium wilt affected 10.2% of banana plants and the coffee berry borer affected 9.7% of coffee plants. There were no differences in pest and pathogen incidence between community forest and polyculture, thus insecticides and fungicides had little to no impact on crop infestations. An increased crop richness favoured a reduction in some insect pests, suggesting a potential increase in natural pest control. Since insecticides and fungicides do not seem to have a significant impact in reducing pest and pathogen infestation (probably due to genetic variability and resistance of pests and pathogens), the most effective Indigenous practice is to diversify profits from different crops, thus buffering the negative effects of market fluctuations and yield loss
Mapping digital twin applications in infrastructure and the built environment across research types, methods, sectors, phases, and scales
Full text linkDigital Twin technologies are increasingly used in infrastructure and the built environment to create dynamic, data-driven models of physical assets and processes. This review analyses recent advancements across sectors such as tunnels, bridges, roads, buildings, construction management, and urban planning, covering all life-cycle phases from design to operation. Integrating Digital Twins with Building Information Modelling, Internet of Things sensors, and Artificial Intelligence enhances real-time monitoring, decision-making, and asset performance. Key methods include monitoring, modelling, and simulation, which improve resource use and proactive maintenance. However, adoption faces challenges such as poor data interoperability, high costs, and technical complexity in merging multiple technologies. Ethical and governance issues around data privacy and security also persist. The review identifies future research needs in improving interoperability, expanding predictive analytics, and assessing large-scale impacts. It highlights Digital Twins' potential to improve resilience, efficiency, and sustainability, stressing the need for policy support and stakeholder collaboration
Module two materials - Evidencing Performance and Quality
No full textTMDP Module 2 teaching materials and resources for days 1 and 2
Gait dynamics classification with criticality analysis and support vector machines
Full text linkClassifying demographic groups of humans from gait patterns is desirable from several long-standing diagnostic and monitoring perspectives. IMU recorded gait patterns are mapped into a nonlinear dynamic representation space using criticality analysis and subsequently classified using standard Support Vector Machines. Inertial-only gait recordings were found to readily classify in the CA representations. Accuracies across age categories for female versus male were 72.77%, 78.95%, and 80.11% for =0.1, 1, and 10, respectively; within the female group, accuracies were 73.36%, 76.70%, and 78.90%; and within the male group, 77.65%, 81.48%, and 81.05%. These results show that dynamic biological data are easily classifiable when projected into the nonlinear space, while classifying the data without this is not nearly as effective
Transforming growth factor-β drives epithelial mesenchymal transition and reduces synthesis of unelaborated O-GalNAc glycans in breast cancer cells
No full textAltered O-glycosylation of cancer cells is frequently associated with metastasis and poor prognosis. During metastasis, cells must also lose their epithelial characteristics and become mesenchymal and motile, termed epithelial-mesenchymal transition (EMT). While it is established that transforming growth factor beta-1 (TGF-β1) can induce EMT, the effect of cytokine-induced EMT on O-glycosylation of breast cancer cells has not previously been explored. MCF-7 and T47-D breast cancer cells were treated with TGF-β1 over a time course of up to 7 days. Morphological changes were assessed using confocal microscopy and quantified; levels of EMT marker expression were assessed using immunofluorescence with confocal microscopy and western blot. The effect of TGF-β1 on synthesis of unelaborated Tn antigen was explored using Helix pomatia agglutinin (HPA) labelling. TGF-β1 treatment induced morphological changes, resulting in an elongated, mesenchymal-like phenotype, and a reduction of epithelial marker E-cadherin but did not detectably induce mesenchymal markers N-cadherin or vimentin. It also resulted in a significant reduction in unelaborated Tn antigen, detected by HPA labelling. These observations are consistent with TGF-β1 inducing an ‘early’ or partial EMT state over this timeframe, and a concomitant change in O-glycosylation, consistent with the synthesis of more elaborated O-glycan structures; such glycoplasticity may function in metastasis
Longitudinal assessment of indoor environment in existing UK social housing dwellings requiring energy retrofit
Full text linkThe UK’s social housing stock is widely recognised to be in poor condition, yet there remains a significant lack of empirical data on the indoor environments experienced by residents—many of whom are vulnerable due to financial hardship or health conditions. This study presents a longitudinal assessment of indoor environmental conditions in 23 EPC D- or E-rated social housing dwellings in Warwickshire, monitored over two consecutive winters (2021/22 and 2022/23). Temperature, relative humidity (RH), and carbon dioxide (CO₂) concentrations were continuously recorded in bedrooms and living rooms, while a subset of 13 homes was additionally monitored for particulate matter (PM₂.₅, PM₁₀) and volatile organic compounds (VOCs) in living rooms.
Findings reveal a marked deterioration in thermal conditions during the second winter. Average living room temperatures fell by 0.7°C (from 19.2°C to 18.5°C) and bedroom temperatures by 1.9°C (from 19.0°C to 17.1°C), likely due to reduced heating use in response to rising energy costs and poor insulation. Indoor air quality (IAQ) was similarly concerning: CO₂ concentrations exceeded the 900 ppm benchmark for over 95% of occupied hours in nearly all rooms across both seasons, with average levels rising from 1,193 ppm to 1,519 ppm. Limited ventilation and increased time spent indoors, as residents sought to conserve warmth, contributed to these conditions. Elevated PM and VOC concentrations were associated with occupant characteristics (smoking and pet ownership) and household activities, providing further evidence of insufficient air exchange.
These results highlight the urgent need for holistic retrofit strategies that address both energy efficiency and IAQ. Prioritising improvements to building fabric and ventilation before heating system upgrades will be essential to safeguard occupant health, comfort, and well-being. The study provides rare empirical evidence and offers insights to inform policy and retrofit design for the UK’s most vulnerable households
Grading matrices (for reference)
No full textPostgraduate Certificate in Managing Practice Quality in Social Care, assignment grading matrices used for assessment