There are many reasons for the formation of myths about maintenance and servicing: rapid technological progress and digitalization result in highly specialized machinery that has to fit into a networked environment. The lack of trained personnel, growing data volumes and the associated increase in security standards and compliance also increase the workload in companies. And competitiveness and cost pressure hang over everything like the sword of Damocles.

"Although the optimization of various processes can mitigate the challenges facing the industry, a number of prejudices remain. They lead to maintenance and servicing being regarded as marginal issues and neglected. We need to overcome this, debunk myths and thus ensure a long-term increase in the efficiency and reliability of machines and systems," says Jan Pakusa, Product Manager Power Supplies / Test & Measurement at Reichelt Elektronik. Pakusa lists the following five myths:

1. maintenance must only be carried out as troubleshooting

Maintenance should take place regularly as part of the maintenance process. Predictive maintenance (preventive maintenance) forecasts future maintenance requirements. Sensors in the machines and systems collect data at a central location, for example on a cloud platform, where it is subjected to comprehensive analysis using algorithms and AI. By identifying potential problems at an early stage, downtimes can be minimized, efficiency increased and the service life of a machine extended. This helps to ensure the smooth operation of critical systems.

2. maintenance only causes expenses

Exactly the opposite is the case: effective maintenance and servicing leads to improved system availability and overall efficiency. Failures and expensive repairs are avoided and the continuous functionality of the system is ensured. The service life is extended and it is therefore less often necessary to purchase new hardware. Well-maintained machines work more efficiently and consume less energy. The costs for this and also the ecological footprint are reduced. The quality of the products manufactured or services provided is maintained, which promotes customer satisfaction. Potential risks for employees and the environment are reduced and safety standards are adhered to.

3. digitized machines or systems require no maintenance

Despite their advanced technology, digital machines and systems require just as much regular maintenance as conventional machines. The physical components are still subject to wear and tear, and software and algorithms require updates. Sensors and hardware are exposed to various environmental conditions, such as high heat, and therefore need to be checked. This early detection of problems ensures the smooth, safe operation and long-term performance of the technology.

4. no trained personnel required for maintenance

Complex machines and systems require specific expertise in order to maintain them safely and effectively. Trained personnel understand the technical details, operating processes and necessary safety guidelines. They can assess and recognize potential problems at an early stage, apply appropriate maintenance procedures and carry out any repairs correctly. Without the appropriate expertise, there is a risk of errors, improper handling or even accidents, which can lead to breakdowns, increased costs and unwanted business interruptions.

5. production is at a standstill during maintenance

Efficient maintenance work on machines and systems without extensive production downtime requires detailed planning and the use of targeted strategies. This includes

-Schedule maintenance windows during low utilization times

-Carry out individual repairs to specific components during operation

-Use parallel systems and redundancies

-Apply maintenance techniques such as in-place repairs

-train specialized maintenance crews

Implement real-time monitoring systems for early problem detection

"German industry can overcome the growing challenges in maintenance and servicing by investing in targeted training on the one hand and the latest technologies on the other. The training courses provide employees with the necessary specialist knowledge as well as the handling of highly specialized systems. AI and machine learning ensure efficient processing of the growing volumes of data and are able to make precise predictions for maintenance requirements," summarizes Pakusa