MxD Cognitive On-Demand Design Advisor

Current design platforms fail to provide real-time feedback from downstream efforts in time to mitigate the cost and schedule impact of design flaws. Facilitating this feedback is elusive without formal representation of multiple manufacturing, supplier and life-cycle attributes. The Raytheon and ITI team proposed this project to implement an Artificial Intelligence (AI)/Machine Learning(ML) based design advisor to provide design engineers viable options to mitigate design and cost risk, decrease Engineering Change Orders (ECOs), and extend product life by addressing obsolescence in electronics. The teams Cognitive On-Demand Design Advisor (CODA) is accessible to diverse users and generates data-driven, system agnostic, and forward-looking design recommendations within the users design environment. CODA is demonstrated via a Circuit Card Assembly (CCA) use-case however the framework approach allows for additional advisement models to be incorporated.