688 research outputs found

    LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing

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    LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft

    Industry 4.0: current trend and future scope for further research in High Performance Manufacturing

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    The fourth industrial revolution requires that personalization processes of mass productions evolve towards flexible, interconnected, cloud production with greater automation in its machines and operations, called Industry 4.0 (I4.0). However, a homogeneous I4.0 concept, infrastructure state, and other issues are still scarce, making difficult to determinate in the specialized literature, the threshold between recent manufacturing and challenges that companies had to reach competitive advantage through I4.0 inclusion. Despite becoming one of the most popular strategies for continuous improvement, many plants are struggling to turn I4.0 into a success. Therefore, this paper analyzes the current trends of Industry 4.0 in High Performance Manufacturing (HPM), aiming to consolidate the existing knowledge on both subjects, providing a starting point for academics and practitioners seeking to implement I4.0 in plants and offering suggestions for future examination. This systematic literature review aims to synthesize, organize, and structure the stock of knowledge relating to I4.0 and HPM. The results show that HPM papers do not evidence a holistic evaluation of I.40 principles and foundations. There exists in HPM literature manufacturing practices that permit evaluate technology inclusion and their performance but not their autonomy, cloud computing and network between machines, supplier, and processes. The HPM papers trends are related with issues such as adaptability, flexibility, reconfigurability, new information technologies, modularity, automation, etc. Regarding study limitations, it is necessary to study current I4.0 adoption level, technological infrastructure, and cultural factors. The practical implications are focused in the identification of manufacturing practices used in specialized literature to measure how technology inclusion increase companies’ performance, proving the technological infrastructure and I4.0 maturity level. The originality of this paper converges on the presentation of some manufacturing practices applied on HPM studies which are associated with I4.0

    An engineering framework for Service-Oriented Intelligent Manufacturing Systems

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    Nowadays fully integrated enterprises are being replaced by business networks in which each participant provides others with specialized services. As a result, the Service Oriented Manufacturing Systems emerges. These systems are complex and hard to engineer. The main source of complexity is the number of different technologies, standards, functions, protocols, and execution environments that must be integrated in order to realize them. This paper proposes a framework and associated engineering approach for assisting the system developers of Service Oriented Manufacturing Systems. The approach combines multi-agent system with Service Oriented Architectures for the development of intelligentautomation control and execution of manufacturing systems.Giret Boggino, AS.; Garcia Marques, ME.; Botti Navarro, VJ. (2016). An engineering framework for Service-Oriented Intelligent Manufacturing Systems. Computers in Industry. 81:116-127. doi:10.1016/j.compind.2016.02.002S1161278

    Addressing Tasks Through Robot Adaptation

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    Developing flexible, broadly capable systems is essential for robots to move out of factories and into our daily lives, functioning as responsive agents that can handle whatever the world throws at them. This dissertation focuses on two kinds of robot adaptation. Modular self-reconfigurable robots (MSRR) adapt to the requirements of their task and environments by transforming themselves. By rearranging the connective structure of their component robot modules, these systems can assume different morphologies: for example, a cluster of modules might configure themselves into a car to maneuver on flat ground, a snake to climb stairs, or an arm to pick and place objects. Conversely, environment augmentation is a strategy in which the robot transforms its environment to meet its own needs, adding physical structures that allow it to overcome obstacles. In both areas, the presented work includes elements of hardware design, algorithms, and integrated systems, with the common goal of establishing these methods of adaptation as viable strategies to address tasks. The research takes a systems-level view of robotics, placing particular emphasis on experimental validation in hardware

    A Novel Method for Adaptive Control of Manufacturing Equipment in Cloud Environments

