Join us for our 20 February 2024 Chapter meeting featuring:
Main Presentation: "Architecting a Purpose-Driven Roadmap for Impactful Digital Transformation", by Dr. Carla Sayan
Abstract:
The Aerospace and Defense Industry is currently undergoing a paradigm shift recognized as digital transformation or digital engineering. Despite its prevalence and being introduced with considerable interest, the precise objectives of this paradigm shift remain elusive from other branches of engineering, fostering diverse interpretations within the industry’s landscape. The paper begins by addressing the fundamental question: what exactly are digital transformation and digital engineering? We then explore whether this concept encompasses the widespread adoption of model-based systems engineering (MBSE), Model-Based Design (MBD) and others. Our inquiry extends to examining how these MB-X methodologies reshape traditional engineering practices, and whether digital engineering transcends beyond the realms of MBSE and MBD to include broader technological, procedural and organizational changes. We will explore whether digital is simply a progressive refinement of longstanding practices on what the hardware (electrical and mechanical) discipline has already proven for decades; that prioritizing modeling and simulation before producing HW can yield an improvement in the development life cycle. This paper aims to define a purpose for digital engineering and outline a roadmap forward for the evolution of digital engineering as a core practice.
Bio:
Carla Sayan Ph.D. is an Associate Director for Systems Engineering at a Government Contractor. She is an inventor, author and has 18+ years of extensive knowledge and industry experience in various domain areas: Sensors and Effectors, Multi-Function RF Systems, Counter Unmanned Aircraft Systems, Systems of Systems Architectures and Embedded Systems Integrity. She is responsible for Company Wide Transformations implementing Digital, Model Based X initiatives and Agile across Franchise Level Programs. Carla holds a Ph.D. in Electrical and Computer Engineering from the University of Arizona and is a member of INCOSE, IEEE and SHPE.
Upcoming INCOSE Events
Symposium on Artificial Intelligence – Machine Learning in Safety Critical Systems
INCOSE India, in collaboration with IEEE Systems Council Bangalore Chapter and Aeronautical Society of India, is organizing this virtual symposium to bring together experts from multiple sectors such as aerospace and automotive, to share their research findings and experiences on various challenges pertaining to adoption of AI-ML in safety critical systems.
Artificial Intelligence for Systems Engineering - AI4SE 2021
Machine Learning in Safety Critical Systems
Location: Virtual
Dates: 21-22 October 2020
Time: 16:00 - 20:00 Indian Standard Time (UTC +5:30)
Registration: https://www.aesievents.com/registration
INCOSE India, in collaboration with IEEE Systems Council Bangalore Chapter and Aeronautical Society of India, is organizing this virtual symposium to bring together experts from multiple sectors such as aerospace and automotive, to share their research findings and experiences on various challenges pertaining to adoption of AI-ML in safety critical systems.
There is an increasing demand for safety critical engineered systems to inculcate humanlike-intelligence and autonomy through adoption of Artificial Intelligence (AI) models, including data-driven decision making capabilities based on machine-learning (ML) algorithms and techniques. This demand is exponentially increasing the complexity in the design, verification, and validation of such safety critical intelligent systems that are subjected to regulations and certifications.
Engineering such systems requires an assurance on the behavior and performance of the system, and may require new approaches in arriving at the system design, in ensuring that the system is ready for operations, and in engineering safe and effective human interaction with intelligent systems. Challenges include new failure modes (e.g. negative side effects, unsafe exploration), unpredictability (e.g. performance on unseen data), trust and robustness (e.g. explainable decisions and behavior).
This symposium aims to bring together experts from multiple sectors such as aerospace, automotive, industrial automation and healthcare to share their research findings and experiences on various challenges pertaining to adoption of AI-ML in safety critical systems, including implications on regulations and certification.
See the Flyer for more details