When reliability engineers dream, it’s of uneventful workdays. Equipment humming, green lights across the board, nice and quiet.
The flip side is the nightmare of unplanned downtime and lost productivity. But an emerging partnership with industrial data scientists is bringing an end to those bad dreams. Data is helping shape maintenance strategies, helping to pinpoint issues that may require preventive maintenance while also avoiding unnecessary planned maintenance.
Data scientists are complementing the deep experience and tribal knowledge of reliability engineers to create a new dynamic duo of industrial maintenance. Industrial customers who have been awash in data but lacking the information they need to reduce maintenance costs and downtime now have an equation that works.
“Insights and data are only as valuable as they are actionable,” said GE’s Casey Walleck. “Reliability engineers know what’s important.”
The result of the partnership is increased savings and equipment availability.
Seeing Big Savings and Avoiding Catastrophic Failure
Walleck heads the customer reliability team at GE’s Remote Monitoring and Diagnostics center in Lisle, Illinois, where they monitors assets in the oil and gas, aviation, chemicals and manufacturing industries.
The team monitors data from the industrial assets, which is combined with historical analytics that can help identify issues long before a catastrophic failure occurs. The savings from individual instances of avoided production loss and avoided maintenance cost ranges from $2,000 per instance all the way up to $60 million, Walleck said.
On average, it takes three-and-a-half months to see a return on a year’s investment in software remote monitoring and diagnostics.
The Aha Moment
Cost savings are compelling for the C-suite. But reliability engineers are made of sterner stuff, Walleck said, and are looking for deep expertise. That’s why GE has a cadre of reliability subject matter experts who have been on the job who can consult on machine issues.
The real “aha moment” comes when the data team points out an emerging issue that isn’t yet apparent to the engineers.
“It happens when we tell them to go do something that they wouldn’t have done otherwise,” Walleck explained. “We say, ‘Go check that bearing, there’s something wrong with it.’”
But even if nothing is wrong, the RM&D team is in constant contact with the engineers. There’s always something in the asset portfolio that they need to keep their eye on.
This constant vigilance allows the combined team of GE data scientists and customer engineers to creep earlier and earlier into the equipment life cycle and start advising on maintenance.
Engineer, Multiply Thyself
Those engineers with decades of knowledge on critical assets are, for all intents and purposes, irreplaceable. But data scientists can help them multiply themselves by allowing them to monitor many more assets with RM&D services and even automating some processes.
It can also capture some of the tribal knowledge that they has been passed down over the years, but not necessarily codified or even written down. RM&D can capture some of the pattern recognition that the best engineers have honed over the years.
Now that they’re paired with data scientists, reliability engineers are becoming more valuable than ever before.
“The reliability engineer is where the rubber meets the road,” Walleck said.
At Minds + Machines 2016, GE Digital will dive deeper into how productivity is unlocked when data scientists partner with reliability engineers. Check out the full agenda.