New survey by reichelt elektronik shows that European business is increasingly confident in the future of predictive maintenance technologies
Industrial machines used during production are becoming increasingly smart, whether that is due to new equipment purchases or through the upgrading of existing machines. A new survey commissioned by reichelt elektronik has demonstrated that predictive maintenance is becoming increasingly established across European industry.
Equipping or retrofitting industrial machines with sensors can provide companies with vital measurements that ensure for smarter production. One of the most profitable uses, and part of the often mentioned Fourth Industrial Revolution, is predictive maintenance. This allows for maintenance to be based on the actual conditions of machines who self-report their current condition. The survey by reichelt shows that this technology is already widespread in European companies and will be used even more widely in the future.
Predictive maintenance is already improving production
Predictive maintenance is already being used by the vast majority of respondents: In fact, 83% of European decision-makers confirm that they already use the technology. Predictive maintenance has evolved past test cases and is now used as a core part of production. On average, the procedure is applied to almost 60% of the machines in each production system. More than a third (38%) state that they use predictive maintenance processes for the majority of their machines (60-99%).
When asked about the biggest advantages of the technology, European decision-makers mentioned an increase in the quality of production (38%) and the ability to avoid machine downtime (43%).
Predictive maintenance will soon become mainstream
Production improvements are already convincing businesses to invest more in predictive maintenance. Reichelt’s survey found that 56% of respondents would like to expand the amount they use the technology in production. Among the European companies surveyed, 24% plan to adopt more predictive maintenance in the next 12 months, while 32% say their plans don’t kick in until after 2021 ends.
The trend towards retroactive installation of sensors is also evident: Almost a third of the companies (32%) already own production facilities that are equipped with predictive maintenance functions, but 42% have had to upgrade their machines with new sensor technology or network technology.
When asked about the future, respondents said they expected predictive maintenance to be the norm for all industrial production machines in the next 10 years.
How predictive maintenance is used by companies
Today, sensors from industrial machines are mainly used to collect data on the following variables:
- Temperature (58%)
- Operating time (51%)
- Rotational speeds (45%)
- Pressure (45%)
- Vibration (32%)
“With the help of algorithms, these measured values can be used to calculate the wear and tear, as well as the probable failure of a machine. Companies can then time maintenance precisely so that components are not replaced weeks or months early,” explains Tobias Thelemann, Product Manager at reichelt elektronik. “This process has traditionally been done at regular intervals (e.g. annually), but with predictive maintenance, this can be done instead only when needed, saving time and money.”
Reasons for upgrading to predictive maintenance
Given these potential time and cost savings, it is not surprising that the most cited reasons for investing in predictive maintenance are as follows:
- Avoidance of production downtime (43%)
- Improved ability to plan maintenance work (37%)
- Increased efficiency in production (37%)
Introducing a new technology into a business however still comes with challenges. Specifically, companies surveyed said they struggled with choosing the right solution or product (34%). Similarly challenging are budget constraints (31%), a lack of understanding in the workforce (28%) or the inability to properly evaluate the data (28%).
Importantly though, reichelt’s survey found that predictive maintenance based on real data is seen as an essential part of the Fourth Industrial Revolution.
Image rights: reichelt elektronik
