Industrialization started with the steam engine, and over the decades we have now entered the fourth round of industrialization. Machines are intelligent and cross-linked to each other. Information is collected in real time and processed and evaluated via artificial intelligence (AI).

One of the primary tasks in Industry 4.0 is to further increase machine availability and output quantities based on digitization solutions. Collecting, saving and evaluating various machine and system data as well as creating a digital twin are the prerequisites for comprehensive maintenance concepts. Data is the resource of the future. An optimized, condition-based maintenance strategy requires permanent monitoring, also known as condition monitoring. The intelligent and communicative protection and power distribution solution of the REX system (fig. 1) helps collect data in a targeted way for the DC 24 V range - the heart of each automation solution. 

Fig. 1: The intelligent and communicative protection and power distribution solution of the REX system helps collect data in a targeted way for the DC 24 V range – the heart of each automation solution.

What maintenance approaches do we know today?

In general, we differentiate two main maintenance approaches. In addition to conventional maintenance in the event of a failure, machine operators are increasingly using planned maintenance approaches. At first glance, reacting only in the event of a failure seems easier and is also supposedly the more cost-saving method. But if you look more closely, unexpected downtimes may quickly lead to very high costs. Comparably longer downtimes due to more difficult troubleshooting and the current bottleneck for spare parts in the procurement market have a massive influence on the choice of the maintenance strategy.

We differentiate three main approaches of planned maintenance, which is the prerequisite for increased machine availability (fig. 2).

• Preventive Maintenance is the easiest solution mainly based on empirical values and specified maintenance intervals.
• Condition-Based Maintenance primarily works with current measuring data. The machine condition is permanently determined and monitored. Condition monitoring systems provide all essentially needed target and actual values. In case of a deviation, a message is issued.
• Predictive Maintenance combines both previously mentioned maintenance approaches and calculates a forecast from a multitude of different data and empirical values using AI. The supreme discipline of the system is the forecast on which components fail and when. The result is used to precisely plan maintenance tasks and derive a specific maintenance strategy.

Fig. 2: Planned maintenance is the prerequisite for increased machine availability. Condition monitoring systems provide measuring values and data.

Artificial intelligence, the Industry 4.0 flagship

Artificial intelligence (AI) means all applications where machines or computers perform humanlike intelligence tasks, also including machine learning. It is not supposed to replace human personnel with machines, but to simplify the daily tasks in a meaningful and supportive way by providing such technology.

Important! There is not only "one" AI, but strong and weak AI. Strong AI should be similar to human intelligence or even surpass it, which is still a dream of the future. A weak or methodical AI processes a specific problem, why it is mainly used for process automation, for image and voice recognition and processing.

In the industrial area, machine maintenance is often done preventively in order to keep downtimes to a minimum. Machine components subject to wear and tear are replaced in determined intervals to prevent failures. This strategy does not efficiently use the component's typical life, which makes it quite costly.

Therefore, more and more machine operators prefer using planned maintenance concepts to decrease maintenance costs by using special Condition Monitoring systems. These systems permanently monitor the machine condition and provide the necessary data for planned maintenance by detecting the actual degree of wear and tear. This helps plan maintenance actions for the end of the typical life and decrease maintenance costs.

Using intelligent Condition Monitoring solutions offers some benefits. Improved process stability leads to increased machine availability and to an increased output quantity. Early detected deviations or determined wear in applications are prerequisites for a sustainable optimization of all maintenance actions.

Digital protection with Condition Monitoring

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