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DESCRIPTION:Improved design, controls and operation with multiphysics simulation\n \nManufacturing is evolving toward a flexible production with autonomous operations to respond to new customer requests, reduce manual labor, and streamline processes.\n \nThe growing engineering complexity is forcing machine builders to adopt new design practices to ensure machines are safe, perform as expected, and cost-effectively designed and built.\n \nThis webinar highlights how system simulation models support engineers during the development and lifecycle of production machines.\n \nMultiphysics system simulations in the early design phase\n \nSystem simulation models can efficiently drive the design of production machines by virtually benchmarking new technologies in terms of performance, reliability, carbon footprint, energy efficiency, costs, and more.\n \nThis webinar showcases real-world examples of how multiphysics system simulations in the early design phase investigated the best sizing of a delta picker and analyzed energy savings in a hydraulic press by comparing different configurations.\n \nRegister for this webinar and see firsthand how system simulation can accelerate the design process and save costs at the same time.\n \nIntegrating and validating smart controls sooner with system simulations\n \nOnce a precise virtual representation of a physical system is available, automation engineers can integrate and validate smart control strategies before a prototype is available.\n \nVirtual commissioning reduces the time and costs associated with getting new machines up and running.\n \nRegister for this webinar and see how an organization used multiphysics simulation to perform virtual commissioning on a thermal subsystem within a unit-dose packaging machine and a tire manufacturer optimized the PID controller of the control valve regulating the internal heating process in a curing press.\n \nUsing system simulations to optimize manufacturing and plan maintenance\n \nSystem models connected to real-time machine data can measure parameters that are unmeasurable or too expensive to be measured by real sensors.\n \nInsights from these digital models can optimize manufacturing operations and improve maintenance planning.\n \nRegister to watch the webinar and see real-world examples of operators using multiphysics simulation models connected to real-time data to estimate the value of variables using virtual sensors and optimizing in-service performance to implement model-based predictive maintenance.\n \nMeet the machinery system simulation speakers:\n \nAldo Alessandro Negri:System Engineer, Technical Sales Support, Siemens Digital Industries Software\n \nAldo has spent his career focused on engineering modelling, simulation, and advanced control. He earned a Bachelors in Management Engineering and a Masters in Automation and Control Engineering from the Politecnico di Milano in Italy. He began working at Siemens in 2018, and his current role involves modeling, simulation, control, and condition monitoring in industrial machinery.\n \nFrancesca Furno:Business Development Simcenter, Siemens Digital Industries Software\n \nFrancesca is a mechanical engineer with a focus on hydraulics components and systems simulation. She earned her Masters in Mechanical Engineering and her PhD in Engergetic Systems from the Politecnico di Torino in Italy. She joined Siemens in 2016 where she helps customers in the automotive, heavy equipment, industrial machinery, and aerospace industries with simulation solutions.\n
DTSTART:20220310T110000
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SUMMARY;LANGUAGE=es-es:Tecnowebinars.com - :: Machinery system simulation for faster commissioning and monitoring
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