数字孪生业务价值
过去,工程仿真软件一直用于新产品设计,但随着先进的嵌入式传感器的出现,工程师现在可以使用这些数据来创建数字孪生。数字孪生可用于实时系统分析,以支持预定的预测性维护并实施性能优化。借助Ansys的混合分析功能,通过将基于机器学习(ML)的分析与基于物理的方法相结合,工程师可以使用预测分析来达到无与伦比的准确性。
过去,工程仿真软件一直用于新产品设计,但随着先进的嵌入式传感器的出现,工程师现在可以使用这些数据来创建数字孪生。数字孪生可用于实时系统分析,以支持预定的预测性维护并实施性能优化。借助Ansys的混合分析功能,通过将基于机器学习(ML)的分析与基于物理的方法相结合,工程师可以使用预测分析来达到无与伦比的准确性。
使用Ansys Twin Builder构建、验证和部署混合数字孪生
Ansys数字孪生
Ansys Twin Builder允许您部署真实系统的完整虚拟原型。这些原型经过部署,可用来管理产品和资产的整个生命周期。这种数字孪生仿真模式使您能够逐步地大幅提高效率,并根据预测方法安排维护,而这些方法通过实际测试和响应会变得更加准确。通过访问这些信息,工程师可以从现有资产中解锁更多价值,从而防止计划外停机并降低运营成本,同时以最佳效率开展工作,所有这些都能通过与物联网(IoT)平台无关的技术实现。
July 2023
We launched Ansys 2023 R2, which extends its digital twin offering with enhanced fusion capabilities for transient data and improved post-processing for Hybrid Analytics. This release improves ROM performance, visualization, and post-treatments. Ansys 2023 R2 enables the co-simulation of Twin Builder and Maxwell for parallel runs, plus an improved licensing scheme supporting HPC.
This webinar explores advantages offered by Ansys Twin Builder in establishing virtual validation workflow for electric vehicles.
Create, validate and deploy better workflows with Ansys Twin Developer in this webinar.
Hear from Tata Steel Nederland experts, who will uncover how they are digitalizing the thermal process management for their iron & steelmaking plants. Using simulation-based digital twins and AI/ML techniques, they can now pursue their initiatives in energy consumption optimization.
Get introduced to the latest PyAnsys package, “PyTwin,” giving easy access to the power of Ansys Digital Twins Runtimes through Python APIs.
Build, Validate and Deploy Simulation-Based Digital Twins
During these 60-minute sessions, our experts will demonstrate the power of Ansys Twin Builder to Build, Validate and Deploy Simulation-Based Digital Twins in various Industries and Applications.
Learn about the ANSYS Twin Builder Fluid Power Library for industrial applications from drills and gearboxes to automotive suspension systems and aircraft landing gear.
Digital twins — virtual representations of a physical product — can unlock value across the entire product lifecycle from design through operation and service.
Today, physics simulation-based digital twins are already representing the real world with a high degree of accuracy. In this webinar, our panel of experts will discuss how to bring together the best of AI and physics to create hybrid digital twins.