Predictive Maintenance vs Preventative Maintenance

Maintenance will happen. It doesn’t matter how well any piece of equipment is made, it’s still going to be subject to the laws of wear and tear. That means at some point it won’t work as well as it did. At a later point, it might work in a way that damages your product. Eventually, you could face the prospect of it not working at all.

With that in mind, what’s the best way to make sure your equipment is operating for as long as possible in a way that doesn’t affect your product? Is it possible to eliminate downtime due to faulty machinery? Can you fix a problem before you know you have one?

What is predictive maintenance?

Predictive maintenance uses sensors to analyse anomalies in production and evaluate the state of machinery. Using that data, systems can predict when equipment is going to need to be maintained.

If the predictive maintenance systems notice a pattern emerging that previously resulted in a breakdown, maintenance engineers can be alerted and corrective work carried out.

Because it happens while equipment is in use, rather than requiring shutdowns at set intervals, it aims to increase the amount of time machinery is up and running between maintenance activities.

How does predictive maintenance work?

Predictive maintenance systems link together sensors, equipment, software, and people. Sensors monitor the quality of output and the machines themselves. Software handles data collection and aggregation. If there’s an issue, maintenance engineers are informed and get to fixing any issues.

A predictive maintenance setup needs to make use of internet of things (IoT) devices and intelligent software systems. Physical systems need to be monitored and communicate vital information to digital ones. That data needs to be collected and turned into insight.

Real time data can be combined with historic data and handled by software powered by artificial intelligence (AI) and machine learning, to predict when equipment will need to be maintained.

A predictive maintenance system is a real example of what Industry 4.0 is capable of; with people, machines, and the digital world working seamlessly to achieve peak production.

What’s the difference between predictive and preventative maintenance?

Preventative maintenance is speculative, and doesn’t take into account real time data collected from machinery. Similar to a car’s MOT, you set a time period and decide that every ‘x’ amount of weeks or months you’ll give the equipment a review.

The problem here is that if the equipment is running fine, it will result in unnecessary downtime. On the other side of things, because it’s speculative, you may miss an issue that needs to be sorted right now.

Preventative maintenance may come with the benefits of requiring less specialised systems to operate, but when things go wrong they can be costly. At best, you have machines operating well that are shut down for no reason. At worst, you miss a fault that causes a catastrophic breakdown because you’re outside of a maintenance window when it occurs.

What are the drawbacks of predictive maintenance?

It can be expensive to set up. Traditional preventive maintenance requires relatively little specialised equipment beyond what’s used in production already. Because maintenance is carried out at regular intervals, no special sensors or data collection software is necessary.

Predictive maintenance also requires a high level of expertise in the people operating it. While the goal is to have automated systems that can keep things running smoothly, you’ll still need trained engineers to make the system run as best as it can.

What are the benefits of predictive maintenance?

Once it’s implemented and integrated, you can save significant amounts of money on downtime, optimising your use of resources. On top of that, you can potentially avoid the cost of replacing equipment that’s suffered catastrophic failure.

With automated systems keeping your machines running as efficiently as possible, the people in your business are free to innovate as only people can. You’re avoiding under utilising talent that’s tied up in rigid and potentially unproductive preventative maintenance cycles.

It’s also worth bearing in mind that these technologies don’t exist in a vacuum. With sensors monitoring the quality of your product and the state of machines, you can achieve predictive maintenance. But, that’s really only the beginning.

These technologies open the door to smart manufacturing and the factory of the future. It might start with minimising downtime and maximising output, but the sky is really the limit when you begin to adopt Industry 4.0 technologies and methodologies.