381 research outputs found
Digitalization and Development
This book examines the diffusion of digitalization and Industry 4.0 technologies in Malaysia by focusing on the ecosystem critical for its expansion. The chapters examine the digital proliferation in major sectors of agriculture, manufacturing, e-commerce and services, as well as the intermediary organizations essential for the orderly performance of socioeconomic agents.
The book incisively reviews policy instruments critical for the effective and orderly development of the embedding organizations, and the regulatory framework needed to quicken the appropriation of socioeconomic synergies from digitalization and Industry 4.0 technologies. It highlights the importance of collaboration between government, academic and industry partners, as well as makes key recommendations on how to encourage adoption of IR4.0 technologies in the short- and long-term.
This book bridges the concepts and applications of digitalization and Industry 4.0 and will be a must-read for policy makers seeking to quicken the adoption of its technologies
Sampling-Based Exploration Strategies for Mobile Robot Autonomy
A novel, sampling-based exploration strategy is introduced for Unmanned Ground Vehicles (UGV) to efficiently map large GPS-deprived underground environments. It is compared to state-of-the-art approaches and performs on a similar level, while it is not designed for a specific robot or sensor configuration like the other approaches. The introduced exploration strategy, which is called Random-Sampling-Based Next-Best View Exploration (RNE), uses a Rapidly-exploring Random Graph (RRG) to find possible view points in an area around the robot. They are compared with a computation-efficient Sparse Ray Polling (SRP) in a voxel grid to find the next-best view for the exploration. Each node in the exploration graph built with RRG is evaluated regarding the ability of the UGV to traverse it, which is derived from an occupancy grid map. It is also used to create a topology-based graph where nodes are placed centrally to reduce the risk of collisions and increase the amount of observable space. Nodes that fall outside the local exploration area are stored in a global graph and are connected with a Traveling Salesman Problem solver to explore them later
Application of knowledge management principles to support maintenance strategies in healthcare organisations
Healthcare is a vital service that touches people's lives on a daily basis by providing treatment and
resolving patients' health problems through the staff. Human lives are ultimately dependent on the skilled
hands of the staff and those who manage the infrastructure that supports the daily operations of the
service, making it a compelling reason for a dedicated research study. However, the UK healthcare sector
is undergoing rapid changes, driven by rising costs, technological advancements, changing patient
expectations, and increasing pressure to deliver sustainable healthcare. With the global rise in healthcare
challenges, the need for sustainable healthcare delivery has become imperative. Sustainable healthcare
delivery requires the integration of various practices that enhance the efficiency and effectiveness of
healthcare infrastructural assets. One critical area that requires attention is the management of
healthcare facilities.
Healthcare facilitiesis considered one of the core elements in the delivery of effective healthcare services,
as shortcomings in the provision of facilities management (FM) services in hospitals may have much more
drastic negative effects than in any other general forms of buildings. An essential element in healthcare
FM is linked to the relationship between action and knowledge. With a full sense of understanding of
infrastructural assets, it is possible to improve, manage and make buildings suitable to the needs of users
and to ensure the functionality of the structure and processes.
The premise of FM is that an organisation's effectiveness and efficiency are linked to the physical
environment in which it operates and that improving the environment can result in direct benefits in
operational performance. The goal of healthcare FM is to support the achievement of organisational
mission and goals by designing and managing space and infrastructural assets in the best combination of
suitability, efficiency, and cost. In operational terms, performance refers to how well a building
contributes to fulfilling its intended functions.
Therefore, comprehensive deployment of efficient FM approaches is essential for ensuring quality
healthcare provision while positively impacting overall patient experiences. In this regard, incorporating
knowledge management (KM) principles into hospitals' FM processes contributes significantly to ensuring
sustainable healthcare provision and enhancement of patient experiences. Organisations implementing
KM principles are better positioned to navigate the constantly evolving business ecosystem easily.
Furthermore, KM is vital in processes and service improvement, strategic decision-making, and
organisational adaptation and renewal.
In this regard, KM principles can be applied to improve hospital FM, thereby ensuring sustainable
healthcare delivery. Knowledge management assumes that organisations that manage their
organisational and individual knowledge more effectively will be able to cope more successfully with the challenges of the new business ecosystem. There is also the argument that KM plays a crucial role in
improving processes and services, strategic decision-making, and adapting and renewing an organisation.
