PurposeThis study aims to identify variability in aviation operators in order to gain greater understanding of the changes in aviation professional groups. Research has commonly addressed human factors and automation in broad categories according to a group’s function (e.g., pilots, air traffic controllers [ATCOs], engineers). Accordingly, pilots and Air Traffic Controls (ATCOs) have been treated as homogeneous groups with a set of characteristics. Currently, critical themes of human performance in light of systems’ developments place the emphasis on quality training for improved situational awareness (SA), decision-making and cognitive load.Design/methodology/approachAs key solutions centre on the increased understanding and preparedness of operators through quality training, the authors deploy an iterative mixed methodology to reveal generational changes of pilots and ATCOs. In total, 46 participants were included in the qualitative instrument and 70 in the quantitative one. Preceding their triangulation, the qualitative data were analysed using NVivo and the quantitative analysis was aided through descriptive statistics.FindingsThe results show that there is a generational gap between old and new generations of operators. Although positive views on advanced systems are being expressed, concerns about cognitive capabilities in the new systems, training and skills gaps, workload and role implications are presented.Practical implicationsThe practical implications of this study extend to different profiles of operators that collaborate either directly or indirectly and that are critical to aviation safety. Specific implications are targeted on automation complacency, bias and managing information load, and training aspects where quality training can be aided by better understanding the occupational transitions under advanced systems.Originality/valueIn this paper, the authors aimed to understand the changing nature of the operators’ profession within the advanced technological context, and the perceptions and performance-shaping factors of pilots and ATCOs to define the generational changes.
Het aantal dierlijke graverijen in fysieke infrastructuren, waaronder waterkeringen, spoordijken en autowegen, neemt de laatste jaren hard toe. Dit komt door exponentiële groei van de bever die in Nederland een beschermde status heeft. Waterschappen geven aan dat de inspectie en detectie van graverijen door bevers geen gemakkelijke opgave is. De gevolgen voor de veiligheid van primaire waterkeringen en spoordijken kunnen aanzienlijk zijn. Om grip te krijgen op graverijen, zijn tot op heden verschillende aanpakken gehanteerd van lopen door watergangen in waadpakken met prikstokken t/m de inzet van GPR, camera- en sonartechnologie alsook getrainde speurhonden. Tot op heden is er nog geen oplossing gevonden voor ongewenste graverijen door bevers. Met dit onderzoeksproject wordt nieuwe technologische kennis ontwikkeld en toegevoegd aan de state-of-the-art op het gebied van detectie van beveractiviteiten (graverijen). In dit project wordt een robot platform (hardware/software) ontwikkeld dat beverschades aan kritieke publieke infrastructuren kan detecteren en monitoren. Hiervoor zijn robuuste technologieën nodig die gangenstelsels/kamers kunnen waarnemen (perceptie), zelfstandig in kaart kunnen brengen (autonome navigatie). Daarnaast moeten operators (veldwerkers) het robot platform eenvoudig kunnen toepassen in hun dagelijkse gebruik (mens-robot interactie). Het consortium bestaat uit publiek partijen (waterschappen, Rijkswaterstaat, provincies), prorail technologieontwikkelaars en dienstleveranciers (MKBs, ander privaat partijen), onderzoeksgroepen van Saxion (lectoraten SMART en TCI), opleidingen en overkoepelende innovatie boosters. Zij zetten kennis en capaciteit in om antwoord te geven op de centrale onderzoeksvraag: “Welke bestaande navigatie- en perceptietechnologieën kunnen binnen een periode van 2 jaar worden doorontwikkeld tot de realisatie en inzet van een gebruiksvriendelijk beverbeheer robotplatform waarmee ongewenste beveractiviteiten vroegtijdig kunnen worden gedetecteerd en herstelmaatregelen effectief kunnen worden ingezet?” Opbrengsten van het project dragen bij aan duurzaam beverbeheer, preventieve detectie en kosteneffectieve inzet van maatregelen die nadien op basis van de verschillende detectiemethoden kunnen worden ontwikkeld. Daarnaast vindt borging van (technologische) kennis plaats in alle deelnemende partijen en opleidingen.
In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
During the coronavirus pandemic, the use of eHealth tools became increasingly demanded by patients and encouraged by the Dutch government. Yet, HBO health professionals demand clarity on what they can do, must do, and cannot do with the patients’ data when using digital healthcare provision and support. They often perceive the EU GDPR and its national application as obstacles to the use of eHealth due to strict health data processing requirements. They highlight the difficulty of keeping up with the changing rules and understanding how to apply them. Dutch initiatives to clarify the eHealth rules include the 2021 proposal of the wet Elektronische Gegevensuitwisseling in de Zorg and the establishment of eHealth information and communication platforms for healthcare practitioners. The research explores whether these initiatives serve the needs of HBO health professionals. The following questions will be explored: - Do the currently applicable rules and the proposed wet Elektronische Gegevensuitwisseling in de Zorg clarify what HBO health practitioners can do, must do, and cannot do with patients’ data? - Does the proposed wet Elektronische Gegevensuitwisseling in de Zorg provide better clarity on the stakeholders who may access patients’ data? Does it ensure appropriate safeguards against the unauthorized use of such data? - Does the proposed wet Elektronische Gegevensuitwisseling in de Zorg clarify the EU GDPR requirements for HBO health professionals? - Do the eHealth information and communication platforms set up for healthcare professionals provide the information that HBO professionals need on data protection and privacy requirements stemming from the EU GDPR and from national law? How could such platforms be better adjusted to the HBO professionals’ information and communication needs? Methodology: Practice-oriented legal research, semi-structured interviews and focus group discussions will be conducted. Results will be translated to solutions for HBO health professionals.
