Predictive Maintenance Environment in Food Processing Plants Provides Early Warning System

Want to save $616,500 a year on a couple of sets of bearings? Consider this simple math word problem:

Johnsonville Sausage LLC had nine checkweighers on which the $55 bearings (50 per machine) were wearing out every two weeks [$55 X 50 bearings X 9 machines X 26 replacements per year = $643,500 per year].

The maintenance guy replaced them with $75 bearings that lasted 15 months each [$75 X 50 bearings X 9 machines X 0.8 replacements per year = $27,000 per year].

“And that doesn’t include my team’s labor,” says Tom Ehrenberg, engineering systems analyst at the Johnsonville, Wis., sausage company. “I wouldn’t have noticed the repair and purchasing history without the trending and analysis of a CMMS [computerized maintenance management system],” he says. In his case, it was the MaintiMizer from Ashcom Technologies Inc.

For more than two decades, the maintenance profession has undergone an evolution from fixing equipment when it breaks to preventing failures to predicting when problems will occur. The results are lower risks to products, productivity and people working in the plant.

Working in a predictive maintenance (PdM) environment can provide this kind of early warning. But not everything needs to be predicted; some assets are more cost-effectively maintained by other means. Plants must consider the three alternative approaches to maintenance for any given asset. According to David Berger, partner in Western Management Consultants, Toronto, they are:

1. Failure-based maintenance (FBM): An asset is run until it fails, at which point it’s repaired or replaced. Depending on the asset, this approach can be hugely economical (e.g., light bulbs), or highly expensive or even life threatening (e.g., large rotating equipment).
2. Use-based maintenance (UBM): An asset is maintained on a periodic or metered basis such as every three months or 10,000 gallons of use. In many cases, this is a more economical approach than FBM, especially when the consequences or cost of running equipment to failure are higher than the cost of the UBM program.
3. Condition-based maintenance (CBM): Triggers are established that correlate to impending equipment degradation or failure. When these conditions are identified through periodic inspections or monitoring, defensive actions are taken, such as repair or replacement of a part, to pre-empt the failure just in time.

Condition-based monitoring identifies impending equipment degradation or failure so corrective action can be taken before a catastrophic failure.

“There are always three choices for maintaining a piece of equipment,” Berger says. No matter the size or sophistication of reliability engineering and failure modes studies, “The same kinds of fundamental questions apply in any context: What does the asset do? What happens if it fails? What program can we put in place that can cost-effectively ensure its reliability?”

Because of the expense of bringing monitoring technology to bear in data-gathering and historical trend analysis, CBM is typically reserved for the most critical assets in a plant whose failures will most risk a production line to go down, a severe health or safety risk such as an explosion or a repair that will take operations offline and torpedo fulfillment of customer orders.

Condition monitoring technologies are many and varied. Vibration monitoring equipment is commonly used to compare meter readings against manufacturer design specifications to quantify the gradual degradation of shafts or bearings and to decide when it's time to make a repair.

Lubrication analysis goes well beyond viscosity readings for serious PdM-ers, who typically send samples to outside laboratories for detailed measures of particulates, oxidation and flashpoint, which pinpoint causes of performance degradation. Likewise, infrared thermography, ultrasonic and laser monitoring systems are in use across many industries.

“There are a lot of different ways to go about condition monitoring,” says Steve Matthews, business manager for Predictive Maintenance Solutions. The Richmond, Va., company provides laser shaft alignment equipment for rotating machinery from sister company Vibralign, and resells DLI Engineering vibration monitoring systems and services. Customers typically outsource services due to the specialized skills required to analyze the data.