Browsing by Author "Dini, Gino"

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    Designing an AR interface to improve trust in Human-Robots collaboration
    (Elsevier, 2018-05-21) Palmarini, Riccardo; Fernández del Amo, Iñigo; Bertolino, Guglielmo; Dini, Gino; Erkoyuncu, John Ahmet; Roy, Rajkumar; Farnsworth, Michael
    In a global, e-commerce marketplace, product customisation is driven towards manufacturing flexibility. Conventional caged robots are designed for high volume and low mix production cannot always comply with the increasing low volume and high customisation requirements. In this scenario, the interest in collaborative robots is growing. A critical aspect of Human-Robot Collaboration (HRC) is human trust in robots. This research focuses on increasing the human confidence and trust in robots by designing an Augmented Reality (AR) interface for HRC. The variable affecting the trust involved in HRC have been estimated. These have been utilised for designing the AR-HRC. The proposed design aims to provide situational awareness and spatial dialog. The AR-HRC developed has been tested on 15 participants which have performed a “pick-and-place” task. The results show that the utilisation of AR in the proposed scenario positively affects the human trust in robot. The human-robot collaboration enhanced by AR are more natural and effective. The trust has been measured through an empirical psychometric method also presented in this paper.
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    Improving efficiency of industrial maintenance with context aware adaptive authoring in augmented reality
    (Elsevier, 2017-04-17) Erkoyuncu, John Ahmet; Fernández del Amo, Iñigo; Roy, Rajkumar; Dalle Mura, Michela; Dini, Gino
    Efficiency of industrial maintenance operation is significantly dependent on the skill and practice of the technicians involved. This paper demonstrates a novel approach to improve the maintenance efficiency through adaptive operational support using a context aware Augmented Reality (AR) technique that adapts with available data and the skill level of the technicians and without the need for prior working knowledge of AR. The AR system can be dynamically adapted by non-programmer maintenance technicians to improve the efficiency further.
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    An innovative user-centred support tool for Augmented Reality maintenance systems design: a preliminary study
    (Elsevier, 2018-05-21) Fernández del Amo, Iñigo; Galeotti, Elisa; Palmarini, Riccardo; Dini, Gino; Erkoyuncu, John Ahmet; Roy, Rajkumar
    Augmented Reality (AR) technologies in maintenance are demonstrated to positively impact on technicians’ work and performance. Current research in this area is mainly focused on solving technical challenges related with AR in industrial environments. Limited attention has been put into the user perception, ergonomics and usability aspects of AR systems design. This paper proposes an innovative user-centred design support tool for AR systems in maintenance contexts. The tool is based on the Analytic Hierarchy Process (AHP), which is a well-established multi-criteria decision-making approach. In this research, AHP is utilised for guiding designers in the evaluation of application-contexts and AR-technologies for selecting the most suitable and effective AR interaction solution. The tool’s validation has been conducted with twelve maintenance-experts in a design workshop using two case studies. The quantitative results obtained in both case studies reveal the applicability of the AHP model, as well as the effectiveness of the design support tool for complex decisions in AR for maintenance. The use of AHP methods for AR design enable experts to deal with complex and contrasting concepts and express a preference among them with a subjective judgement based on their personal understanding of the problem. Therefore, simplifying the design of AR systems for complex maintenance contexts.
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    A stochastic evaluation framework to improve the robustness of manufacturing systems
    (Taylor & Francis, 2023-01-03) Pagone, Emanuele; Haddad, Yousef; Barsotti, Ludovico; Dini, Gino; Salonitis, Konstantinos
    This work presents a framework to assess the robustness of manufacturing systems. Robustness, which is an indicator of the system’s ability to maintain its desired performance in face of disturbances, is quantified considering the variance of manufacturing system performance indicators. According to the framework, key objectives are first explicitly defined to guide a thorough exploration of the manufacturing system structural and dynamic characteristics. Several simulation experiments, orchestrated methodically through experimental design, are run and statistically analysed through analysis of variance (ANOVA) tests, including also financial implications. The framework has been tested and validated against a case study where the robustness of the manufacturing system with regard to six aerospace product types is evaluated. The mentioned case study proved that the framework has the potential to improve the robustness of manufacturing systems, identifying the most and least disruptive dispatching policies.