Our digital engineering software solutions are being driven by a range of key technologies, including Hyperautomation, AI Engineering, Decision Intelligence and Cloud-native paradigm. In this spotlight, we discuss how ESTECO VOLTA and modeFRONTIER have evolved to stay on the edge of these technology trends and support organizations to embrace the necessary digitalization shift in product development. It is an inspiring conversation with Dario Campagna (Research Project Manager), Danilo Di Stefano (modeFRONTIER Product Manager) and Marco Turchetto (VOLTA Product Manager) covering our main development drivers to address companies’ expectations in the digital engineering age.
1. Explore our hyperautomation approach: from engineering to business process workflow
Hyperautomation is a business-driven approach that organizations use to identify and automate industry-specific processes. When it comes to the simulation and analysis domain, the foundation of our technology has always been integration and process workflow automation. On this basis, you can expect to learn more how modeFRONTIER’s new guided process simplifies all the steps involved in introspecting CAD/CAE model with the aim of moving directly to the Planner environment to define design exploration and optimization studies.
Our Process Automation technology has evolved with the introduction of Business Process Management (BPM) capabilities. As a result, it is no longer restricted to the engineering process workflow. The CAE automation can now be combined with the management of human tasks within a business process workflow.
With time, we extended our simulation process automation with the introduction of Business Process Management technology into the VOLTA SPDM platform. Marco Turchetto explains how this can be beneficial for organizations seeking to map, standardize and execute engineering design processes.
2. Extend the usage of Artificial Intelligence (AI) and Machine Learning (ML) methods in engineering simulation
To achieve a higher level of maturity in the digital engineering initiatives, organizations should also focus on making extensive use of AI and ML techniques to reduce the simulation turnaround time, minimize prototypes and speed up the whole design process. Danilo Di Stefano points out how users can now leverage their Python programming skills and ML libraries to either post-process optimization results, train Response Surface Models (RSMs) or even import their own algorithm into modeFRONTIER.
Making extensive use of AI methods also means expanding its usage to a wider audience of CAE engineers. This happens through a state-of-the-art autonomous approach to configure design exploration and optimization algorithms.
However, identifying the right strategy for your design problem can take a certain level of knowledge and expertise. In the spotlight, you can get to know how modeFRONTIER’s autonomous algorithm mode opens the door to anyone who wants to investigate the design space and is not necessarily an optimization expert. Also, this reflects in our CAE democratization approach within the VOLTA SPDM platform. Different subject matter experts can collaborate in real-time on the same design challenge and configure design space exploration strategies in one-click.
3. Adopt a Decision Intelligence approach for informed data-driven design insights
The execution of design space exploration strategies usually generate a lot of numbers which are meaningless unless you give them a proper interpretation. Is the complexity only limited to the amount of data? Or is it also related to the number of variables that you are tasked to manage in the engineering process workflow? You can find out how modeFRONTIER answers these needs with a multitude of design charts and post-processing tools for advanced data analysis.
An effective Decision Intelligence approach should also take into account scenarios where a wider audience of engineers may need to access product performance metrics and get complete visibility into the simulation design process.
What if many stakeholders need to access simulation results to make informed decisions? Marco Turchetto gives a comprehensive overview of how different subject matter experts can benefit from VOLTA’s web-based dashboards for 3D model visualization and post-processing to collaboratively compare and validate design solutions in real time.
4. Make efficient use of computing resources for simulation-driven product development
To achieve good optimization results, you must perform many simulations which are computationally expensive due to the nature of the solvers involved. Danilo Di Stefano clarifies how modeFRONTIER job scheduling technology enables users to face these challenges by efficiently distributing computational workloads across HPC and cloud environments.
A reliable web-based system for running distributed computations is necessary to scale up the execution of Multidisciplinary Design Optimization (MDO) studies effectively.
Things are getting even more complicated when you need to orchestrate and execute Multidisciplinary Design Optimization (MDO) processes. You can get an insight into how VOLTA’s web-based job scheduling technology supports IT departments to set-up the MDO execution while end-users just have to submit the evaluations and wait for the results.
5. Get a preview of what comes next in VOLTA and modeFRONTIER