4,897 research outputs found

    Industry 4.0 Solutions as Enablers for the Sustainability of the Italian Ceramic Tiles Sector

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    The Italian ceramic tiles district has a long tradition but is called to face new sustainability challenges related to the profitability, the environmental impact, and the capability to offer pleasant and motivating working conditions for new young employees. New Industry 4.0 approaches are emerging to evolve the current industrial organization and are expected to enhance the overall economic, environmental, and social viability. In this context, this paper aims at demonstrating the positive correlation between the new technologies and the sustainability of the sector. It outlines the main achievements of a 4-year project financed by the Italian government, involving the entire chain made up of research centers, technology providers, and tiles producers. The presented approach is concretized in several technological innovations based on the Industry 4.0 paradigm. Furthermore, a pilot line was created to test the new systems and collect data on the process. The main results are reported in terms of improved sustainability KPIs, such as extended possibility of control of production plants, waste reduction, lower consumption of raw materials and chemical additives. Finally, a sensible increase in the operators' digitalization level is registered, making a shift from a physical and hard working environment towards more conceptual and attractive job conditions

    Operator interfaces for the lifecycle support of component based automation systems

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    Current manufacturing automation systems (specifically the powertrain sector) have been facing challenges with constant pressures of globalisation, environmental concerns and ICT (Information and Communication Technology) innovations. These challenges instigate new demands for shorter product lifecycles and require customised products to be manufactured as efficiently as possible. Manufacturing systems must therefore be agile to remain competitive by supporting frequent reconfigurations involving distributed engineering activities. [Continues.

    Virtual reality for the built environment: A critical review of recent advances

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    This paper reviews the current state of the art for Virtual Reality (VR) and Virtual Environment (VE) applications in the field of the built environment. The review begins with a brief overview of technological components involved in enabling VR technology. A classification framework is developed to classify 150 journal papers in order to reveal the scholarly coverage of VR and VE from 2005 to 2011, inclusive. The classification framework summarizes achievements, established knowledge, research issues and challenges in the area. The framework is based on four layers of VR: concept and theory, implementation, evaluation and industrial adoption. These layers encompass architecture and design, urban planning and landscape, engineering, construction, facility management, lifecycle integration, training and education. This paper also discusses various representative VR research work in line with the classification framework. Finally the paper predicts future research trends in this area

    Smart Factory Using Virtual Reality and Online Multi-User: Towards a Metaverse for Experimental Frameworks

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    Virtual reality (VR) has been brought closer to the general public over the past decade as it has become increasingly available for desktop and mobile platforms. As a result, consumer-grade VR may redefine how people learn by creating an engaging “hands-on” training experience. Today, VR applications leverage rich interactivity in a virtual environment without real-world consequences to optimize training programs in companies and educational institutions. Therefore, the main objective of this article was to improve the collaboration and communication practices in 3D virtual worlds with VR and metaverse focused on the educational and productive sector in smart factory. A key premise of our work is that the characteristics of the real environment can be replicated in a virtual world through digital twins, wherein new, configurable, innovative, and valuable ways of working and learning collaboratively can be created using avatar models. To do so, we present a proposal for the development of an experimental framework that constitutes a crucial first step in the process of formalizing collaboration in virtual environments through VR-powered metaverses. The VR system includes functional components, object-oriented configurations, advanced core, interfaces, and an online multi-user system. We present the study of the first application case of the framework with VR in a metaverse, focused on the smart factory, that shows the most relevant technologies of Industry 4.0. Functionality tests were carried out and evaluated with users through usability metrics that showed the satisfactory results of its potential educational and commercial use. Finally, the experimental results show that a commercial software framework for VR games can accelerate the development of experiments in the metaverse to connect users from different parts of the world in real time.Universidad Cooperativa de Colombia-Cali, Colombia INV278

    Plant-Wide Diagnosis: Cause-and-Effect Analysis Using Process Connectivity and Directionality Information