The goal of KM is to aid action – providing "a knowledge pull" rather than the information overload most
people experience in healthcare FM. Other motivations for seeking better KM in healthcare FM include
patient safety, evidence-based care, and cost efficiency as the dominant drivers. The most evidence exists
for the success of such approaches at knowledge bottlenecks, such as infection prevention and control,
working safely, compliances, automated systems and reminders, and recall based on best practices. The
ability to cultivate, nurture and maximise knowledge at multiple levels and in multiple contexts is one of
the most significant challenges for those responsible for KM. However, despite the potential benefits,
applying KM principles in hospital facilities is still limited. There is a lack of understanding of how KM can
be effectively applied in this context, and few studies have explored the potential challenges and
opportunities associated with implementing KM principles in hospitals facilities for sustainable healthcare
delivery.
This study explores applying KM principles to support maintenance strategies in healthcare organisations.
The study also explores the challenges and opportunities, for healthcare organisations and FM
practitioners, in operationalising a framework which draws the interconnectedness between healthcare.
The study begins by defining healthcare FM and its importance in the healthcare industry. It then discusses
the concept of KM and the different types of knowledge that are relevant in the healthcare FM sector.
The study also examines the challenges that healthcare FM face in managing knowledge and how the
application of KM principles can help to overcome these challenges. The study then explores the different
KM strategies that can be applied in healthcare FM. The KM benefits include improved patient outcomes,
reduced costs, increased efficiency, and enhanced collaboration among healthcare professionals.
Additionally, issues like creating a culture of innovation, technology, and benchmarking are considered.
In addition, a framework that integrates the essential concepts of KM in healthcare FM will be presented
and discussed.
The field of KM is introduced as a complex adaptive system with numerous possibilities and challenges.
In this context, and in consideration of healthcare FM, five objectives have been formulated to achieve
the research aim. As part of the research, a number of objectives will be evaluated, including appraising
the concept of KM and how knowledge is created, stored, transferred, and utilised in healthcare FM,
evaluating the impact of organisational structure on job satisfaction as well as exploring how cultural
differences impact knowledge sharing and performance in healthcare FM organisations.
This study uses a combination of qualitative methods, such as meetings, observations, document analysis
(internal and external), and semi-structured interviews, to discover the subjective experiences of
healthcare FM employees and to understand the phenomenon within a real-world context and attitudes of healthcare FM as the data collection method, using open questions to allow probing where appropriate
and facilitating KM development in the delivery and practice of healthcare FM.
The study describes the research methodology using the theoretical concept of the "research onion". The
qualitative research was conducted in the NHS acute and non-acute hospitals in Northwest England.
Findings from the research study revealed that while the concept of KM has grown significantly in recent
years, KM in healthcare FM has received little or no attention. The target population was fifty (five FM
directors, five academics, five industry experts, ten managers, ten supervisors, five team leaders and ten
operatives). These seven groups were purposively selected as the target population because they play a
crucial role in KM enhancement in healthcare FM. Face-to-face interviews were conducted with all
participants based on their pre-determined availability. Out of the 50-target population, only 25 were
successfully interviewed to the point of saturation. Data collected from the interview were coded and
analysed using NVivo to identify themes and patterns related to KM in healthcare FM.
The study is divided into eight major sections. First, it discusses literature findings regarding healthcare
FM and KM, including underlying trends in FM, KM in general, and KM in healthcare FM. Second, the
research establishes the study's methodology, introducing the five research objectives, questions and
hypothesis. The chapter introduces the literature on methodology elements, including philosophical views
and inquiry strategies. The interview and data analysis look at the feedback from the interviews. Lastly, a
conclusion and recommendation summarise the research objectives and suggest further research.
