ML Application to Manufacturing Feasibility Assessment

Data

* Project specific

* Ex: RSW 3T stack up testing

* "Reactive" data collection (ex: new material proposed)

* Data resides locally

Expert Engineer

Outcome

* Project specific conclusions

* Ex: Ok or Not Ok for RSW

* Expert engineer becomes more knowledgeable

Data

* Collection from multiple projects

* Enterprise-wide data sources

* "Proactive" data collection

* Centralized data

Computer

Outcome

* Project specific & generalized conclusions

* Reduce duplicate or near-duplicate testing

* Build empirical models to reduce future testing

* Identify gaps & do proactive testing

* Expert engineer & enterprise wide knowledge enhancement

Expert Engineer

Design Engineer

Outcome

* Upfront manufacturing feasibility assessment

* Reduced requests for testing

* Reduced rework

Machine Learning Approach

Traditional Approach