As manufacturers work to rebound from pandemic-related disruptions, one of the obstacles they face is a growing shortage of maintenance technicians. These workers were already in short supply before the pandemic, and now the problem is even worse.
While the U.S. Bureau of Labor Statistics projects that job openings for machinery maintenance workers and similar roles will grow at more than three times the rate for all jobs, a wave of retirements combined with fewer new workers is creating a huge gap. By 2030, Deloitte projects that there could be more than 2 million unfilled manufacturing jobs in the U.S., including maintenance roles.
The shortage of maintenance technicians creates a cascade of challenges for manufacturers. In the short run, these challenges include disrupted production schedules and increased safety risks. Over the long haul, a lack of regular maintenance and insight into machinery function can put plants’ capital equipment at risk of serious damage and shortened lifespans. Each of these challenges puts manufacturers at a competitive disadvantage.
One solution to the worker shortage is to use wireless sensor networks to automatically monitor equipment temperature, vibration and other functions in order to identify and prioritize maintenance needs. Then, managers can schedule maintenance in ways that optimize technicians’ efficiency, so they can keep capital equipment operating, avoid unplanned downtime and reduce equipment-related safety risks.
Remote sensors are useful for plant maintenance tasks because they are low-cost, don’t require wiring and install quickly. Once in place, they continuously send real-time data to a secure gateway that relays that data to the cloud for secure storage. Plant managers, maintenance chiefs and other employees who need access can then log in to the sensor network console on a smartphone, tablet or computer to view real-time data such as motor vibration range, food storage equipment temperatures and humidity levels in areas where computer equipment and other equipment must stay dry.
With a sensor network in place, the console data can help avoid acute maintenance issues, help schedule preventive maintenance tasks in the most efficient way, and build a data set that managers can use to implement a predictive maintenance program that yields long-term cost savings and may extend the life of the equipment.
Avoid run-to-failure with remote sensor data
Unplanned downtime caused by equipment failures is expensive. One study found that the average cost of unplanned downtime is $250,000 per hour, and equipment failures can result in many hours offline, especially if the plant has to order—or fabricate—parts to complete repairs. However, proper maintenance and monitoring can prevent many equipment failures, and sensors can help by alerting maintenance crews and managers as soon as a problem arises.
For example, a vibration sensor attached to the motor on a CNC (Computer Numerical Control) router can indicate when the router is operating outside of its ideal range. The sensor system can generate an instant alert that’s sent via SMS, email or automated voice call to the shift manager, supervisor or technician so they can check the router to see what’s causing the problem. If a worker is placing too much stress on the router, they can learn to adjust to operate the equipment within the proper range. If the equipment has a loose part or another mechanical problem, it can be fixed before the router fails or creates substandard product.
Preventive maintenance optimization with wireless sensors
The data that sensors collect from plant equipment can create a picture of how that equipment functions over time. By generating reports in the network console, maintenance technicians can see which pieces of equipment are trending away from their ideal operating temperature or vibration ranges and use that information to decide how to prioritize preventive maintenance tasks.
For example, instead of performing routine maintenance on every compressor during the same week, technicians could focus on the ones that are moving fastest toward out-of-bounds measurements and free up time to also take care of equipment with worn bearings—as indicated by vibration data—before it fails.
Prioritizing maintenance by urgency of need also allows plants to keep running with fewer available technicians, and it allows workers to order replacement parts and supplies early enough to avoid express shipping costs. Because preventive maintenance can be scheduled during the least disruptive times, it can help minimize downtime as well.
Sensor data is necessary for predictive maintenance programs
Equipment data from sensors is the cornerstone of predictive maintenance (PdM)—a customized maintenance schedule based on data-driven, AI-powered identification of equipment needs. By performing maintenance only when it’s needed, manufacturers can save money on calendar-based preventive maintenance. They can also use PdM data and analyses to prevent equipment failures by detecting small but significant changes in equipment function with enough lead time to plan repairs and order or make any needed replacement parts.
These advantages are the reason that the U.S. market for PdM in manufacturing is projected to grow by more than 16% CAGR through 2027. Because it takes time to build up a usable database for PdM, manufacturers who begin gathering data now will have a competitive advantage over those who adopt PdM later on.
Sensors on OEM equipment can help customers solve their maintenance challenges
For producers of manufacturing equipment, remote sensor systems represent a way to help customers maintain their equipment for efficiency. Adding wireless temperature and vibration sensor to new products enables brands to offer maintenance as a service (MaaS) as a subscription. By taking maintenance monitoring off customers’ to-do lists, equipment manufacturers can build loyalty, bring in more revenue and help customers get the most value possible from their equipment.
Even for manufacturers whose products aren’t a natural fit for MaaS offerings, implementing wireless sensor networks on their own plant equipment offers a secure, easy to deploy method for keeping that equipment in good shape and making the best use of employees’ time. With so few technicians available to fill a growing number of jobs, sensors represent a clear path to more efficient and consistent maintenance.
Ray Almgren is the CEO at Swift Sensors, a developer of cloud-based wireless sensor systems for industrial applications. Prior to his role at Swift Sensors Ray was the Vice President of Marketing at National Instruments. Ray received his BS in Electrical Engineering from the University of Texas at Austin. Follow him on LinkedIn, Facebook, Twitter @swift_sensors.
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