If your production machines could talk, what would they tell you? Would they be annoying and over-dramatic with their problems, or would they be pretty chill, and just tell us what we need to know. I don't think anyone needs, or wants drama from their production machines (or anyone else for that matter). I think a simple "compressor unit 3 in location10, needs bearing size X replaced within the next two days" would be good. No chit-chat about your vacation plans or how your BBQ turned out last weekend; none of that; just straight to the point and clearly tell us what they need and when they need it by would be great.
Emerson’s Zedi Machine Health Monitoring does just that - we can provide you and your people with complete, secure and actionable data to help you anticipate impending issues and proactively deal with them to prevent or minimize downtime and to keep production running efficiently and reliably to meet your lofty targets and goals.
Emerson's Zedi IIoT platform to analyzes your data into actionable, easy to understand analytics to closely monitor issues like machine vibrations and process variables to keep your people on top of changes in the most common fails that can predict issues with a wide range of assets.
Here is a list of what we can monitor now:
• Balance – imbalance• Alignment – misalignment
• Looseness – mechanical looseness
• Blade Pass – bladed component issues
• Flow Turbulence – turbulence in pumps & rotating stall in fans
• Gear Faults – gear misalignment & cracked or broken tooth
• Tooth wear – worn tooth issue
• Bearing – mechanical bearing defects
• Lubrication – anti-friction bearing lubrication issues
• Oil whirl – bearing instability caused by oil whirls
• Air gap – inductive motor air gap problems
• Duty – instrumentation problems; heat exchanger
• Fouling – heat transfer coefficient; heat exchanger
In short, we’re helping you upgrade from preventative production asset or machine maintenance to predictive maintenance. What’s the difference? Well, it can be up to $260,000 per hour*—that’s what a recent survey showed was the cost of facility downtime, which might be due to scheduling your “preventive” maintenance just one day too late. Not to mention the cost associated with all that 'preventative' maintenance you have scheduled for field people and vehicles to drive all over the place doing that maintenance - that is may not even need - over time, that can really add up!
The practical difference is that preventive maintenance is based on manufacturer recommendations for typical operating conditions—based on things like temperature, hours of operation, workload and others. That may be fine when everything always works normally—but when was the last time that actually happened?
Predictive maintenance, on the other hand, uses sensors to track things as mentioned above, to give you early warning when things are just starting to stress. And it can tell the difference between normal daily fluctuation parameters and outliers. It's like those people we all know; they take great care of their bodies, eat properly, get plenty of rest and have no stress; but something else goes wrong and they end up having a heart condition, or something else potentially worse out of nowhere! Maybe we need to look at 'predictive' people health too.
Either way, an early warning can let you know a technician needs a few minutes to replace a bearing or to change the oil. Otherwise that issue could create a domino effect as one machine’s sudden lockup could damage conveyors and other machinery above and below it in the line. So when operating conditions have conspired to shorten the maintenance life, you’ll be ready.
Of course, predictive maintenance can in some cases lengthen the maintenance schedule. Maybe compressor 5 is newer and more advanced, getting more hours out of a bearing. Why leave it on the same schedule as your 10-year-old faithful machine?
Or maybe you’re one of the 70% of companies surveyed in 2017 who are not sure when maintenance or replacement is needed**. That's a pretty large percentage of companies that just don't know or have any insights at all.
**https://garvey.com/7-downtime-statistics-find-terrifying/
*https://www.aberdeen.com/blogposts/stat-of-the-week-the-rising-cost-of-downtime