Overall, this study highlights the importance of KM in healthcare FM and provides insights for healthcare
FM directors, managers, supervisors, academia, researchers and operatives on effectively leveraging
knowledge to improve patient care and organisational effectiveness
A strategic turnaround model for distressed properties
The importance of commercial real estate is clearly shown by the role it plays, worldwide, in the sustainability of economic activities, with a substantial global impact when measured in monetary terms. This study responds to an important gap in the built environment and turnaround literature relating to the likelihood of a successful distressed commercial property financial recovery. The present research effort addressed the absence of empirical evidence by identifying a number of important factors that influence the likelihood of a successful distressed, commercial property financial recovery. Once the important factors that increase the likelihood of recovery have been determined, the results can be used as a basis for turnaround strategies concerning property investors who invest in distressed opportunities. A theoretical turnaround model concerning properties in distress, would be of interest to ‘opportunistic investing’ yield-hungry investors targeting real estate transactions involving ‘turnaround’ potential. Against this background, the main research problem investigated in the present research effort was as follows: Determine the important factors that would increase the likelihood of a successful distressed commercial property financial recovery. A proposed theoretical model was constructed and empirically tested through a questionnaire distributed physically and electronically to a sample of real estate practitioners from across the globe, and who had all been involved, directly or indirectly, with reviving distressed properties. An explanation was provided to respondents of how the questionnaire was developed and how it would be administered. The demographic information pertaining to the 391 respondents was analysed and summarised. The statistical analysis performed to ensure the validity and reliability of the results, was explained to respondents, together with a detailed description of the covariance structural equation modelling method used to verify the proposed theoretical conceptual model. vi The independent variables of the present research effort comprised; Obsolescence Identification, Capital Improvements Feasibility, Tenant Mix, Triple Net Leases, Concessions, Property Management, Contracts, Business Analysis, Debt Renegotiation, Cost-Cutting, Market Analysis, Strategic Planning and Demography, while the dependent variable was The Perceived Likelihood of a Distressed Commercial Property Financial Recovery. After analysis of the findings, a revised model was then proposed and assessed. Both validity and reliability were assessed and resulted in the following factors that potentially influence the dependent variables; Strategy, Concessions, Tenant Mix, Debt Restructuring, Demography, Analyse Alternatives, Capital Improvements Feasibility, Property Management and Net Leases while, after analysis, the dependent variable was replaced by two dependent variables; The Likelihood of a Distressed Property Turnaround and The Likelihood of a Distressed Property Financial Recovery. The results showed that Strategy (comprising of items from Strategic Planning, Business Analysis, Obsolescence Identification and Property Management) and Concessions (comprising of items from Concessions and Triple Net Leases) had a positive influence on both the dependent variables. Property Management (comprising of items from Business Analysis, Property Management, Capital Improvements Feasibility and Tenant Mix) had a positive influence on Financial Turnaround variable while Capital Improvements Feasibility (comprising of items from Capital Improvements Feasibility, Obsolescence Identification and Property Management) had a negative influence on both. Demography (comprising of items only from Demography) had a negative influence on the Financial Recovery variable. The balance of the relationships were depicted as non-significant. The present research effort presents important actions that can be used to influence the turnaround and recovery of distressed real estate. The literature had indicated reasons to recover distressed properties as having wide-ranging economic consequences for the broader communities and the countries in which they reside. The turnaround of distressed properties will not only present financial rewards for opportunistic investors but will have positive effects on the greater community and economy and, thus, social and economic stability. Vii With the emergence of the COVID-19 pandemic crisis, issues with climate change and sustainability, global demographic shifts, changing user requirements, shifts in technology, the threat of obsolescence, urbanisation, globalisation, geo-political tensions, shifting global order, new trends and different generational expectations, it is becoming more apparent that the threat of distressed, abandoned and derelict properties is here to stay, and which will present future opportunities for turnaround, distressed property owners, as well as future worries for urban authorities and municipalities dealing with urban decay. The study concluded with an examination of the perceived limitations of the study as well as presenting a comprehensive range of suggestions for further research.Thesis (PhD) -- Faculty of Engineering, Built Environment and Information Technology, School of the built Environment, 202
Incorporating optimization in strategic conflict resolution for UAS traffic management
This study presents an approach to incorporate optimisation in the strategic conflict resolution service for unmanned aircraft systems (UAS) traffic management. A conventional approach in line with the First-Come, First-Served (FCFS) principle is introduced, following the generation of two types of flight plans (i.e., linear and area operations) with uncertainty buffers further taken into account. This approach is based on iteratively checking the availability of the shared airspace volumes. Next, an optimisation model is formulated, using the same common airspace representation, aiming at minimising the overall delay and deviation to the equivalent FCFS solution (i.e., fairness concern), subject to operational constraints including a time-based separation minima. Some potential implementations are also envisioned for the optimisation model under plausible operational scenarios. Finally, simulation experiments are performed where five case studies are designed, including FCFS and optimisation, as well as their hybrid and batch uses depending on the flight plan submission time. Sensitivity analysis is conducted to assess the impact of some specific model assumptions. Results suggest that, compared to FCFS, a notable delay reduction can be achieved with optimisation incorporated, which is due to the FCFS prioritisation scheme that is often not efficient.Single European Sky ATM Research 3 Joint Undertaking (SESAR JU) through the European Union’s Horizon 2020 Research and Innovation Program: Air Mobility Urban-Large Experimental Demonstrations (AMU-LED) (Grant Number: 101017702)
