Design en onderzoek zijn twee kennisgebieden die elk hun eigen tradities, methoden, standaarden en praktijken hebben. Deze twee werelden lijken behoorlijk gescheiden, waarbij onderzoekers onderzoeken wat er is en ontwerpers visualiseren wat er zou kunnen zijn. Dit boek slaat een brug tussen beide werelden door te laten zien hoe design en onderzoek geïntegreerd kunnen worden om een nieuw kennisveld te ontwikkelen. Dit boek bevat 22 inspirerende beschouwingen die laten zien hoe de unieke kwaliteiten van onderzoek (gericht op het bestuderen van het heden) en ontwerp (gericht op het ontwikkelen van de toekomst) gecombineerd kunnen worden. Dit boek laat zien dat de transdisciplinaire aanpak toepasbaar is in een veelheid van sectoren, variërend van gezondheidszorg, stedelijke planning, circulaire economie en de voedingsindustrie. Het boek bestaat uit vijf delen en biedt een scala aan illustratieve voorbeelden, ervaringen, methoden en interpretaties. Samen vormen ze het kenmerk van een mozaïek, waarbij elk stukje een deel van het complete plaatje bijdraagt en alle stukjes samen een veelzijdig perspectief bieden op wat toegepast ontwerponderzoek is, hoe het wordt geïmplementeerd en wat de lezer ervan kan verwachten.
This study focuses on the feasibility of electric aircraft operations between the Caribbean islands of Aruba, Bonaire, and Curaçao. It explores the technical characteristics of two different future electric aircraft types (i.e., Alice and ES-19) and compares their operational requirements with those of three conventional types currently in operation in the region. Flight operations are investigated from the standpoint of battery performance, capacity, and consumption, while their operational viability is verified. In addition, the CO2 emissions of electric operations are calculated based on the present energy mix, revealing moderate improvements. The payload and capacity are also studied, revealing a feasible transition to the new types. The impact of the local climate is discussed for several critical components, while the required legislation for safe operations is explored. Moreover, the maintenance requirements and costs of electric aircraft are explored per component, while charging infrastructure in the hub airport of Aruba is proposed and discussed. Overall, this study offers a thorough overview of the opportunities and challenges that electric aircraft operations can offer within the context of this specific islandic topology.
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The constant growth of air traffic, especially in Europe, is putting pressure on airports, which, in turn, are suffering congestion problems. The airspace surrounding airport, terminal manoeuvring area (TMA), is particularly congested, since it accommodates all the converging traffic to and from airports. Besides airspace, airport ground capacity is also facing congestion problems, as the inefficiencies coming from airspace operations are transferred to airport ground and vice versa. The main consequences of congestion at airport airspace and ground, is given by the amount of delay generated, which is, in turn, transferred to other airports within the network. Congestion problems affect also the workload of air traffic controllers that need to handle this big amount of traffic.This thesis deals with the optimization of the integrated airport operations, considering the airport from a holistic point of view, by including operations such as airspace and ground together. Unlike other studies in this field of research, this thesis contributes by supporting the decisions of air traffic controllers regarding aircraft sequencing and by mitigating congestion on the airport ground area. The airport ground operations and airspace operations can be tackled with two different levels of abstractions, macroscopic or microscopic, based on the time-frame for decision-making purposes. In this thesis, the airport operations are modeled at a macroscopic level.The problem is formulated as an optimization model by identifying an objective function that considers the amount of conflicts in the airspace and capacity overload on the airport ground; constraints given by regulations on separation minima between consecutive aircraft in the airspace and on the runway; decision variables related to aircraft entry time and entry speed in the airspace, landing runway and departing runway choice and pushback time. The optimization model is solved by implementing a sliding window approach and an adapted version of the metaheuristic simulated annealing. Uncertainty is included in the operations by developing a simulation model and by including stochastic variables that represent the most significant sources of uncertainty when considering operations at a macroscopic level, such as deviation from the entry time in the airspace, deviation in the average taxi time and deviation in the pushback time. In this thesis, optimization and simulation techniques are combined together by developing two methods that aim at improving the solution robustness and feasibility. The first method acts as a validation tool for the optimized solution, and it improves the robustness of solution by iteratively fine-tuning some of the optimization model input parameters. The second method embeds the optimization in a simulation environment by taking full advantage of the sliding window approach and creating a loop for a continuous improvement of the optimized solution at each window of the sliding window approach. Both methods prove to be effective by improving the performance, lowering the total amount of conflicts up to 23.33% for the first method and up to 11.2% for the second method, however, in contrast to the deterministic method, the two methods they are not able to achieve a conflict-free scenario due to the effect of uncertainty.In general, the research conducted in this thesis highlights that uncertainty is a factor that affects to a large extent the feasibility of optimized solution when applied to real-world instances, and it, moreover, confirms that using simulation together with optimization has the potentiality toivdeal with uncertainty. The framework developed can be potentially applied to similar problems and different optimization solving methods can be adapted to it.Keywords: Optimization, Simulation, Integrated airport operations, Uncertainty
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Production processes can be made ‘smarter’ by exploiting the data streams that are generated by the machines that are used in production. In particular these data streams can be mined to build a model of the production process as it was really executed – as opposed to how it was envisioned. This model can subsequently be analyzed and stress-tested to explore possible causes of production prob-lems and to analyze what-if scenarios, without disrupting the production process itself. It has been shown that such models can successfully be used to diagnose possible causes of production problems, including scrap products and machine defects. Ideally, they can even be used to model and analyze production processes that have not been implemented yet, based on data from existing production pro-cesses and techniques from artificial intelligence that can predict how the new process is likely to be-have in practice in terms of data that its machines generate. This is especially important in mass cus-tomization processes, where the process to create each product may be unique, and can only feasibly be tested using model- and data-driven techniques like the one proposed in this project. Against this background, the goal of this project is to develop a method and toolkit for mining, mod-elling and analyzing production processes, using the time series data that is generated by machines, to: (i) analyze the performance of an existing production process; (ii) diagnose causes of production prob-lems; and (iii) certify that a new – not yet implemented – production process leads to high-quality products. The method is developed by researching and combining techniques from the area of Artificial Intelli-gence with techniques from Operations Research. In particular, it uses: process mining to relate time series data to production processes; queueing networks to determine likely paths through the produc-tion processes and detect anomalies that may be the cause of production problems; and generative adversarial networks to generate likely future production scenarios and sample scenarios of production problems for diagnostic purposes. The techniques will be evaluated and adapted in implementations at the partners from industry, using a design science approach. In particular, implementations of the method are made for: explaining production problems; explaining machine defects; and certifying the correct operation of new production processes.
