Global predictive maintenance market value is expected to reach 23.5 billion U.S. dollars by 2024 — according to the latest Statista Research Department forecast. Back in 2018, the value of the market amounted to “only” 3.3 billion dollars. The compound annual growth rate is projected as high as 40 per cent!
What exactly is predictive maintenance, and why does it gain popularity at such a pace?
The main goal of predictive maintenance is to keep the cost of equipment maintenance low through
The probability of failures is reduced thanks to direct monitoring of conditions and the performance of equipment.
There are three basic types of maintenance differing in the adopted model of the procedure:
Suppose that we own and use a passenger car. One day the car won’t start. We call in assistance, which transports the car to a repair shop. A mechanic identifies the problem, let’s say fuel supply pump failure. We have to replace the broken pump with a new one. We pay for the part and the service. We applied the model of Reactive Maintenance, which is fixing equipment when it breaks. It’s the most expensive possible option.
With the car running right, we commute every day. Odometer ticks. It is time to change the engine oil. From the producer’s recommendations, we know we should do it as often as every 15 thousand kilometres. We go to the repair shop, where the filter and oil are changed. Most likely, we avoid a much graver failure of the engine. This is an example of Preventive Maintenance, which is repair and conservation based on risk analysis. This model lets us save some money. In the case of most cars, this is a method that gives satisfactory effects.
Imagine that our car could talk and tell us exactly when we should change the engine oil. It turns out that it’s not such a surrealistic vision! There are systems on the market that allow analysing the car’s vibrations and plan repairs and conservation based on this data. This kind of solution is implemented in car rentals and transportation fleets. Why? The answer is simple — it saves money.
By interpreting ongoingly supplied data, you can pinpoint the exact moment the precautionary measures will be required. Let’s say the above-mentioned engine oil we can change not every 15 thousand kilometres, but according to actual consumption every 18, 21, 14, 23 thousand and so on. These are not only less frequent changes but also minimalization of malfunction occurrence. This model is the most efficient and the most economical — we call it Predictive Maintenance.
The best solution most often turns out to be an adequate balance between preventive and predictive maintenance. How to strike this balance?
In production plants and other greater industry enterprises, a good solution is adopting Reliability Centred Maintenance (RCM). That means creating a maintenance strategy for the whole plant or infrastructure. You develop plans for every department or facility considering equipment, functions, probable failures, their effects and causes. Then, you make choices of specific tasks and precautionary measures, both preventive and predictive. To achieve that, you need to designate a person responsible for the entire process.
A trend that is also gaining more and more popularity is Risk-Based Maintenance (RBM), which prioritises threats and directs resources toward those that have the riskiest consequences. To achieve that, a risk matrix is used:
Consulting approach
RCM and RBM are a part of what we call consulting approach. It is a maintenance option in which you have business workshops where you set priorities. The advantages of this approach are that it is easy to introduce to employees and the fact that you analyse your resource. Among the disadvantages are required efforts, need of frequent updates and designation of a person managing the implemented system.
Technological approach
An alternative to this is a technological approach. Its strong points are shorter time involvement on the customer's side and a simpler process of implementation. However, this process requires well-prepared data and historical data for algorithms training. It also may be necessary to install additional sensors.
Why is maintenance organization so important after all? For several reasons like:
All of the above reasons can be shorten to the primary purposes of optimising production cost, increasing competitiveness, and maximization of profit.
Write to us to learn more about what approach will be right for your organization. With our partners such as GE Digital and Microsoft, we can build a solution tailored to your needs. We handle the entire process, from business workshops to building tools and integrating with other company systems.
