Employ virtual prototypes and holistic modeling in heavy equipment engineering
Heavy equipment engineers need to continuously improve and optimize equipment designs, but how can they get product designs right sooner to meet both project and product targets? Predictive performance engineering has tremendous business potential and allows companies to unlock new levels of innovation and performance.
Companies can enable continuous improvement with a maturity model framework as well as increase performance engineering maturity by improving the following four processes:
- Create holistic equipment models
- Predict performance through simulation
- Improve predictions through testing
- Improve predictions with field data
Download the latest analyst report written by Tech-Clarity to discover how increasing performance engineering maturity through virtual prototypes and holistic modeling can improve efficiency and reduce costs.
Meet project objectives with Siemens comprehensive digital twins
Today’s more instrumented and connected products provide a new opportunity for equipment manufacturers to leverage vast amounts of real-world, operational data from the IoT, control systems, and other data sources to identify performance improvement opportunities. The first step to improve performance engineering is to ensure that digital product representations, or digital twins, adequately represent the final product. Heavy equipment companies can meet project objectives while reducing costs with Siemens comprehensive digital twins.
Benefits of continuous verification in heavy equipment engineering
To meet project objectives and optimize performance, heavy equipment engineering must be able to increase virtual verification and improvement through testing as well as field data predictions.
Explore the improvement opportunities in this analyst report to discover how you can increase performance engineering maturity, then adopt more advanced processes and technology to drive meaningful equipment and process improvement going forward.
Související zdroje informací
Infineon & Coseda: Facelifting a SystemC System Level Model Towards Physical Prototype – Adoption of High-Level-Synthesis
Infineon & Coseda present on the adoption of High-Level-Synthesis at an existing SystemC system level model.
Infineon: HLS Formal Verification Flow Using Siemens Formal Verification
High-Level Synthesis (HLS) is design flow in which design intent is described at a higher level of abstraction such as SystemC/C++/Matlab/etc.
STMicroelectronics: A Common C++ and UVM Verification Flow of High-Level IP
STMicro presents a unified way to integrate the definition of RTL and C functional coverage and assertion (reducing the coding effort) and a method to add constraints to the random values generated in UVMF.
High-Level Synthesis & Advanced RTL Power Optimization – Are you still missing out?
Discover how C++ & SystemC/MatchLib HLS is more than just converting SystemC to RTL. In the RTL Design space, we will cover our technology for Power Optimization with PowerPro Designer & Optimizer.
Alibaba: Innovating Agile Hardware Development with Catapult HLS
At the IP level, an ISP was created within a year using Catapult, a task impossible using traditional RTL. To reduce dependency on designer experience, Alibaba introduced an AI-assisted DSE tool.