Each GE business unit created their own bespoke tools to track the performance of their assets.
A new Industrial IIoT application was created to securely connect high-value industrial assets to the internet which could be shared across business.
When GE Digital formed a “dream team” of designers to build out this flagship Predix Platform Application I was selected from dozens of designers to discover the pain points of our largest customers and design a scaleable solution.
Research and Insights
GE Power customers rely on vibration and combustion engineers to monitor their critical assets to avoid costly downtime.
When researching the Power Generation monitoring center I noticed that as a result of various acquisitions and siloed development efforts engineers used 15 different data visualization tools to understand the output of various machine learning and physics-based monitoring systems.
I went about documenting these systems, and generated a prioritized list of features and workflows designed to provide access to the data though a single tool.
The resulting industry-leading end to end solution enables new diagnostic engineers to quickly learn how to diagnose the most critical equipment first, skip the false positives, and forward the more complex issues to the appropriate subject matter expert.
By increasing reliability each power plant is saving $3M/year by reducing downtime and are 2-3% more fuel efficient.
The physics-based algorithms used by the team generates excellent results: