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Predictive maintenance: recognising disruptions before they occur

Predictive maintenance
Process monitoring, Condition monitoring, Breakdown monitoring

 

With Christian Maier GmbH & Co. KG on the way to the Digital Factory

Digitalisation, Industry 4.0, Smart Factory and Predictive Maintenance – various challenges that the maierGROUP are currently facing with. Since 2017, Christian Maier GmbH & Co. KG has been developing and researching intelligent rotary joints. After the successful patent grant (in 2019) for the LinkC, the core of the sensor solution, the intelligent rotary joints was presented to our customers for the first time at the K show in 2019. Subsequently, the first pilot project with state-of-the-art sensor technology in the rotary joints for real-time measurement started at Lacom.

In 2020, we won the Ostwürttemberg Innovation Award. Step by step, we are implementing our innovations. Our goal is: the ability to maintain machines and systems in a predictive, i.e. proactive, manner in order to minimise downtimes and malfunctions or, at best, even avoid them completely. On top of that, we offer them the safety of their turning operation and they can monitor their entire process.

KI prevents machine breakdowns
Together with the university of applied sciences in Aalen, we are working on the latest research results on a test stand that is designed to reduce unplanned machine breakdowns and prevent lengthy maintenance processes. The aim is to use artificial intelligence to recognise the condition of certain components and predict imminent failures. The test stand is equipped with many sensors that provide data on temperature, pressure, speed, wear, torque, leakage, temperature and wear to the rotating union. In order to examine four mechanical seals simultaneously, the test rig has been running continuously since March. This allows the wear behaviour of a rotating union to be recorded realistically over various process parameters. For the evaluation, the data is fed into an artificial intelligence that learns from the interrelationships of the individual parameters. The goal is for the rotating union to become a smart element of an entire plant. Through the AI, the machine states and irregularities are to be recognised in real time, and imminent failures are to be foreseen. The project is funded by the “Central Innovation Programme for SMEs” of the Federal Ministry for Economic Affairs and Energy.

 

Prüfstand _Christian Maier GmbH & Co. KG
Test bench of Christian Maier GmbH & Co. KG at Aalen University

 

 

 

 

 

ZIM projekt

 

Secure your lead with intelligent rotary joints

With our new sensor technology, we help our customers to improve the economic efficiency of their plant. Our sensor solution offers manufacturer-independent compatibility through IO-Link. Unplanned downtimes are largely prevented by predictive maintenance. They provide reliable process data at all times. This allows optimisation potentials to be recognised and implemented. Conversely, energy and CO2 are saved. Continuous monitoring of the rotating union improves machine safety, making torn hoses a thing of the past.

 

We look forward to the next steps with you.

Mr Manuel Schöferle (Manuel.Schoeferle@maier-heidenheim.de) and Mr Markus Scharting (Markus.Scharting@maier-heidenheim.de) will be happy to assist you.

 

Newspaper reports:

Schwäbische Post | Freitag, 02.07.2021
Wie Maschinenausfälle verhindert werden können

 

Aalener Nachrichten | Montag, 07.06.2021
Tag der offenen Tür: Wissenschaft digital erleben

 

Presseinformation Hochschule Aalen, 18. 05.2021
Mit KI Maschinenausfälle verhindern