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Inovação e gerenciamento de programa sincronizado e colaborativo para novos programas
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Integration of mechanical, software and electronic systems technologies for vehicle systems
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A inovação de produtos através do gerenciamento eficaz de formulações, embalagens e processos de manufatura integrados
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O desenvolvimento de novos produtos aproveita dados para melhorar a qualidade e a lucratividade e reduz custos e tempo de introdução no mercado
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Supply chain collaboration in design, construction, maintenance and retirement of mission-critical assets
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Construction, mining, and agricultural heavy equipment manufacturers striving for superior performance
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Integration of manufacturing process planning with design and engineering for today’s machine complexity
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Visibility, compliance and accountability for insurance and financial industries
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Inovação na construção naval para reduzir de maneira sustentável o custo do desenvolvimento de frotas futuras
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Siemens PLM Software, a leader in media and telecommunications software, delivers digital solutions for cutting-edge technology supporting complex products in a rapidly changing market.
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“Inovação de produtos personalizados" através da digitalização para atender a demandas do mercado e reduzir custos
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Remove barriers and grow while maintaining your bottom line. We’re democratizing the most robust digital twins for your small and medium businesses.
Explore IndustryAssessing variability influence on electronics thermal reliability using thermal analysis
Assessing variability influence on electronics thermal reliability using thermal analysis
Combining design space exploration and electronics thermal analysis
The traditional use of electronics thermal analysis in its basic function has always been to assess whether a design will adequately ensure maximum temperatures are not exceeded. Improving a design to meet a performance goal using parametric studies and optimization techniques is widely recognized. Even assessing mission profiles using transient simulation is now more prevalent for power management studies or to generate temperature cycling insights.
How many thermal simulation-based design processes today are typically assessing the wide influence of variability from either manufacturing defects or to help quantify impacts of simulation input variations? This on-demand webinar explores the use of electronics thermal analysis combined with statistical design space exploration tools.
Typical electronics cooling simulation studies include multiple design inputs that may be subject to variability e.g data sheet interpretation, material property variation, incorporation of engineering judgment.
Understanding how the thermal performance changes as uncertainties are quantified through statistics will result in more reliable electronics systems
By combining electronics cooling thermal simulation with statistical approaches, engineers can more fully explore the design space. They can also apply analysis to evaluating potential impacts of certain manufacturing quality variation or defects. This on-demand presentation introduces an approach to simulation-based assessment of variations in manufacturing that can influence field reliability of an electronics product.
Studies performed shown in this presentation include Design of Experiments and Monte Carlo methods
A 3D thermal simulation model can provide more insight if it is exercised beyond the nominal input values. Surrogate modeling provides a method to guide an electronics thermal design within the time constraints of a typical design process.
An example is included in this recorded technical presentation looking at the impact of different sizes of TIM material defect, position and variations in thermal conductivity that then influence the operating junction temperature of a package.
Similar approaches to this example can be used to explore variation in thermal bondline performance by evaluating surface flatness, voiding, material performance and TIM degradation over lifetime due to cycling.
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Combining design space exploration and electronics thermal analysis
The traditional use of electronics thermal analysis in its basic function has always been to assess whether a design will adequately ensure maximum temperatures are not exceeded. Improving a design to meet a performance goal using parametric studies and optimization techniques is widely recognized. Even assessing mission profiles using transient simulation is now more prevalent for power management studies or to generate temperature cycling insights.
How many thermal simulation-based design processes today are typically assessing the wide influence of variability from either manufacturing defects or to help quantify impacts of simulation input variations? This on-demand webinar explores the use of electronics thermal analysis combined with statistical design space exploration tools.
Typical electronics cooling simulation studies include multiple design inputs that may be subject to variability e.g data sheet interpretation, material property variation, incorporation of engineering judgment.
Understanding how the thermal performance changes as uncertainties are quantified through statistics will result in more reliable electronics systems
By combining electronics cooling thermal simulation with statistical approaches, engineers can more fully explore the design space. They can also apply analysis to evaluating potential impacts of certain manufacturing quality variation or defects. This on-demand presentation introduces an approach to simulation-based assessment of variations in manufacturing that can influence field reliability of an electronics product.
Studies performed shown in this presentation include Design of Experiments and Monte Carlo methods
A 3D thermal simulation model can provide more insight if it is exercised beyond the nominal input values. Surrogate modeling provides a method to guide an electronics thermal design within the time constraints of a typical design process.
An example is included in this recorded technical presentation looking at the impact of different sizes of TIM material defect, position and variations in thermal conductivity that then influence the operating junction temperature of a package.
Similar approaches to this example can be used to explore variation in thermal bondline performance by evaluating surface flatness, voiding, material performance and TIM degradation over lifetime due to cycling.