Why do you need a predictive maintenance strategy to succeed?
Technology has saturated nearly every step of the manufacturing process. As more facilities embrace Industry 4.0, technologies like AI, automation and the IoT are making factories safer, more efficient places. Predictive maintenance can bring the same benefits to machine repair.
Many manufacturing technologies improve the operation of machinery, but that’s not all machine ownership entails. You also have to consider the maintenance and repair of any devices, robotic or not. Proper, proactive care can extend a machine’s life and functionality, and vice versa.
Manufacturers spent at least $50 billion on maintenance and repair in 2016. Today, your facility may host more advanced, complicated machinery, making repairs even costlier. To make the most of your mechanical investments, you need optimal care, and predictive maintenance enables that.
The Risks of Run-to-Failure Operation
The most straightforward approach to maintenance is running machines until they malfunction. Run-to-failure operation often isn’t as extreme as waiting until something breaks, but typically looks like running something until an issue is noticeable. While this approach maximizes a machine’s uptime until the point of failure, it comes with considerable risks.
Most notably, run-to-failure operation increases the likelihood of a catastrophic malfunction, which can be costly and dangerous. Without attention, seemingly minor issues can snowball into much more severe ones that cost more to repair. Some of these may even threaten any employees working on or near the machine when it breaks.
While run-to-failure temporarily avoids downtime, it will eventually lead to expensive interruptions. Malfunctions will cause unexpected stoppages, disrupting the entire manufacturing process by ceasing or slowing production until repairs occur. You’ll need a more proactive approach to maintenance to avoid these monetary and safety risks.
Traditional Preventive Maintenance Misses the Mark
Most manufacturers try to avoid run-to-failure to some degree, typically adopting preventive maintenance. This approach involves scheduled downtime to perform routine procedures on machines, preventing major issues. Preventive maintenance can add 20 years to a machine’s life, but traditional methods aren’t perfect.
Typically, preventive maintenance looks like getting the oil changed in your car, where you perform small tune-ups on a schedule. The trouble with this approach comes when a machine doesn’t need any maintenance. There’s a chance you could be stopping production, however briefly, when you don’t need to.
Scheduled maintenance can also make inventory management more complicated than it needs to be. You’ll have to decide which parts you need on hand and when to order them, which can be challenging to determine. You can end up with a surplus of one component or find yourself needing another you didn’t anticipate.
Predictive Maintenance Fixes Issues on Both Sides
Predictive maintenance provides a solution to the shortcomings of both these approaches to repair. This method is preventive, but unlike traditional, scheduled preventive maintenance, it involves addressing needs as they arise by using machinery to predict when a machine needs a specific tune-up or repair and addressing it before it leads to malfunctions.
Like traditional preventive approaches, predictive maintenance takes time to fix small issues before they become more severe. Unlike conventional methods, though, it’s need-based, so you don’t have to worry about unnecessary downtime for unneeded repairs. It enables you to run your machines with the least amount of disruption possible.
Since this method relies on predictions, it also addresses the issue of inventory management. An advanced enough system can tell you what you need before the problem becomes disruptive. You can then acquire the parts you need to do the job.
How Does Predictive Maintenance Work?
Predictive maintenance relies on IoT technology that records data on a machine’s performance. You may already use these devices to measure things like efficiency, as many smart factories do. The predictive approach to repair takes these readings and runs them through an algorithm that looks for potential maintenance issues.
Since manufacturers must filter and analyze data to draw insights from it, AI is crucial here. Making predictions like this based on data is AI’s specialty. AI also gets better at understanding each machine’s maintenance needs the more you use it.
Through machine learning, AI programs can teach themselves how to recognize new patterns. Since every machine ages differently, this adaptability is crucial to reliable predictive maintenance. Your predictive maintenance strategy’s effectiveness hinges on your AI and how you train it.
Developing and Applying Your Predictive Maintenance Strategy
As helpful as it would be, applying predictive maintenance to every machine in your facility at once isn’t realistic. It’s better and more feasible to take a more gradual approach, developing it on a few systems before expanding. As a starting point, look for any machines that are integral to your process and need frequent maintenance.
Start with these machines, either installing new IoT sensors or using existing ones to gather performance and mechanical data. Then, start running this data through an AI program capable of predictive analytics. Train it to make connections between things like oil levels and the need for maintenance.
While you focus on developing AI, don’t forget about your human maintenance crew. They must have access to machine data to respond as quickly as possible before the AI becomes adept at predicting maintenance needs. They may also be able to see areas where the AI falls short and make recommendations.
As you develop your predictive maintenance system on one or two machines, apply preventive maintenance to everything else. If your manual maintenance systems are similar to the AI-based one, transitioning will go more smoothly. From there, once you’re satisfied with your predictive maintenance’s performance, start applying it elsewhere.
Protect Your Investments
Industrial machines are a substantial investment. If you don’t take care of them, you could end up losing much more money than necessary. Predictive maintenance will help you get the highest return on your investment you can.
Predictive maintenance takes the smart factory to a new extent, applying performance analytics to repair, not just operation. As you move toward a connected facility, this method is a crucial step toward success. Without it, your IoT investments will go underused, and your machines will experience a shorter life.
Article by —
Megan Ray Nichols
Freelance Science Writer
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