1,720,983 research outputs found
A drone service to support the Isle of Wight NHS in the UK
No full textWith interest in drone delivery growing throughout the world, this study explores the challenges associated with developing a medical drone logistics service to support the National Health Service on the Isle of Wight in the UK. Two separate trials were undertaken to investigate the potential for drone delivery in this area, carrying medical goods and aseptic cancer medicines. The first trial took place using a fixed-wing drone during COVID-19 lockdown restrictions, whilst the second used hybrid fixed-wing vertical take-off and landing (VTOL) drone. Key findings suggested that electric VTOL drones present significant advantages in terms of point-to-point direct servicing, emissions, and time-savings, though range and payload limitations introduce further challenges. Legislation, airspace management, and technology findings were also made, with legacy regulations causing barriers to carriage of medical goods by drone. Future work seeks to understand the costs and benefits of a more sustained service in a medical setting
Quantifying weather tolerance criteria for delivery drones - a UK case study
No full textAs demand for final mile delivery has increased, the use of delivery drones is being explored in many countries, including the UK. Despite offering perceived benefits over existing methods in terms of delivery speed and reliability, there is little understanding of the design criteria needed for drones to actually realise them. This paper investigates how reliability and resilience of deliveries vary by transport mode, relating to the delivery success (i.e., can a delivery be made in a given timewindow), and the flexibility of this success (i.e., how many different time windows are possible).Comparing the performance of current UK ground transport modes and drones using historic weather and reliability data, a review of the factors that contribute to what makes a reliable and weather resistant drone service is presented. Results suggested that a significant wind tolerance would be required to achieve a level of service equal to ground transportation, with VTOL platforms requiring tolerances ranging from 14 m/s (Solent region), to more than 23 m/s (Scottish Hebrides). Fixed-wing platform tolerances were not as high, with a tolerance of 10 m/s achieving flights on almost all days in all case study areas.It is likely that some locations cannot reliably be served by drone and must depend on contingency options when flights are not possible. With significant variations in tolerance requirements, and notable seasonal variances, applications of delivery drones should be considered on a case-by-case basis, comparing to existing modes, to ensure reliable supply chains are realised.</p
Understanding the challenges of drone medical logistics services in developed nations
No full textUncrewed Aerial Vehicles (UAVs, or drones) have attracted considerable interest as a potential alternative logistics mode, with many studies suggesting that drones will offer faster and more reliable goods transport, whilst reducing associated energy, emissions, and costs compared to traditional modes. This may be true in some select settings and industries, but there are many barriers to achieving widespread implementation, particularly in developed nations.The number of trials of drone delivery has increased in recent years, with the majority being proof-of-concept experiments, never achieving sustained commercial operation. Furthermore, several major players in the logistics industry, e.g., Amazon and DHL, have more recently scaled back their development of such technologies, suggesting there are greater challenges that make the integration of UAVs into existing logistics operations less viable. Arguably the most successful drone delivery system in the world is primarily based in Rwanda, where Zipline routinely deliver blood stocks from central hubs, reaching hospitals significantly faster and more reliably than by road. To the authors’ knowledge, Zipline remains the only commercial national drone logistics operation currently active in the world, posing the question as to why take-up has not been more rapid.There is a general trend towards using drones in the medical sector, where there is potential for expedited delivery of time-sensitive, high-value cargoes to have significant impacts on patient care. Evidence identifies a range of trials carrying goods, such as diagnostic specimens, vaccines, and blood stocks, where delivery times are critical to ensure goods are outside of controlled conditions for as little time as possible or to improve the health outcomes of patients. Whilst this may give some perceived benefits, current legislation with regards to good carriage has not been designed for or applied to autonomous, uncrewed aircraft. In the case of UAVs, their vibration profiles can be significantly different to that of traditional land-based modes, with higher frequencies potentially damaging some of the more sensitive medical products (e.g., haemolysis of blood, etc.). As a result, UAV operators will need to evidence that their platforms do not adversely affect the products carried.To a certain extent, packaging may assist in this endeavour; however, regulations and industry standards may also limit the scope to adapt designs and hence limit the opportunities for UAVs. Dangerous goods regulations prescribe specific design criteria to reduce the likelihood of spillage and damage, and medical regulators require that temperature ranges are not exceeded during transit. This has led to rigorously tested standardised packaging being widely adopted in developed nations, leaving little margin for change which impacts on the minimum carrying requirements for UAVs. Furthermore, until UAVs are more widely adopted, these standards are unlikely to change, meaning that in the short term, drone platforms need to be selected such that the weights and volumes of existing payloads can be carried.Additional safety precautions in developed nations limit the use of package drop systems, meaning vertical take-off and landing (VTOL) functionality will be required to realise the benefits of point-to-point delivery. Meanwhile, a fixed-wing element will enable a greater travel range, particularly if electrically powered. Thus, for