NAFEMS Americas and Digital Engineering (DE) teamed up (once again) to present CAASE, the (now Virtual) Conference on Advancing Analysis & Simulation in Engineering, on June 16-18, 2020!

CAASE20 brought together the leading visionaries, developers, and practitioners of CAE-related technologies in an open forum, unlike any other, to share experiences, discuss relevant trends, discover common themes, and explore future issues, including:
-What is the future for engineering analysis and simulation?
-Where will it lead us in the next decade?
-How can designers and engineers realize its full potential?
What are the business, technological, and human enablers that will take past successful developments to new levels in the next ten years?

Resource Abstract

With the increasing complexity of systems, traditional engineering approaches have shown limitations. Until recently, engineers had a lot of knowledge and through their experience and working together there was a lot of interactions and communication and therefore, it resulted in many high-quality products because people knew their boundaries exactly and who to talk to. Today it is more discipline-centric where you know roughly from a previous project the new solution to be developed. The system definition is often limited to defining the system requirements from the marketing or product manager needs and then on to develop the components of the solution. The performances is typically accessed after the design has been done. Product design is becoming increasingly complex these days, we are now in a cyber-physical systems world with software intensive systems, distributed systems, cloud services environment, etc. The intelligence is now not only in the system but also in the surrounding environment with interactions between multiple systems.

Model Based Systems Engineering (MBSE) is the state of the art approach to address this complexity and develop high quality products. It addresses the analysis of the problem, prior to the development of the solution, through behavior and structure analysis. One aim of the approach is to define achievable targets that drive the design instead of designing and then assessing performances.

Using an electric vehicle powertrain example, we will illustrate how to achieve performance design in the context of a system architecture utilizing a systems engineering methodology called Cyber MagicGrid©. Through this framework we will cover all phases from analyzing the problem, definition of a solution by utilizing trade studies, implementation and assessment of component performance, verification of system performance and validation of the system against stakeholder requirements. This will help to understand how this framework helps to manage the complexity of a development program and thus reduces the risk cost overruns due to late phase re-designs or product recalls due to bad quality products.