Zoekresultaten

Navigating Mexico’s Interoceanic Corridor

The Interoceanic corridor of Mexico stands as a pivotal infrastructure project poised to significantly enhance Mexico's national and regional economy. Anticipated to start the operations in 2025 under the auspice of the national government, this corridor represents a strategic counterpart to the Panama Canal, which faces capacity constraints due to climate change and environmental impacts. Positioned as a promising alternative for transporting goods from Asia to North America, this corridor will offer a new transport route, yet its real operational capacity and spatial impacts remains uncertain. In this paper, the authors undertake a preliminary, informed analysis leveraging publicly available data and other specific information about infrastructure capacities and economic environment to forecast the potential throughput of this corridor upon full operationalization and in the future. Applying simulation techniques, the authors simulate the future operations of the corridor according to different scenarios to offer insights into its potential capacity and impacts. Furthermore, the paper delves into the opportunities and challenges that are inherent in this project and gives a comprehensive analysis of its potential impact and implications.

Unraveling user type characteristics

Analysis of charging behavior of different type of users within the Amsterdam area. A definition of different type of users is deemed neccesary to forecast charging behaviour.---Analyse van laadgedrag van verschillende type gebruikers van de laadinfrastructuur in Amsterdam. Definitie van type gebruikers is nodig om voorspellingen over het verbruik te kunnen doen (EN).

Relevante factoren voor de prestatie in High Mix Low Volume productieomgevingen

Toeleverende bedrijven in de Brainport regio zijn veelal te typeren als high mix low volume (HMLV) productieomgevingen. Deze bedrijven kenmerken zich door een breed aanbod aan mogelijke producten (grote variëteit in producten), die veelal in lage volumes geproduceerd worden. Vaak zijn dit klantspecifieke producten die eenmalig, of incidenteel geproduceerd worden. Deze bedrijven focussen zich traditioneel op efficiënt gebruik van resources, waarbij bezettingsgraad en kostendekking relevant zijn. De toenemende klantvraag in de regio leidt tot druk op de productiecapaciteit. Een eerste intuïtieve reactie van deze bedrijven is om de bezettingsgraad van machines verder te verhogen. Om de kosten (Cost) beheersbaar te houden, wordt niet direct geïnvesteerd in extra capaciteit. Een ongewenst neveneffect is dat tijdigheid (Delivery, zoals levertijden, leverbetrouwbaarheid, flexibiliteit) en kwaliteit (Quality) verder onder druk komen te staan. De ogenschijnlijke tegenstrijdigheid tussen kosten en tijdigheid in deze HMLV-productieomgevingen, is een vaak terugkomend vraagstuk bij praktijkgerichte onderzoeken die door Fontys Technische Bedrijfskunde studenten uitgevoerd worden. Dit resulteert in de volgende onderzoeksvraag: Welke subaspecten zijn mogelijk relevant voor de prestatie met betrekking tot Quality, Delivery en Cost (QDC) van een HMLV-productieomgeving?

Forecasting cyanobacterial blooms using high frequency monitoring data

Cyanobacterial blooms can be toxic to humans swimming in affected waters. According to the European Bathing Water Directive bathing waters should be closed during cyanobacterial blooms. In the Netherlands, cyanobacteria monitoring in all official bathing water locations is usually performed every two weeks during the bathing season. In face of the large temporal and spatialvariability of cyanobacterial bloom dynamics this monitoring frequency however is too low for adequate early warnings to the public.High frequency monitoring and forecasting models can provide information on cyanobacterial blooms in between the regular monitoring dates and for a few days into the future. In the H2020 project EOMORES, we have combined observational data from a spectral camera (Ecowatch) near a Dutch bathing site with fluorescence data from an underwater drone to analyse the variability ofcyanobacterial blooms at short temporal and spatial scales. The results are used in a short term forecasting model of cyanobacterial blooms (AlgaeRadar) and a 3D scum forecasting model (EWACS). The AlgaeRadar is cross-validated with biweekly data from other bathing water sites and shows improved model performance compared to an earlier version that was built with only biweekly data.For the site with high-frequency chlorophyll observations the near-real time data are assimilated in the model to further enhance the model performance. Model performance of EWACS is verified using high frequency pictures from the Ecowatch station, showing scum layers on the water. This allowed us to validate and calibrate the EWACS model. Model validation abilities were in the pastalso limited by to the patchy nature and high temporal variability of the scum layers, which was not covered by sparse scum observations. With the resulting models, early warnings for cyanobacterial blooms are more reliable than those from the current practice that are merely based on biweekly monitoring data. For the protection of public health this provides better opportunities as well.

Genius forecasting vs. forecasting geniuses: an innovation (and) design viewpoint.

Demand Forecasting

Here, we delve into Demand Forecasting via Machine Learning, dissecting how to predict future demand using time-sensitive data. Westveer highlights key forecasting models, from the basic Simple Exponential Smoothing to the advanced SARIMA, applied to an electricity production dataset. The session, encapsulating the essence of data-driven forecasting, culminates in a compelling three-year predictive outlook, illustrating the transformative potential of machine learning in strategic planning and decision-making.