anything meaningful to be carried, it is likely that the UAVs used will be fairly large, and VTOL-fixed-wing hybrid setups. In the authors’ experience of testing such technology, a 5-metre wingspan drone with 0.75-metre propellors meets these requirements. Despite meeting the payload requirements, the selected drone does introduce some further limitations with regards to the availability of practical landing sites which don’t detract from their existing function (e.g., removal of public greenspace). The addition of overflight risk also restricts the scope for straight-line flights in order to reduce safety concerns in the event of a crash.Amongst further challenges, it may appear that drone services in developed nations are extremely limited in scope; however, there are still some use cases that will benefit from such a service. Factors that limit the potential of surface transportation, such as road quality, detour index/circuity factor (i.e., how indirect routes are), and the payload due to be carried, can all contribute to how great the benefits of a drone service can be. Through a comparison of successful delivery services, this research also explores what it takes to better existing logistics methods
Investigating the scope for integrating uncrewed aerial vehicles (UAVs) into mixed-mode fleets to support national health service (NHS) logistics operations
No full textLocal healthcare logistics systems carry a variety of cargoes to ensure patient care is maintained, though they account for a significant proportion of the total healthcare emissions footprint. Legislation and self-defined targets are driving the UK's National Health Service (NHS) to make their carbon impact net-zero; thus, this research investigated the scope for a multi-modal logistics network with vans, bikes, and uncrewed aerial vehicles/UAVs to support this goal. The unique contributions of this study include new approaches to solving the heterogeneous two-echelon vehicle routing problems associated with the collection of diagnostic specimens from community clinics. After initial investigations using a column generation heuristic, an adaptation of the Clarke and Wright Savings Algorithm with a bin packing algorithm was developed to evaluate the scope for integrating multi-mode fleets. The implications of good distribution practices and dangerous goods regulations were also explored, and new procedures were proposed. Meanwhile, an analysis of weather reliability criteria found that a 14 m/s peak gust tolerance would be essential for UAVs to match business-as-usual performance levels. Accounting for practicalities around payloads and delivery site constraints, case study data from the Solent region (UK) were applied to the algorithm. In a baseline case, 76 doctor's surgeries were served by 4 vans, costing £190k and generating 7.7 T CO2-eq. per year. It was found that introducing a mixed-mode system with 1 van and 10 UAVs could enable transit time reductions of up to 84% (209 mins to 33 mins), however, the resulting increase in operating costs (+133%, +£253k per year) and emissions (+211%, +19.5 T CO2-eq. per year) may prove difficult to justify. Furthermore, the absolute time savings may be inconsequential to patient care and the wider supply chain. In another case study involving 22 surgeries, van and bike combinations gave the lowest emission outcomes, with CO2-eq. reductions of up to 7% for a 3% increase in costs
An adapted savings algorithm for planning heterogeneous logistics with uncrewed aerial vehicles
No full textThis paper proposes a new extension to the Sustainable Specimen Collection Problem (SSCP), where medical specimens are transported by vans, bikes, and uncrewed aerial vehicles (UAVs, or drones) from local medical practices/offices to a central hospital laboratory for analysis, employing a two-echelon collection approach. Time restrictions from existing operations and literature are also introduced, with the study being formulated as a weighted multi-objective problem seeking to minimise (i) operating costs; (ii) transit times; and (iii) energy/environmental impacts. A new adaptation of the Clarke and Wright Savings Algorithm is subsequently presented to create collection rounds that leverage each mode's strengths. Subsequently, routes are compiled into workable fixed shifts using a modified bin-packing algorithm in each iteration. The approach of this study is based on a case study of the UK's National Health Service (NHS), involving the collection of pathology samples using traditional vans operating within fixed time slots. Using case study data from the Solent region (England), a novel test instance generation methodology was also developed, whereby realistic site positioning and origin-destination travel data are captured to enable effective algorithm experimentation. The findings from applying the proposed algorithm to a set of test instances based on this methodology are subsequently discussed, where it was found that the adapted savings and bin-packing approach produced effective solutions quickly, with 90% of all large instances (200 sites) being solved within 15 min. Further algorithm developments and the application of the devised problem/methodologies are also discussed.</p
Understanding the viability of drone logistics for assisting pathology transportation: a case study in Dorset, UK
No full textIntegrating drones into medical logistics could improve patient care through expedited delivery from remote areas, whilst reducing the NHS’ environmental impact. This research assesses the feasibility of integrating drones into fixed-round van pathology logistics. Historical data on patient diagnostic collections were analysed from 72 GP surgeries in Dorset, UK, delivering to three hospitals. The impact on van numbers, CO2 emissions, time, distance and cost from introducing drones to serve specific surgeries were quantified using optimisation techniques. The results suggested that introducing 5 drones serving 13 surgeries removed 4 vans, decreased daily CO2 emissions by 77 kg and mileage by 51% but to the detriment of overall daily cost, which increased by 58%. The surgeries served by drones experienced an 83%reduction in average sample delivery time over business-as-usual, with potential positive impacts on bleed-to-diagnosis times
