What happens when your production line suddenly stops? It’s probably happened to you before … and it will probably happen again.
Whenever a critical piece of equipment stops working—for any reason—diminished productivity, revenue and customer loyalty follow unless your team is ready to respond.
The difference between a minor disruption and a costly crisis often comes down to one thing: Did you see the breakdown coming?
The value of listening to your machines
Machines don’t usually fail without warning: they run hotter than usual, vibrate at a slightly different frequency, draw a little more current, etc. These small changes are easy to miss through manual checks and scheduled inspections, but they’re expensive to ignore.
While most modern manufacturing lines are highly efficient, they’re also vulnerable to unexpected breakdowns caused by aging components and undetected equipment-health issues. No matter how advanced your operations, a single failing part can bring them down.
What is predictive maintenance?
By proactively detecting likely failure before it occurs, predictive asset maintenance changes the game in advanced manufacturing.
It’s made possible with a flow of real-time performance data coming from connected equipment for meaningful analysis. This data foundation allows you to identify subtle patterns and trends, surface early warnings and act before a problem takes hold.
Here’s how predictive maintenance works:
- A network of sensors monitors machine health and collects data about operational parameters like vibration, temperature, speed and pressure.
- That information is continuously analyzed for patterns and variances to detect early signs of wear, misalignment or fatigue.
- When a performance variance is uncovered, maintenance teams are alerted so they can complete necessary repairs or schedule a parts replacement.
Think of predictive asset maintenance as machines “talking” to operators. When they share real-time performance signals with the people responsible for keeping lines running, critical repairs can be anticipated and addressed before equipment breaks down.
Depending on your plant’s technology infrastructure and digital maturity levels, predictive maintenance alerts could look like:
- Simple emails to notify team members about issues
- Text alerts that reach technicians on the floor as soon as a variance is detected
- Dashboard updates that give teams a unified view of asset health across lines and locations
- Automatic feeding of sensor data to AI models to predict failure and optimize maintenance timing
Advantages of predictive maintenance for advanced manufacturing
For operations and maintenance teams, gaining early real-time visibility into equipment health and performance changes how work is done. Repairs can be planned instead of rushed. Parts can be ordered without panic or rush shipping. Production can keep moving while maintenance is scheduled during times that will have the least impact.
This shift to predictive maintenance has a compounding effect on plant operations:
- Equipment failures become predictable and preventable instead of sudden and costly
- Repair costs are lower since teams work on their own timeline rather than responding to a crisis
- Machines run reliably and last longer because wear is addressed before it compounds
- Maintenance labor moves to where it’s needed most
- Energy efficiency improves when machines operate within designed parameters
- Asset utilization rates rise, maximizing throughput and ROI
Advantages of predictive maintenance for OEMs and integrators
The same connected data that helps plant operators prevent downtime helps OEMs (original equipment manufacturers) and systems integrators design, build and support smarter, more resilient equipment.
By incorporating remote monitoring into offerings, OEMs and integrators can position themselves as long-term operational partners. They become the team that installed your equipment … and keeps it running.
Predictive insights can also help OEMs make their own products better. When they can observe performance across dozens of customer sites, OEMs gain visibility into how their machines hold up in real operating conditions: which components wear the fastest, where failures originate and possible design changes that would address problems.
Unlocking the power of connected data for predictive asset maintenance
Capturing and transmitting equipment and performance data is the only way to stay ahead of equipment failure and protect uptime.
For example, by adding low-cost sensors to existing conveyors, robots and automated guided vehicles (AGVs), manufacturers can capture real-time data on indicators like vibration, temperature and battery health. When this sensor data is combined with programmable logic controller (PLC) information, such as machine status and error codes, maintenance teams gain a complete and connected view of asset health. With these insights, they can flag early signs of trouble long before a breakdown happens.
Belden’s complete connection solutions help plants take advantage of intelligent monitoring to unlock new possibilities like predictive asset maintenance.
Our solutions enable you to:
- Capture, move and centralize real-time data from new and legacy machines
- Integrate sensors and hardware to track equipment conditions
- Unify data so it can be analyzed and acted upon
With the right solutions in place, advanced manufacturing environments can break the cycle of unpredictability and get ahead of disruptions by making hidden issues visible and actionable.