Workload Analyzer

Usage of data deluge generated by machines to analyze workload of equipment/machine to avoid overloading of machines

Comment 3

Inspiration

Life of the machine will be affected if the machine is not regularly functioning on the optimal parameters for a very long period of time. So GE Brilliant APIs can be used to drill down the usage and work load of the machine.

What it does

How we built it

Having poor maintenance schedules – or no maintenance schedules at all – creates an opportunity for machine failure, which contributes to loss in production time. Sooner or later, poorly maintained machines will become slow, inefficient, and eventually break down. Delay in production time leads to negative consequences like loss in orders, timeconsuming maintenance and repair, firefighting (unscheduled overtime), and a premium paid for replacement parts. With effective usage of data deluge generated by the machines, workload of the equipment/machine can be analyzed to avoid the overloading of the machines leading to increase in the life of the machine. Timely notification and dynamic dashboard of the machine usage can reduce the occurrence of the failures

Challenges we ran into

Integration of Manufacturing API with polymer components

Accomplishments that we're proud of

Optimal usage of Efficiency Analyzer application’s API to provide drill down view for stakeholders

What we learned

How to provide deep insight of machine operations

What's next for Workload Analyzer

Predict machine failures owing overloading of machine and proactive recommendations for maintanance

Built With

Share this project:

Updates