1,720,982 research outputs found
Digital twin-based reinforcement learning framework: application to autonomous mobile robot dispatching
No full textThis paper proposes a new framework for embedding an Intelligent Digital Twin (DT) in a production system with the objective of achieving more efficient real-time production planning and control. For that purpose, the Intelligence Layer is based on Reinforcement Leaning (RL) and Deep RL (DRL) algorithms. The use of this control instead of parametric simulation-based optimization approach allows to benefit from the separation between the training and execution phase. To ensure consistency and reusability, this work presents a standardized framework, based on a formal methodology, that specifies how the various components of the DT-based RL architecture interact over time to achieve essential real-time concurrency and synchronization aspects. Experiments are conducted in a small-scale production system where material handling operations are performed by an Autonomous Mobile Robot (AMR) in an Industry 4.0 Laboratory. Results showed how synchronized state updates between the Physical and Cyber World are used within the Decision Layer to ensure real-time response for the AMR dispatching requests. Finally, to deal with continuous and high-dimensional state spaces, the Deep Q-Network is implemented. The findings of an extensive computational study reveal that implementing the DT-based DRL solution leads to improved efficiency and robustness when compared to conventional dispatching rules
NOVEL METHODS FOR TEACHING SIMULATION: STRENGTHENING DIGITAL TWIN DEVELOPMENT
No full textThis article proposes new methods for teaching Discrete Event Simulation (DES) in manufacturing systems. Over the last four decades, numerous books have offered methods for teaching DES as what-if analysis tools for addressing stochastic problems. However, the emergence of the Digital Twin (DT) concept has posed challenges for such traditionally designed DES models. These models often struggle to evolve effectively into Real-Time Simulators (RTS). RTS are connected DES models embedded as kernels in the DT framework and synchronized based on real-time sensor data streams. Thus, the objective of this work is to introduce teaching methods that provide deeper insights into designing the needed high-fidelity DES models capable of evolving into RTS. It also illustrates how the Immersive Learning approach is employed to immerse students in a manufacturing environment through Virtual Reality (VR) experiences, allowing them to grasp key concepts such as granularity levels and synchronization challenges in deploying a DT
TOWARDS STANDARDIZING THE INTEGRATION OF DIGITAL TWINS IN MANUFACTURING SYSTEMS
No full textIndustrial sectors are increasingly prioritizing the integration of Digital Twin (DT) technology into their operations to enhance manufacturing system decision-making. However, implementing DTs remains highly challenging due to its novelty, highlighting the pressing need for the development of more formal methodologies to guide its effective implementation. Therefore, the aim of this paper is to present ongoing research concerning DT design and implementation in accordance with the ISO 23247 standard. The objective of this DT is to embed real-time Autonomous Mobile Robot dispatching decision in a small-scale production system. The present work outlines the essential steps for transitioning from a traditional Discrete Event Simulation model to a Real-Time Simulation, ensuring connectivity and synchronization with the physical system to achieve efficient implementation. It also exhibits the benefit of using rigorous formalism clarifying the complex sequencing involved in capturing and transmitting real-time sensor data between physical and cyber system
Framework for Smart Online 3D Bin Packing Using Augmented Reality
No full textGiven the growth of the e-commerce market and the increasing demands, it is crucial to come up with an efficient and optimized way to pack products. Furthermore, the advent of new technologies and the fourth industrial revolution opened up a range of research areas and opportunities to expand the scope of classic packing applications. In this context, this work presents a framework to assist operators with an immersive application to assure smart packing. For that purpose, several heuristics that take into consideration multiple conditions imposed by the nature of the product are embedded to solve the online 3D Bin Packing Problem. Then the best packing solution is sent to the Augmented Reality developed application to immerse the operator in the packing process. This framework is designed for industries that rely on manual packing and aims to automate the process and/or provide intelligent decision-aid tools to ensure a smart packing process
A SIMULATION-BASED OPTIMIZATION APPROACH TOWARDS HUMAN-CENTRIC SCHEDULING IN PRESENCE OF HETEROGENEOUS WORKFORCE
No full textIndustry 5.0 places a strong emphasis on human-centric scheduling, recognizing that by prioritizing the well-being and needs of workers, it not only enhances productivity but also aligns with sustainable principles. To achieve such a schedule, the present work proposes to resort to the Simulation-based Optimization. This approach allows for accurate modeling of the stochastic behavior observed in manual task processing times. Specifically, an asymmetric right-skewed function is used to reproduce prolonged delays attributed to the fatigue and attention span of older workers. This skewness was identified in empirical data, where delays may stem from psychological and biological factors. Experiments were conducted in a learning factory, where both older and younger manual workers collaborated to fulfill customer orders. The results reveal the gap found when such stochastic human behavior is ignored. Thus, in manual operations, achieving a more efficient and human-centric scheduling approach necessitates the inclusion of worker-specific variability pattern
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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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