Predictive maintenance: definition, benefits, examples ... all with one click!

► What is predictive maintenance?

Predictive maintenance generally refers to the early anticipation and prevention of faults in machine equipment or components thanks to information on their condition. This is achieved using data-based methods that analyse the condition of your machines and help to predict malfunctions, faults and the timing of necessary maintenance work.

► Is there a difference between "predictive maintenance" and "smart maintenance"?

No. Both terms are now used synonymously in the Industry 4.0 terminology. The following terms are also synonymous:

• predictive servicing
• forecasting maintenance

For the sake of simplicity, the umbrella term "predictive maintenance" will therefore be used in the following.

► What does predictive maintenance have to do with Industry 4.0?

Industry 4.0 promises greater efficiency in production through networked machines as well as insights from data analyses and improved machine availability. In this context, predictive maintenance, i.e. a condition-based maintenance process based on the analysis of process and machine data, is a key component.

► What is the aim of predictive maintenance?

Unplanned downtime of production equipment costs money and cuts your profits significantly in the long run. What is certain is that machine and system failures pose a serious threat to the industrial sector. Predictive maintenance should lead to cost savings compared to preventive maintenance processes based on routine, interval or time, as work is only carried out when necessary.

► What is needed?

First of all, various sensors are needed to record functionally relevant data on the machines, such as speed, temperature, noise, bearing vibrations or power consumption. Next, a combination of real-time analysis technology and a database is required to interpret and meaningfully analyse the sensor data. If all this is successful, it will be possible to rectify the machine problem before it actually arises.

► Is predictive maintenance only for traditional MRO companies?

No. Predictive maintenance is not only interesting for the manufacturing industry or associated MRO areas (Maintenance, Repair & Operations), but also for all mobility services - whether in the air, in vehicles or on rails. 
It is usually worthwhile for companies that frequently use the same type of machine or do not want to use predictive maintenance for their own production, but for the machines they sell.

►How can I get started right away?

Collecting and analysing machine data is central to this type of intelligent maintenance. The data can be used to calculate the optimum time for maintenance in order to avoid malfunctions. Machine data is usually recorded using sensors attached to the machine or system component, often aptly called predictive maintenance sensors. In the igus energy chain, this job is performed by the i.Sense condition monitoring sensors from smart plastics. This intelligent sensor technology continuously records the various operating states of the energy supply.

► What other data is required for the most accurate possible maintenance forecast?

The prerequisite for the most accurate possible indication of fault-free running time is that information on usage is as accurate as possible. This includes information on the place of use with weather conditions and temperatures, distances covered, number of cycles, etc. Thanks to the knowledge acquired in the igus test laboratory and the current condition data, igus is able to predict the service life data precisely. A necessary replacement of a component is then indicated in good time and enables planned and resource-conserving maintenance.

►Do you always need new software or IT tools?

The prerequisite for predictive maintenance is that the machines are networked, i.e. all machines provide their data for storage and analysis in a database. This is ensured with an OPC UA protocol.
With the igus i.Cee solutions for predictive maintenance, however, no additional systems or hardware are required. All the necessary data is provided via the associated i.Sense sensors and the special AI algorithms are implemented in the i.Cee module. And the associated i.Cee dashboard can be accessed with any standard PC.

► What other maintenance strategies are there?

In its DIN EN 13306 - Terms and definitions of maintenance, the German Institute for Standardisation defines a maintenance strategy as a procedure for achieving maintenance objectives, such as maintaining a specified condition or extending the life expectancy of a machine. A distinction is usually made between the following three different approaches:

• Reactive maintenance strategy / Damage-dependent maintenance strategy
• Preventive maintenance strategy
• Predictive maintenance strategy

► What characterises reactive maintenance?

With the reactive form of maintenance, damage to machines is repaired and production parts are replaced only when there is an acute problem. This means that companies have to react quickly in the event of damage in order to be able to continue production as quickly as possible and avoid high downtimes and costs. Most often, this strategy is used with machines that don't need to be repaired often or that can be repaired or replaced cheaply.

► What is the difference between preventive and predictive maintenance?

Preventive maintenance is a maintenance strategy in which measures are carried out at certain intervals. These can be based on time or quantity. In other words, you do not wait until systems or machine parts break down, but systematically carry out preventive inspections and maintenance measures. The actual degree of wear and tear on the machines and systems is irrelevant. In predictive maintenance, on the other hand, process and machine data is recorded, stored and subsequently analysed during operation using sensors and interfaces.

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