An Industrial AI Platform to Solve Problems
The DecisionIQ platform was built by our industry savvy team of mechanical, electrical and industrial engineers with a world class team of data scientists. They built a platform for engineers to solve problems that limit industrial performance. The team transformed the proven engineering methods that are foundational to today’s industrial operations into state-of-the-art engineering analytics to be used in a next-generation machine learning AI platform. This approach produces results that are distinctively superior in accuracy of prediction, quality of diagnostics and quick adoption by technical operating teams. And we keep it simple for the engineers -- we hide the data science and just show the underlying offending variables, features and recommends type of response required.
Our Engineers Understand Your Problems and Your Data
Any Process in Your Operation
Any problem in any operational process can be tracked if it shows in your underlying data. We are expert in production and maintenance process.
Any Data, Any Sensor
We can join multiple wired sensor types, wireless IoT sensors, any condition data, PLC data and process data from any API and historian type.
We have your diagnostics reports and deployments ready within 30 days of receipt of data.
Low Data Sample Rates
Our engineering analytics enables us to build data models with low data sample rates, ideal for a light footprint on IT infrastructure. No edge computing required.
Automation at Scale
Our engineering analytics enable your technical workforce to solve more problems across each site. They also automatically benefit from learning at other sites.
More Than Failure Predictions
There are many types of failures and other anomalies. We find them all, including operational startup and shut down, data corruption, data streaming corruption.
Diagnostics and Continuous Monitoring
For each alert, engineering diagnostics are provided that are useful for root cause analysis. This helps engineers determine the type of failure underway and how to prepare. In this case, time-series supported vibration data from a 3rd party wireless sensor by a waterfall presentation of waveform frequencies with failure modes.
How We Enable Root Cause Analysis
Our platform consolidates much of the data required for Root Cause Analysis (RCA) and Six Sigma Continuous Improvement Process (CIP). We assist with process measurement and cause of failures. We typically connect to multiple data sets from production process to condition monitoring from maintenance. We include work orders and spare parts when relevant. Predicted failures show all the offending variables from these data sets. We show feature extracted data as shown in the diagnostics panel above. All this works to give engineering much, if not all, the data they need to perform a structured CIP or RCA by an experienced engineer. But we automate much of the process so an engineer can make a final determination.