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    Production plants used in modern process industry must produce products that meet stringent environmental, quality and profitability constraints. In such integrated plants, non-linearity and strong process dynamic interactions among process units complicate root-cause diagnosis of plant-wide disturbances because disturbances may propagate to units at some distance away from the primary source of the upset. Similarly, implemented advanced process control strategies, backup and recovery systems, use of recycle streams and heat integration may hamper detection and diagnostic efforts. It is important to track down the root-cause of a plant-wide disturbance because once corrective action is taken at the source, secondary propagated effects can be quickly eliminated with minimum effort and reduced down time with the resultant positive impact on process efficiency, productivity and profitability. In order to diagnose the root-cause of disturbances that manifest plant-wide, it is crucial to incorporate and utilize knowledge about the overall process topology or interrelated physical structure of the plant, such as is contained in Piping and Instrumentation Diagrams (P&IDs). Traditionally, process control engineers have intuitively referred to the physical structure of the plant by visual inspection and manual tracing of fault propagation paths within the process structures, such as the process drawings on printed P&IDs, in order to make logical conclusions based on the results from data-driven analysis. This manual approach, however, is prone to various sources of errors and can quickly become complicated in real processes. The aim of this thesis, therefore, is to establish innovative techniques for the electronic capture and manipulation of process schematic information from large plants such as refineries in order to provide an automated means of diagnosing plant-wide performance problems. This report also describes the design and implementation of a computer application program that integrates: (i) process connectivity and directionality information from intelligent P&IDs (ii) results from data-driven cause-and-effect analysis of process measurements and (iii) process know-how to aid process control engineers and plant operators gain process insight. This work explored process intelligent P&IDs, created with AVEVAÂź P&ID, a Computer Aided Design (CAD) tool, and exported as an ISO 15926 compliant platform and vendor independent text-based XML description of the plant. The XML output was processed by a software tool developed in MicrosoftÂź .NET environment in this research project to computationally generate connectivity matrix that shows plant items and their connections. The connectivity matrix produced can be exported to ExcelÂź spreadsheet application as a basis for other application and has served as precursor to other research work. The final version of the developed software tool links statistical results of cause-and-effect analysis of process data with the connectivity matrix to simplify and gain insights into the cause and effect analysis using the connectivity information. Process knowhow and understanding is incorporated to generate logical conclusions. The thesis presents a case study in an atmospheric crude heating unit as an illustrative example to drive home key concepts and also describes an industrial case study involving refinery operations. In the industrial case study, in addition to confirming the root-cause candidate, the developed software tool was set the task to determine the physical sequence of fault propagation path within the plant. This was then compared with the hypothesis about disturbance propagation sequence generated by pure data-driven method. The results show a high degree of overlap which helps to validate statistical data-driven technique and easily identify any spurious results from the data-driven multivariable analysis. This significantly increase control engineers confidence in data-driven method being used for root-cause diagnosis. The thesis concludes with a discussion of the approach and presents ideas for further development of the methods

    A flexible sensor technology for the distributed measurement of interaction pressure

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    We present a sensor technology for the measure of the physical human-robot interaction pressure developed in the last years at Scuola Superiore Sant'Anna. The system is composed of flexible matrices of opto-electronic sensors covered by a soft silicone cover. This sensory system is completely modular and scalable, allowing one to cover areas of any sizes and shapes, and to measure different pressure ranges. In this work we present the main application areas for this technology. A first generation of the system was used to monitor human-robot interaction in upper- (NEUROExos; Scuola Superiore Sant'Anna) and lower-limb (LOPES; University of Twente) exoskeletons for rehabilitation. A second generation, with increased resolution and wireless connection, was used to develop a pressure-sensitive foot insole and an improved human-robot interaction measurement systems. The experimental characterization of the latter system along with its validation on three healthy subjects is presented here for the first time. A perspective on future uses and development of the technology is finally drafted

    A component-based approach to human–machine interface systems that support agile manufacturing

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    The development of next generation manufacturing systems is currently an active area of research worldwide. Globalisation is placing new demands on the manufacturing industry with products having shorter lifecycles and being required in more variants. Manufacturing systems must therefore be agile to support frequent manufacturing system reconfiguration involving globally distributed engineering partners. The research described in this thesis addresses one aspect within this research area, the Human Machine Interface (HMI) system that support the personnel involved in the monitoring, diagnostics and reconfiguration of automated manufacturing production machinery. Current HMI systems are monolithic in their design, generally offer poor connectivity to other manufacturing systems and require highly skilled personnel to develop and maintain them. The new approach established in the research and presented in this thesis provides a specification capture technique (using a novel storyboarding modelling notation) that enables the end users HMI functionality to be specified and rapidly developed into fully functional End User HMI's via automated generation tools. A novel feature in this HMI system architecture that all machine information is stored in a common unified machine data model which ensures consistent accurate machine data is available to all machine lifecycle engineering tools including the HMI. The system's run-time architecture enables remote monitoring and diagnostics capabilities to be available to geographically distributed engineering partners using standard internet technologies. The implementation of this novel HMI approach has been prototyped and evaluated using the industrial collaborators full scale demonstrator machines within cylinder head machining and engine assembly applications
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