Lower costs, higher output with Predictive Maintenance
Few breakdowns happen without warning. The challenge is spotting the signs early enough to plan and schedule repairs. Predictive maintenance technologies provide that insight.
Used wisely, vibration and oil analysis, thermography testing and ultrasonic leak detection reveal changes in how equipment is running. Before there’s any obvious sign of impending failure, replacement parts can be put on order and the work can be scheduled for a time that minimizes production losses.
A predictive maintenance program reduces unplanned production downtime by allowing better maintenance scheduling. It improves equipment safety and product quality through early identification of changes in operating conditions. Capacity increases when less time is spent on reactive maintenance and costs go down because there’s less need for overtime and rush orders.
A data-driven maintenance strategy
ATS’ predictive maintenance strategy uses data to drive asset management decisions. Traditional time or usage-based maintenance helps protect against breakdowns, but leaves open the risk of doing too much, too little, or the wrong type of work. We begin by base-lining current operating conditions. Then, regular data acquisition and predictive maintenance analytics start to reveal important trends.
Knowing what’s likely to happen inside complex machinery lets managers make better decisions. Spares inventories can be paired down instead of holding them for “just-in-case.” Decisions about scheduling equipment maintenance can be taken collaboratively rather than overriding production needs. By revealing the true causes of failure, the data can shape purchasing decisions, depreciation rates and planned replacement dates.
A crystal ball for the maintenance function
Every predictive maintenance program ATS puts together is tailored to the specific needs of each facility and customer. Inspection and evaluation by skilled technicians is a common thread running through every program. That’s why businesses are hiring ATS to capture their valuable data and use it to make more aligned decisions affecting their machine uptime.