Predictive maintenance: Avoid unscheduled machine downtime

07 February 2022

Increase plant availability and ensure process conformity with smart plastic solutions from igus.

To avoid a system failure, more and more condition monitoring and predictive maintenance solutions are being used to ensure that maintenance work can be scheduled, and unplanned failures avoided. For this, systems for condition monitoring are the first development stage, and the next step towards implementing a comprehensive maintenance concept is predictive maintenance.

Conventional maintenance involves the replacement of moving components such as energy chain systems or plain bearings at regular intervals. This allows components to be replaced when they are still operational. If they are replaced shortly before they reach the end of their actual life, the service life can sometimes be significantly extended. This reduces both costs and the maintenance effort – without compromising reliability.

In these cases, predictive maintenance systems that work with IoT are valuable. They monitor the condition of the components while predicting their service life during operation. If irregularities occur (e.g. due to an accident or the presence of contaminants), the system detects these irregularities and issues a warning message. The user is then able to eliminate the unusual operating condition before major damage occurs.

Minimise service and maintenance costs

An increasing number of production plants are recognising the savings potential offered by networking machines and machine components at the data and IT level, right through to cross-company networking. Here, there are further advantages in the use of energy chain and plain bearing systems with "built-in" predictive maintenance.

All sensor data – e.g. the calculations of the individual service life and the resulting notification – can be passed on to higher-level IT systems and evaluated or documented there. This includes management execution systems (MES), zero-downtime systems (ZDT) and software for company-wide maintenance.

Smart "preventive maintenance" – with i.Cee

As an intelligent "preventive maintenance" system, i.Cee consists of three levels: sensors, hardware and data collection/evaluation. At the heart of the system is the software. It creates the conditions for an intelligent, condition-based and individual service life calculation, as well as continuous monitoring of an energy chain or plain bearing system.

The i.Cee software calculates the service life of the component based on the load. When the operation or software is started, the service life is compared with the algorithms of the current online service life calculator. The recorded environmental and movement data is applied and the double strokes and/or kilometre readings are transferred to the software. It converts the data to life in days. This results in the service life up to the recommended replacement, assuming the anticipated movement data with 24/7 use and constant impact of the maximum environmental data.

Learning software

When commissioning the i.Cee System, the "worst-case scenario" is assumed based on the predicted service life. During operation, the system records the actual loads of the application, e.g. intermittent operation and pauses/interruptions as well as temperature fluctuations, vibrations, lateral accelerations, chemical influences and abrasive media. On this basis, the remaining service life is continuously recalculated – assuming the actual motion and load profile for further operation. If an i.Cee:net is used, the online service life calculators of the components used are regularly queried at the same time and the display of the remaining service life is adjusted accordingly.

When using i.Cee:local without an internet connection (see diagram), if there is a serious deviation in the movement and environmental data, a temporary, manual query is requested from the customer's system in order to adapt the service life calculator to the actual conditions.

Sensors record real operating data

Abrasion and wear sensors, which are installed in or attached to the igus products used, ensure a further comparison with the real conditions to which the respective igus product is exposed in the application. The sensors transmit information on the percentage lifetime status of the polymer components subject to abrasion. This sensor information "overwrites" the given calculations, so that the forecasts become increasingly more accurate as the operation progresses and change from a "worst-case scenario" to an adaptive, learning scenario.

Provide inspection proposals and real-time information

Based on the calculations shown above, the customer receives information on the maintenance recommendations provided by the empirical values gathered over several years in the field of energy supply and bearing technology. Both the above-mentioned sensors for service life calculation and the i.Sense sensor units for condition information provide data from which, in many cases, indicators for premature wear of the product or the risk of product failure can be determined at a very early stage.