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Predictive maintenance with IoT software

AI software for predictive
maintenance measures

Real-time machine insights

Detect anomalies

Predict failures

Analysis of the cause of the fault

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Cost savings

Reduce maintenance costs & extend machine service life

Assistance & security

Real-time insights without maintenance personnel

Easy integration

Seamless integration into existing systems

Scalability

Algorithm can be extended to other machines

Typical challenges in the industry

Machine maintenance is a major challenge for businesses - especially when undetected faults suddenly lead to production stoppages and delivery delays. Reactive maintenance, which involves repairing or replacing components, leads to long downtimes and bottlenecks for maintenance personnel. Even regular preventive maintenance does not solve the problem: it often wastes resources and causes unnecessary costs.

The solution: predictive maintenance

Predictive maintenance offers a solution to this challenge by acting like a preventive health check for machines. It uses data analysis and machine learning to predict potential failures at an early stage. This enables companies to identify and schedule maintenance needs in advance, resulting in reduced downtime, optimised use of resources and lower overall maintenance costs.

The advantages of predictive maintenance

Longer machine service life

Optimised use of maintenance staff

Reduction of downtimes

Greater operating efficiency

How does predictive maintenance work?

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5 steps to predictive maintenance

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From needs analysis to implementation and continuous optimisation - we support you at every step of your predictive maintenance project.

Maintenance software from aiomatic

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Real-time analysis of sensor data

Clearer assessment of health status

Analysis of the cause of the fault

Visual analysis to identify the main causes

Possible applications of the predictive maintenance software from aiomatic

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Infrastructure

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Medical Technology

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Energy

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Mobility

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Chemistry

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Pet food

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Metal plants

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Tools

Requirements for predictive maintenance

Secure and scalable data infrastructure

Reliable sensor data that allows conclusions to be drawn about the condition of the machines

Powerful analysis software

Frequently asked questions

Here you will find answers to the most frequently asked questions about predictive maintenance and our software solution.

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