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    The ability to adaptively control manufacturing equipment, both in local and distributed environments, is becoming increasingly more important for many manufacturing companies. One important reason for this is that manufacturing companies are facing increasing levels of changes, variations and uncertainty, caused by both internal and external factors, which can negatively impact their performance. Frequently changing consumer requirements and market demands usually lead to variations in manufacturing quantities, product design and shorter product life-cycles. Variations in manufacturing capability and functionality, such as equipment breakdowns, missing/worn/broken tools and delays, also contribute to a high level of uncertainty. The result is unpredictable manufacturing system performance, with an increased number of unforeseen events occurring in these systems. Events which are difficult for traditional planning and control systems to satisfactorily manage. For manufacturing scenarios such as these, the use of real-time manufacturing information and intelligence is necessary to enable manufacturing activities to be performed according to actual manufacturing conditions and requirements, and not according to a pre-determined process plan. Therefore, there is a need for an event-driven control approach to facilitate adaptive decision-making and dynamic control capabilities. Another reason driving the move for adaptive control of manufacturing equipment is the trend of increasing globalization, which forces manufacturing industry to focus on more cost-effective manufacturing systems and collaboration within global supply chains and manufacturing networks. Cloud Manufacturing is evolving as a new manufacturing paradigm to match this trend, enabling the mutually advantageous sharing of resources, knowledge and information between distributed companies and manufacturing units. One of the crucial objectives for Cloud Manufacturing is the coordinated planning, control and execution of discrete manufacturing operations in collaborative and networked environments. Therefore, there is also a need that such an event-driven control approach supports the control of distributed manufacturing equipment. The aim of this research study is to define and verify a novel and comprehensive method for adaptive control of manufacturing equipment in cloud environments. The presented research follows the Design Science Research methodology. From a review of research literature, problems regarding adaptive manufacturing equipment control have been identified. A control approach, building on a structure of event-driven Manufacturing Feature Function Blocks, supported by an Information Framework, has been formulated. The Function Block structure is constructed to generate real-time control instructions, triggered by events from the manufacturing environment. The Information Framework uses the concept of Ontologies and The Semantic Web to enable description and matching of manufacturing resource capabilities and manufacturing task requests in distributed environments, e.g. within Cloud Manufacturing. The suggested control approach has been designed and instantiated, implemented as prototype systems for both local and distributed manufacturing scenarios, in both real and virtual applications. In these systems, event-driven Assembly Feature Function Blocks for adaptive control of robotic assembly tasks have been used to demonstrate the applicability of the control approach. The utility and performance of these prototype systems have been tested, verified and evaluated for different assembly scenarios. The proposed control approach has many promising characteristics for use within both local and distributed environments, such as cloud environments. The biggest advantage compared to traditional control is that the required control is created at run-time according to actual manufacturing conditions. The biggest obstacle for being applicable to its full extent is manufacturing equipment controlled by proprietary control systems, with native control languages. To take the full advantage of the IEC Function Block control approach, controllers which can interface, interpret and execute these Function Blocks directly, are necessary

    IRS-assisted UAV Communications: A Comprehensive Review

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    Intelligent reflecting surface (IRS) can smartly adjust the wavefronts in terms of phase, frequency, amplitude and polarization via passive reflections and without any need of radio frequency (RF) chains. It is envisaged as an emerging technology which can change wireless communication to improve both energy and spectrum efficiencies with low energy consumption and low cost. It can intelligently configure the wireless channels through a massive number of cost effective passive reflecting elements to improve the system performance. Similarly, unmanned aerial vehicle (UAV) communication has gained a viable attention due to flexible deployment, high mobility and ease of integration with several technologies. However, UAV communication is prone to security issues and obstructions in real-time applications. Recently, it is foreseen that UAV and IRS both can integrate together to attain unparalleled capabilities in difficult scenarios. Both technologies can ensure improved performance through proactively altering the wireless propagation using smart signal reflections and maneuver control in three dimensional (3D) space. IRS can be integrated in both aerial and terrene environments to reap the benefits of smart reflections. This study briefly discusses UAV communication, IRS and focuses on IRS-assisted UAC communications. It surveys the existing literature on this emerging research topic and highlights several promising technologies which can be implemented in IRS-assisted UAV communication. This study also presents several application scenarios and open research challenges. This study goes one step further to elaborate research opportunities to design and optimize wireless systems with low energy footprint and at low cost. Finally, we shed some light on future research aspects for IRS-assisted UAV communication
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