Innovate UK: 1002320
When to Replan? An Adaptive Replanning Strategy for Autonomous Navigation using Deep Reinforcement Learning
The hierarchy of global and local planners is one of the most commonly
utilized system designs in autonomous robot navigation. While the global
planner generates a reference path from the current to goal locations based on
the pre-built static map, the local planner produces a kinodynamic trajectory
to follow the reference path while avoiding perceived obstacles. To account for
unforeseen or dynamic obstacles not present on the pre-built map, ``when to
replan'' the reference path is critical for the success of safe and efficient
navigation. However, determining the ideal timing to execute replanning in such
partially unknown environments still remains an open question. In this work, we
first conduct an extensive simulation experiment to compare several common
replanning strategies and confirm that effective strategies are highly
dependent on the environment as well as the global and local planners. Based on
this insight, we derive a new adaptive replanning strategy based on deep
reinforcement learning, which can learn from experience to decide appropriate
replanning timings in the given environment and planning setups. Our
experimental results demonstrate that the proposed replanner can perform on par
or even better than the current best-performing strategies in multiple
situations regarding navigation robustness and efficiency.Comment: 7 pages, 3 figure
An Analysis Review: Optimal Trajectory for 6-DOF-based Intelligent Controller in Biomedical Application
With technological advancements and the development of robots have begun to be utilized in numerous sectors, including industrial, agricultural, and medical. Optimizing the path planning of robot manipulators is a fundamental aspect of robot research with promising future prospects. The precise robot manipulator tracks can enhance the efficacy of a variety of robot duties, such as workshop operations, crop harvesting, and medical procedures, among others. Trajectory planning for robot manipulators is one of the fundamental robot technologies, and manipulator trajectory accuracy can be enhanced by the design of their controllers. However, the majority of controllers devised up to this point were incapable of effectively resolving the nonlinearity and uncertainty issues of high-degree freedom manipulators in order to overcome these issues and enhance the track performance of high-degree freedom manipulators. Developing practical path-planning algorithms to efficiently complete robot functions in autonomous robotics is critical. In addition, designing a collision-free path in conjunction with the physical limitations of the robot is a very challenging challenge due to the complex environment surrounding the dynamics and kinetics of robots with different degrees of freedom (DoF) and/or multiple arms. The advantages and disadvantages of current robot motion planning methods, incompleteness, scalability, safety, stability, smoothness, accuracy, optimization, and efficiency are examined in this paper
Asymptotically optimal inspection planning via efficient near-optimal search on sampled roadmaps
Inspection planning, the task of planning motions for a robot that enable it to inspect a set of points of interest, has applications in domains such as industrial, field, and medical robotics. Inspection planning can be computationally challenging, as the search space over motion plans grows exponentially with the number of points of interest to inspect. We propose a novel method, Incremental Random Inspection-roadmap Search (IRIS), that computes inspection plans whose length and set of successfully inspected points asymptotically converge to those of an optimal inspection plan. IRIS incrementally densifies a motion-planning roadmap using a sampling-based algorithm and performs efficient near-optimal graph search over the resulting roadmap as it is generated. We prove the resulting algorithm is asymptotically optimal under very general assumptions about the robot and the environment. We demonstrate IRIS’s efficacy on a simulated inspection task with a planar five DOF manipulator, on a simulated bridge inspection task with an Unmanned Aerial Vehicle (UAV), and on a medical endoscopic inspection task for a continuum parallel surgical robot in cluttered human anatomy. In all these systems IRIS computes higher-quality inspection plans orders of magnitudes faster than a prior state-of-the-art method
Occupant-Centric Simulation-Aided Building Design Theory, Application, and Case Studies
This book promotes occupants as a focal point for the design process
Path and Motion Planning for Autonomous Mobile 3D Printing
Autonomous robotic construction was envisioned as early as the ‘90s, and yet, con-
struction sites today look much alike ones half a century ago. Meanwhile, highly
automated and efficient fabrication methods like Additive Manufacturing, or 3D
Printing, have seen great success in conventional production. However, existing
efforts to transfer printing technology to construction applications mainly rely on
manufacturing-like machines and fail to utilise the capabilities of modern robotics.
This thesis considers using Mobile Manipulator robots to perform large-scale
Additive Manufacturing tasks. Comprised of an articulated arm and a mobile base,
Mobile Manipulators, are unique in their simultaneous mobility and agility, which
enables printing-in-motion, or Mobile 3D Printing. This is a 3D printing modality,
where a robot deposits material along larger-than-self trajectories while in motion.
Despite profound potential advantages over existing static manufacturing-like large-
scale printers, Mobile 3D printing is underexplored. Therefore, this thesis tack-
les Mobile 3D printing-specific challenges and proposes path and motion planning
methodologies that allow this printing modality to be realised. The work details
the development of Task-Consistent Path Planning that solves the problem of find-
ing a valid robot-base path needed to print larger-than-self trajectories. A motion
planning and control strategy is then proposed, utilising the robot-base paths found
to inform an optimisation-based whole-body motion controller. Several Mobile 3D
Printing robot prototypes are built throughout this work, and the overall path and
motion planning strategy proposed is holistically evaluated in a series of large-scale
3D printing experiments
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