Improving the efficiency of patient diagnostic specimen collection with the aid of a multi-modal routing algorithm
No full textThe Sustainable Specimen Collection Problem (SSCP), in which diagnostic specimens are collected from GP surgeries (doctor’s office/clinics) and subsequently transported to a hospital laboratory for analysis using more sustainable transport modes, is introduced in this paper. Using a weightedobjective function, we solve a new multi-objective problem using cycle consolidation to limit driving time and the numbers of vans used whilst improving overall service quality, reducing costs and emissions. This particular heterogeneous vehicle routing problem is explored and applied to tworeal-world case studies in the UK, where 97 and 22 sites (respectively) are currently served, using a column generation based heuristic algorithm with some additional improvement heuristics. The results demonstrated a potential improvement in the system’s maximum delivery time between 41% and 74% compared to business-as-usual activity using solely road vehicles. Road vehicle (van) fleets could be reduced by up to 40%, and the total driving time across the fleet by between 41% and 65%. Operational costs were estimated to increase by up to 38%, though additional workloads for gig-economy cycle couriers and improvement in specimen quality and service reliability may make this trade-off worthwhile. Tailpipe CO2 emissions were also reduced by up to 43%. The proposed algorithm was effective, reducing computational time by up to 99% whilst achieving an average of 5% deviation from optimality
Assessment of primary care services operational resilience by patients: implications for COVID-19 recovery
No full textWhile the National Health Service of the United Kingdom recovers from COVID-19, it's crucial to assess the impact of the dynamic capabilities within its healthcare services to ensure future public health protection. This study adopts mixed methods of literature review and surveys. Survey findings reveal that agility, flexibility, and building redundancy proved instrumental in reconfiguring resource foundations swiftly and fostering new partnerships. These actions were essential for sustaining service quality and efficiency. The analysis recommends that patients and healthcare professionals should co-design a technology-driven primary care service provision that is person-centric and digitally inclusive. Furthermore, primary care service stakeholders should develop targeted collaborations, and workforce development should be a priority to increase medical reserve in the healthcare system. This research provides empirical evidence, enabling the National Health Service to persist in enhancing dynamic capabilities and reinforcing resilience for anticipated and unforeseen future challenges
Are Drones Safer Than Vans?: A Comparison of Routing Risk in Logistics
No full textDrones are being considered as an alternative transport mode to ground based van networks. Whilst the speed and application of such networks has been extensively studied, the safety aspects of such modes have not been directly compared. Using UK Department for Transport data and a drone flight planning approach using a probabilistic risk model, an estimation of fatality rates for seven origin-destination (O-D) pairs was undertaken in a theoretical case study of medical deliveries in the Southampton area of the UK. Using failure rates from the literature, results indicated that commercial vehicles (<3.5 T) were safer than drones in all cases by ≤12.73 (12.73 times more fatalities by drone than by road). With the O-D pairs covering a range of localities, routes covering more mileage on minor roads were found to be the least safe but were still ≥1.87 times safer than drone deliveries. Sensitivity tests on the modelled drone failure rates suggested that the probability of a failure would have to be ≤5.35×10−4 per flight-hour for drone risk to be equal to van risk. Investigating the circuity of drone routes (how direct a route is) identified that level of risk had a significant impact on travel distances, with the safest paths being 273% longer than the riskier, straight-line flight equivalent. The findings suggest that the level of acceptable risk when designing drone routes may negatively impact on the timeliness of drone deliveries due to the increased travel distance and time that could be incurred
Drones: the scope for integration into multi-modal urban logistics services
No full textUncrewed Aerial Vehicles (UAVs, or drones) are seen as a potential new logistics mode, both for urban areas and beyond, that could reduce service times, energy consumption, tailpipe atmospheric emissions, and numbers of van/truck-based trips, whilst also improving accessibility in hard-to-reach locations. Drones have been used successfully across many sectors from surveillance and security to photography and surveying, inspection of infrastructure and agriculture, aid provision, and environmental monitoring. Most of these activities involve flights within Visual-Line-of-Sight (VLOS), where the operator retains visual contact with the drone at all times. In contrast, large-scale commercial drone logistics services (i.e., payload delivery) require flights Beyond-Visual-Line-of-Sight (BVLOS) that entail more risk and require specific permissions, particularly in densely populated urban areas, which are key reasons why such services are not prevalent except for some medical use cases in Africa.With a particular focus on medical use cases, and using first-hand experience of operating BVLOS flights, this chapter will discuss the practical realities of integrating drones into existing urban logistics supply chain infrastructures, specifically:i) Public acceptance of drones for urban logistics purposes.ii) Payload capabilities of drones relative to the service demand.iii) Adherence to client quality assurance requirements when transporting sensitive payloads.iv) Implications of dangerous goods regulations for drone payloads.v) Implications of air and ground risks on route planning and optimisation.vi) Mechanisms for integrating drones alongside crewed aircraft in shared airspace.vii) Overall service reliability given weather conditions and minimal risk routing.viii) Cost implications of utilising drones as part of multi-modal urban logistics supply chains.<br/
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