How Data-Driven Predictive and Preventative Maintenance Can Increase Manufacturing Uptime


Unplanned downtime is the ultimate nemesis for a facility, operations, or production manager. Between the lost person-hours, suspended production, and cost of repairs, it is enough to delay your shipments or, worse — throw your budget off track. Most manufacturers regularly deploy preventative maintenance practices to avoid these situations — but that usually is not enough. Traditional preventative maintenance resolves issues on only 18% of machinery when performed, which means 82% of machines break down due to random or unknown factors.

Those unknown factors can be identified through the consistent monitoring of machinery and addressed with predictive maintenance. More often than not, manufacturers send employees to walk the facility and manually record data from various meters and sensors — but this practice can interfere with productivity and allow for human error in transcribing data. Even under the best circumstances, the accurate collection, aggregation, and analysis of that data are challenging.

Through a network of devices with wireless sensors that automatically capture data and transmit it to a centralized software platform, facility, operations, or production managers gain insight into machine performance and where there might be issues.

Let’s take a closer look at two ways you can facilitate preventative and predictive maintenance to benefit your business.

Preventative Maintenance

Through interconnected sensors and instruments, data is collected 24 hours a day and stored in a centralized location (often the cloud), which helps to remove guesswork and estimations around preventative maintenance. Over time, facility managers can meter or collect data to establish benchmarks of regular machine usage and performance and schedule preventative maintenance sessions at the right time.

Example: In a beverage manufacturing plant, a conveyor belt that transports the product to the quality assurance station has a history of unplanned downtime. With operational data tracked 24 hours a day, the conveyor belt’s average total use time is established, which helps facility managers understand what the threshold is for preventative or scheduled maintenance. Over several months, data is collected and shows the conveyor belt operates for about 16 hours a day. The facility manager knows that at 2,000 hours of use, the conveyor develops problems and can break down, so preventative maintenance is scheduled at 1,700 hours to limit the risk of unplanned downtime. 

Predictive Maintenance

With the same interconnected sensors and instruments, facility managers can more easily (and accurately) get ahead of issues that lead to unplanned downtime. The motors within machines often are early indicators of when there is a risk for unplanned downtime. By implementing specialized sensors for vibration and temperature, facility managers can better understand a motor’s status and when predictive maintenance should be deployed. 

Example: A vibration sensor attached to the motor of the conveyor belt in the beverage manufacturing plant. By carefully monitoring vibration frequency and patterns, the facility manager can understand the baseline for the motor’s status and, ultimately, the conveyor belt’s status. The motor’s vibration levels remained in line with the predetermined benchmark for a few months, so no maintenance was necessary. However, eventually, the vibration frequency and amplitude started to increase. The rise in motor vibration indicated that the bearings within the motor had begun to fail, and the motor needed replacement soon. By having the data to identify the change in vibration patterns, the facility manager could predict the motor’s imminent failure and schedule maintenance before it caused any damage to the rest of the conveyor belt or production line.

Whenever manufacturing production comes to an unexpected stop, the result is a loss of product and productivity, increased stress, and focus on how to avoid this situation in the future. 

Digital Lumens’ SiteWorx Facility Insights application suite enables metering and monitoring of sensor data, such as airborne particle counters, air quality, differential pressure, flow, accelerometers, and gas sensors, in addition to energy and other critical utilities. When data falls outside established limits, SiteWorx will trigger email or SMS notifications for you to take action. 

Learn how SiteWorx Facility Insights create new efficiencies and value for your industrial facility.