Effective maintenance strategies for optimal machine performance

The different maintenance strategies

Preventative/Preventive Maintenance:

Regular maintenance work is carried out, regardless of whether systems show signs of wear or not. Although this can reduce downtime, preventative measures can be expensive and inefficient. They are suitable for systems with predictable wear, such as heating and cooling systems or certain pumps.
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Reactive/Corrective Maintenance:

This strategy is fast but expensive and risky. A recent study by Siemens (2023) shows that a failure costs companies 380,000 euros on average. For this reason, reactive maintenance is only suitable for non-critical systems such as office printers, lighting systems or smaller tools.
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Predictive/condition-based maintenance:

This strategy uses data and analytics to monitor equipment health and Predict Maintenance needs before failures occur. It minimizes downtime and significantly reduces maintenance costs. Organizations should note that this maintenance strategy requires extensive data collection and analysis, and initial investments in technology and training is necessary. Once implemented, Predictive Maintenance offers major cost savings for critical equipment and complex production environments such as conveyor belts, CNC machines, high-performance furnaces, or robotic systems in automotive production.

Predictive Maintenance with AI software of aiomatic

With aiomatic, companies can practice Predictive Maintenance by using AI and data analytics to continuously monitor the health of their assets. Our software solution serves as a digital maintenance assistant that integrates an engineer's expertise into a powerful AI system. By analyzing large amounts of data and applying advanced algorithms, precise forecasts can be made about maintenance requirements: Maintenance is carried out exactly when it is needed, minimize downtimes and maximize productivity.

The best thing about it: It doesn't take much effort to integrate our software and to benefit from our Predictive Maintenance (PdM) solution. In fact, it's just 5 easy steps before you can take advantage of our software:

Benefits of AI software displayed with icons

As you can see, the process is clearly structured and easy to implement. We support you at every stage and attach great importance to intensive exchange. In this way, you can raise your maintenance strategy to a new level and increase the reliability of your systems. Schedule a demo today to discover all the benefits of our software!

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FAQ

What are the most common challenges when implementing maintenance strategies?

The most common challenges in implementing maintenance strategies include: Inadequate data security and quality, lack of know-how, limited financial resources, and complex plant structures. Thorough planning, staff training, and investment in the right technology can help address these challenges.

How does aiomatic's AI-based software work

aiomatic's software continuously collects data from systems and carries out analyses to identify patterns and predict future maintenance requirements. This enables companies to carry out maintenance exactly when they are most effective.

Which companies can profit from using Predictive Maintenance software?

Implementing Predictive Maintenance provides manufacturing companies with numerous benefits, including reducing maintenance costs, minimizing downtime, extending equipment life, increasing equipment availability, and improving the overall efficiency of production processes.

Importance of maintenance strategies for optimizing your systems

Planned and unplanned maintenance measures

What are maintenance strategies?

The different maintenance strategies

Preventative/Preventive Maintenance:

Reactive/Corrective Maintenance:

Predictive/condition-based maintenance:

Predictive Maintenance with AI software of aiomatic

What are the most common challenges when implementing maintenance strategies?

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