1,720,966 research outputs found
Smart retrofitting for human factors: a face recognition-based system proposal
Full text linkIndustry nowadays must deal with the so called “fourth industrial revolution”, i.e. Industry 4.0. This revolution is based on the introduction of new paradigms in the manufacturing industry such as flexibility, efficiency, safety, digitization, big data analysis and interconnection. However, human factors’ integration is usually not considered, although included as one of the paradigms. Some of these human factors’ most overlooked aspects are the customization of the worker’s user experience and on-board safety. Moreover, the issue of integrating state of the art technologies on legacy machines is also of utmost importance, as it can make a considerable difference on the economic and environmental aspects of their management, by extending the machine’s life cycle. In response to this issue, the Retrofitting paradigm, the addition of new technologies to legacy machines, has been considered. In this paper we propose a novel modular system architecture for secure authentication and worker’s log-in/log-out traceability based on face recognition and on state-of-the-art Deep Learning and Computer Vision techniques, as Convolutional Neural Networks. Starting from the proposed architecture, we developed and tested a device designed to retrofit legacy machines with such capabilities, keeping particular attention to the interface usability in the design phase, little considered in retrofitting applications along with other Human Factors, despite being one of the pillars of Industry 4.0. This research work’s results showed a dramatic improvement regarding machines on-board access safety
A unified framework to catalogue and classify digital games based on interaction design and validation through clustering techniques
Full text linkThe digital games industry has grown exponentially due to the diversification of games and the increasing multiplicity of the user target base. The market explosion and the great variety make digital game cataloguing and classification challenging issues whose effectiveness can advance scientific research and address design, development and distribution. Firstly, the present study reviews previous cataloguing for video and serious games through systematic literature review and, joining together the findings from the literature review, develops a unified cataloguing model based on five definitions. This model can aid designers in tailoring their applications and contribute to disseminating game design knowledge in academic research. Then, a matrix that correlates design principles and the cataloguing model’s metadata is applied to the cataloguing model, obtaining a unified classification system. Together, they offer a comprehensive framework for understanding the multifaceted landscape of digital games, addressing the limitations of existing domain-specific approaches and providing a versatile tool for game designers. Research validation exploits a two-stage cluster analysis using agglomerative hierarchical and k-means clustering on the data extracted from a sample of digital games. The results show the framework's effectiveness in categorizing digital games without a clear-cut distinction between video and serious games. The system's application in real-world scenarios suggests its potential to guide game development. Future work will refine the proposal based on feedback from digital game designers, expanding the research scope to include a broader range of games
A Multi-Criteria Analysis Method in Algorithm-Driven Design
No full textThe study presents a new method based on generative design and multi-criteria analysis to select the best design option accounting for engineering performance, economic feasibility and other design goals (e.g. novelty, compliance). A comparison between topology optimization and generative design is proposed and discussed. The method is applied to the design of a rocker for racing cars
Validation of computer vision-based ergonomic risk assessment tools for real manufacturing environments
Full text linkThis study contributes to understanding semi-automated ergonomic risk assessments in industrial manufacturing environments, proposing a practical tool for enhancing worker safety and operational efficiency. In the Industry 5.0 era, the human-centric approach in manufacturing is crucial, especially considering the aging workforce and the dynamic nature of the entire modern industrial sector, today integrating digital technology, automation, and sustainable practices to enhance productivity and environmental responsibility. This approach aims to adapt work conditions to individual capabilities, addressing the high incidence of work-related musculoskeletal disorders (MSDs). The traditional, subjective methods of ergonomic assessment are inadequate for dynamic settings, highlighting the need for affordable, automatic tools for continuous monitoring of workers’ postures to evaluate ergonomic risks effectively during tasks. To enable this perspective, 2D RGB Motion Capture (MoCap) systems based on computer vision currently seem the technologies of choice, given their low intrusiveness, cost, and implementation effort. However, the reliability and applicability of these systems in the dynamic and varied manufacturing environment remain uncertain. This research benchmarks various literature proposed MoCap tools and examines the viability of MoCap systems for ergonomic risk assessments in Industry 5.0 by exploiting one of the benchmarked semi-automated, low-cost and non-intrusive 2D RGB MoCap system, capable of continuously monitoring and analysing workers’ postures. By conducting experiments across varied manufacturing environments, this research evaluates the system’s effectiveness in assessing ergonomic risks and its adaptability to different production lines. Results reveal that the accuracy of risk assessments varies by specific environmental conditions and workstation setups. Although these systems are not yet optimized for expert-level risk certification, they offer significant potential for enhancing workplace safety and efficiency by providing continuous posture monitoring. Future improvements could explore advanced computational techniques like machine learning to refine ergonomic assessments further
A novel platform to enable the future human-centered factory
Full text linkThis paper introduces a web-platform system that performs semi-automatic compute of several risk indexes, based on the considered evaluation method (e.g., RULA-Rapid Upper Limb Assessment, REBA-Rapid Entire Body Assessment, OCRA-OCcupational Repetitive Action) to support ergonomics risk estimation, and provides augmented analytics to proactively improve ergonomic risk monitoring based on the characteristics of workers (e.g., age, gender), working tasks, and environment. It implements a body detection system, marker-less and low cost, based on the use of RGB cameras, which exploits the open-source deep learning model CMU (Carnegie Mellon University), from the tf-pose-estimation project, assuring worker privacy and data protection, which has been already successfully assessed in standard laboratory conditions. The paper provides a full description of the proposed platform and reports the results of validation in a real industrial case study regarding a washing machine assembly line composed by 5 workstations. A total of 15 workers have been involved. Results suggest how the proposed system is able to significantly speed up the ergonomic assessment and to predict angles and perform a RULA and OCRA analysis, with an accuracy comparable to that obtainable from a manual analysis, even under the unpredictable conditions that can be found in a real working environment
Augmented Reality for assembly operation training. Does immersion affect the recall performance?
No full textThis study aims at comparing three assembly training applications based on different XR technologies characterized by different degrees of immersion (i.e., an MR application based on Hololens 2, a desktop AR application and a digital handbook visualized on a monitor). A total of 54 subjects, recruited among students and personnel of Università Politecnica delle Marche, have been involved. They were assigned to 3 groups age and gender matching. Each group is asked to complete the training related to the assembly of a Lego commercial set (i.e., LEGO 10593), using one of the three considered applications. Results allows us to observe the effects of the immersion on the recall performances, assessed in terms of recall completion time, assembly mistakes, picking mistakes and sequence mistakes
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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