Artificial Intelligence Applied to Smart Model Based Systems Engineering

This presentation was made at the NAFEMS Americas Seminar "Model-Based Engineering: What is it & How Will It Impact Engineering Simulation" held on the 1st of October 2019 in Columbus Ohio

Resource Abstract

Smart Model Based Systems (SMBSE) engineering is an evolution from Model Based Systems Engineering (MBSE), by incorporating digital capabilities to expedite a quality execution and minimize unintended effects. SMBSE integrates Systems Engineering (SE) functionality with a suite of smart tools, by modelling complex systems, requirements, constraints, targets, validation and verification plans, to develop the simplest solution.



The SMBSE distinctive features from the conventional MBSE include reusability, automation, dynamic simulation and optimization. SMBSE incorporates Artificial Intelligence (AI), as an enabler of the optimization element with machine learning algorithms, to facilitate the overall design effort and develop an optimal design solution.



The AI application in SMBSE framework drives the opportunity for optimizing design processes, with learning capabilities for different system scenarios and objectives.



AI tools will enable engineers to focus on the Systems Engineering roles that add more value to prevent unexpected results and ensure user needs compliance, as well as providing more time to optimize solutions from the early stages of designing complex systems engineering.



The increasing complexity of disruptive technologies requires the application of smart systems engineering tools to develop digital methodologies, enhanced by AI, oriented to automate as possible, the complex design processes. This effort requires the application of automation and AI capabilities, but also systems integration tools to facilitate the interface between different software platforms and hardware, to expedite the design iterations to generate the optimal solution.



The proposed SMBSE framework provides the opportunity to release time, for product designer teams, by automating complex design process of conventional technologies and focus on disruptive technologies generation.



There is a never-ending race to innovate based on new technologies that require design cyber tools in accordance with the increasing complexity of today’s products and services. The conjunction of AI and systems engineering provides the design path to face this permanent challenge.