Maintenance Isn’t an Expense; It’s an Investment

July 4, 2016
Maintenance becomes strategic when you leverage real-time machine data to proactively manage your production assets.

Almost a third of all manufacturing facilities experience unexpected machine failure, and many report up to 800 hours of downtime each year. Fortunately, this reality is about to change. Companies that are investing in preventive maintenance strategies are reducing their risk of unplanned downtime and in turn improving their production volumes and profits.

The majority of manufacturers—past and present—rely on equipment specs to set up maintenance and replacement schedules. Companies value and understand the importance of avoiding unplanned downtime, but without machine data, scheduled maintenance is the best defense. But machine specs and maintenance guidelines don’t accurately incorporate actual use on the floor. Companies are left with a reactive strategy, leaving them vulnerable to unnecessary maintenance, equipment being replaced while it still has a useful life, or unnecessary downtime due to unexpected problems.

Let’s look at a cylinder. An operator would never notice any lag between the moment a signal is sent to the cylinder to start and when it actually starts. However, it is possible that the cylinder actually took 50 ms to start; knowing that piece of information could reveal a developing problem. By monitoring that data, you identify a pattern that indicates an impending failure. Once the pattern is identified, the component would be scheduled for repair and be replaced prior to failure, during a “planned maintenance event.”

Condition monitoring identifies changes and events that could shorten the normal lifespan of a machine. By tracking the equipment in operation, problems can be flagged and repaired. Replacement parts can be ordered in advance and personnel are scheduled to make the repair during normal operations. Bottom line: Condition monitoring is a proactive strategy to take the “what if?” out of maintenance.

There are many monitoring tools that can be used in a predictive maintenance program, including vibration analysis, thermography, motor testing, tribology and laser shift alignment. Whether you need standalone modules or can integrate these tools with your existing automation and control systems depends on your situation. A control system integrator can assist you in assessing how to start and identify which data to track to give you the greatest return.

This newfound data has given us the ability to use statistical process control (SPC) in ways that have not been considered before. With SPC, you can monitor and potentially control devices to ensure reliability by predicting anomalies that lead to failures. SPC can be set up to monitor normal operation on any data point and detect statistical variances that identify upstream problems well before they become unscheduled downtime.

Because there is so much data available, it’s important to identify what data to collect, how to analyze it and what to communicate to the shop floor. Failure to carefully consider your roadmap for your data usage can lead to wasted money, frustration and poorly functioning systems. Start with your most critical assets, build a foundational system and build onto it, in small chunks, from there. In this way, you can start getting important information to plant personnel right away so action can be taken right away.

Maintenance becomes strategic when you leverage real-time machine data to proactively manage your production assets. Reducing unplanned downtime results in improving profitability. That’s how you convert maintenance from an expense to an investment.

Michael Gurney is CEO of Concept Systems Inc., a certified member of the Control System Integrators Association. See Concept Systems’ profile on the Industrial Automation Exchange.