Ensuring that equipment is working safely and efficiently is critical to any successful manufacturing operation. That goes double for food processing. Erratic asset performance indicated by vibration or power performance issues can produce batches of wasted, unhealthy product and unplanned downtime.
In the past, some food-processing facilities took a run-to-failure approach to facility maintenance. At the time this was considered more acceptable than a preventive maintenance approach of scheduling maintenance based on data about asset longevity or original equipment manufacturer recommendations, rather than actual evidence that an asset might need attention.
This preventive approach could be costly and lead to wasteful spending on premature replacement of working parts, so many operations opted to let equipment run to failure. The problem was companies paid in other ways. Each time a machine fails without warning, it costs anywhere from hundreds to tens of thousands of dollars per hour in lost productivity1.
An alternative to those two approaches was to adopt machine monitoring that would provide more data about the health of the equipment. This required complex and time-consuming installation protocols, and running cables or mounting detailed bracket-and-screw systems. Some systems required internal installation—a messy process that also called for opening a machine, completing installation, and extensive cleanup, which increased the risk of contaminating food products. Even after all this labor, many of these sensors didn’t provide accurate or easily accessible information about machine performance, and most didn’t provide round-the-clock insight into a system’s operational trends and health.
It’s not surprising that against this backdrop many maintenance and factory managers continued to choose the run-to-failure approach.
Adjusting from run-to-failure to optimal maintenance
Fortunately, modern sensor systems for the food-processing market have made it much easier to adopt a remote condition monitoring (CM) system and provide more transparent and accessible data.
The latest remote CM sensors are mounted externally to machines—rather than internally—and take less than an hour to install. Built on advanced cloud-based technology, these sensors use wireless connectivity to send vibration and power monitoring data to a computerized maintenance and management system (CMMS) such as eMaint. The data is immediately accessible to maintenance teams via mobile devices or PCs. Every team member can see data seamlessly in real time, so they can discuss and analyze trends in machine performance. From this, they can decide how to further assess the machine’s behavior and draw conclusions about when and how to address early-stage abnormalities based on measurements.
Remote CM is considered an improvement over preventive maintenance because it is based on actual evidence that an asset may need attention. It supports predictive maintenance by providing real-time trend data and sending alerts to facility managers when those fluctuations exceed accepted, user-defined norms for that asset.
This approach eliminates the waste associated with unnecessary preventive repairs, while alerting maintenance personnel to problems before they become acute. This supports phased, scheduled maintenance tailored to documented need.
The advantages of remote CM technology
Facility managers can position wireless sensors on or near assets they are measuring, and then link the sensors to a secure public cloud. Wireless sensors can monitor several machine parameters, including vibration levels, multiple aspects of a machine’s power (voltage, current, etc.), and surface temperature. Each sensor can be set up to send push notifications as alarms when monitored assets deviate from user-set parameters. Facility operators can customize alarm triggers around the specs for a particular piece of equipment and send alerts to select teams or individuals.
Wireless sensors are paired with eMaint CMMS software that aggregates trend data and stores records and provides information visually in reports. This makes facility audits easier and provides new maintenance team members with readily available historical equipment performance as they grow into their roles.
Food-processing maintenance teams can also use performance history to make more strategic maintenance decisions, while minimizing asset downtime. They can track an asset’s performance and longevity in comparison to expected specifications, and use that information to inform future equipment acquisition plans.
Fluke offers remote CM tools which, together with eMaint, provide a comprehensive picture of asset health and the documentation necessary to comply with strict safety, health, quality, and environmental regulatory standards.
Fluke 3561 FC Vibration Sensors measure real-time and historical triaxial vibration as well as surface temperature data. This enables you to screen for imbalance, looseness, misalignment, and bearing faults in rotating assets, including pumps, motors, and conveyors.
The Fluke 3540 FC Three-Phase Power Monitor measures key electrical variables such as current, voltage, and frequency to screen food-processing equipment such as freezers, refrigerators, and conveyor belts for performance problems or premature wear.
In action: Lamonica’s Pizza Dough
Lamonica’s Pizza Dough in Los Angeles, which manufactures ready-to-bake raw pizza dough for consumers, started testing a Fluke gateway and sensor to remotely monitor its refrigeration unit motors.
“Lamonica’s Pizza tries to provide the best quality dough for a delicious price,” said Jorge Leon, refrigeration mechanic. “Before, what we would do is wait until it breaks; then we’d fix it. Once we had Fluke Connect, we were able to detect problems ahead of time. It became preventive maintenance, more than just repair.”
Because Lamonica’s Pizza Dough offers raw pizza dough, refrigeration units need to operate properly to uphold product quality. Concerns about potential refrigeration irregularities led Leon and Lamonica’s to Fluke.
“We deal with a lot of motors, and it’s good to detect when they’re over-amping,” Leon said, noting that Fluke sensors log power currents. “You know exactly what time you were over-amping the motor.”
Historically, Lamonica’s has used many sources for machine data, such as outside vibration specialists, costly teardowns and more. However, maintenance teams can get this information from a much more cost-effective and easily accessed system in Fluke.
Leon was eager to begin formally working with a Fluke 3540 FC Three-Phase Power Monitor to better monitor the refrigeration units, especially with the experience he’s already had with the gateway and sensor.
“It proved to minimize downtime by catching the problem ahead of time,” Leon said. “It has eased my mind because we have alarms set up.”
5 steps to beginning a sensor pilot program in your food-processing facility
- Choose an asset to track
Consider a “bad actor” or a machine that is difficult to access. Food-processing environments often include finicky or hard-to-reach machines in physically remote or dangerous, locations.
- Choose the best sensor for the job
When the asset misbehaves or malfunctions, what indicators might have predicted the problems? Is it a matter of power fluctuation or vibration and friction?
- Download the Fluke Connect app
Make sure to involve multiple team members so all stakeholders become familiar with the tracking interface and learn how alarm notifications will be delivered to some or all of them.
- Install the sensor
Sensor installation is simple because sensors are installed externally on assets to be monitored.
- Assess and analyze data
With condition monitoring data, teams can take a more strategic approach to planning repairs, noting patterns in the data or (eventually) developing historical records for reporting purposes. This could influence future operation of the asset(s). Teams can aggregate data from multiple sensors for a single view of asset health. They can also incorporate non-sensor data (such as hand-tool measurements taken during regular plant rounds) into the data environment, for a holistic understanding of performance.
When it comes to food processing, identifying and addressing small manufacturing issues before they escalate into large-scale problems is smart business. Wireless sensors equipped with remote CM software make it easy to use today’s advanced cloud technologies to run a more efficient continuous monitoring system.
Editor’s note: You can download this article as a pdf to read later.
 Martinez, Henry. “How Much Does Downtime Really Cost?” Information Management, 29 July 2009, www.information-management.com/news/how-much-does-downtime-really-cost