Cross-Re-Tour supports European tourism SME while implementing digital and circular economy innovations. The three year project promotes uptake and replication by tourism SMEs of tools and solutions developed in other sectors, to mainstream green and circular tourism business operations.At the start of the project existing knowledge-gaps of tourism SMEs will be researched through online dialogues. This will be followed by a market scan, an overview of existing state of the art solutions to digital and green constraints in other economic sectors, which may be applied to tourism SME business operations: water, energy, food, plastic, transport and furniture /equipment. The scan identifies best practices from other sectors related to nudging of clients towards sustainable behaviour and nudging of staff on how to best engage with new tourism market segments.The next stage of the project relates to two design processes: an online diagnostic tool that allows for measuring and assessing (160) SME’s potential to adapt existing solutions in digital and green challenges, developed in other economic sectors. Next to this, a knowledge hub, addresses knowledge constraints and proposes solutions, business advisory services, training activities to SMEs participating. The hub acts as a matchmaker, bringing together 160 tourism SMEs searching for solutions, with suppliers of existing solutions developed in other sectors. The next key activity is a cross-domain open innovation programme, that will provide 80 tourism SMEs with financial support (up to EUR 30K). Examples of partnerships could be: a hotel and a supplier of refurbished matrasses for hospitals; a restaurant and a supplier of food rejected by supermarkets, a dance event organiser and a supplier of refurbished water bottles operating in the cruise industry, etc.The 80 cross-domain partnerships will be supported through the knowledge hub and their business innovation advisors. The goal is to develop a variety of innovative partnerships to assure that examples in all operational levels of tourism SMEs.The innovation projects shall be presented during a show-and-share event, combined with an investors’ pitch. The diagnostic tool, market scan, knowledge hub, as well as the show and share offer excellent opportunities to communicate results and possible impact of open innovation processes to a wider international audience of destination stakeholders and non-tourism partners. Societal issueSupporting the implementation of digital and circular economy solutions in tourism SMEs is key for its transition towards sustainable low-impact industry and society. Benefit for societySolutions are already developed in other sectors but the cross-over towards tourism is not happening. The project bridges this gap.
In De Haagse Hogeschool werken de lectoraten vanuit faculteiten, dicht bij het onderwijs, nauw samen in zeven kenniscentra. Deze kenniscentra zijn de verbinding tussen de regio, met zijn actuele thema’s (vaak gelinkt aan het missiegedreven innovatiebeleid van de overheid) en het onderwijs en onderzoek van de Haagse Hogeschool. De zeven kenniscentra van De Haagse Hogeschool zijn: Cybersecurity, Digital Operations & Finance, Global & Inclusive Learning, Global Governance, Health Innovation, Governance of Urban Transitions & Mission Zero. Deze kenniscentra zijn in opstartende fase en worden ondersteund door centrale diensten. De Haagse Hogeschool kiest voor versterking van de onderzoeksinfrastructuur die centraal staat in de kenniscentra: ‘de Haagse Labs’. Praktijkgericht onderzoek vindt in deze omgevingen plaats als een vervlechting van onderwijs (studenten en docenten), onderzoek, het werkveld en maatschappelijke partners. Sommige labs hebben een tijdelijk karakter, andere, zoals de hogeschool zelf, zijn continu een omgeving waarbinnen onderzoek gedaan wordt. De Haagse Labs zijn bij uitstek de plek waarin nauw samengewerkt wordt met andere hogescholen of kennisinstellingen (veelal zijn ze ontstaan uit een samenwerking zoals The Green Village, of het Basalt SmartLab). De keuze voor de Haagse Labs geeft verdieping aan regionale samenwerkingen en bijbehorende speerpunten. De huidige, meer informele inrichting, kan met behulp van Impuls 2020, verder structuur krijgen, leiden tot een betere kennisdeling tussen de kenniscentra heen en de regionale netwerkvorming versterken. Naast het formaliseren van ‘de Haagse Labs’ zetten we in op zichtbaarheid van de Hogeschool in de regio door te investeren in communicatie (denk bijvoorbeeld aan het opzetten van podcasts, en digitale middelen in Corona-tijd). Die profilering van ons onderzoek wordt verder ondersteunt door een traject rond visievorming en strategische positionering. De kenniscentra zullen begeleid worden om einde 2021 een visie te ontwikkelen met bijbehorende acties om de rol van de hogeschool in de regio te versterken.
