Fast, problem-free automated production is essential in modern-day factories. Predictive maintenance based on the Industrial Internet of Things (IIoT) is the key. It enables businesses to optimise their production availability, improve their delivery capability and perfect their products.
If a company’s production facilities operate as intended, it can manufacture the planned quantities, provide the promised services and reliably meet delivery deadlines. Perfect machine maintenance ensures all individual parts and components are in the best possible condition and there are no unexpected interruptions in the production process. This is a key prerequisite for maximum profitability in industries where high system availability is a must, such as the energy and automotive sectors. But when is the right time to carry out production plant maintenance? This used to be based solely on experience, estimates and fixed maintenance intervals. Now, however, it is possible to use digital resources to determine the ideal timing – accurately and in line with requirements. Predictive maintenance of machinery is an integral part of an Industry 4.0 production environment and enables faults to be predicted before they actually occur. Based on cutting-edge sensor technology and precise data analyses, this new maintenance model saves money by preventing unscheduled downtime on production lines and costly repairs.
Turning guesswork into knowledge is the promise that makes predictive maintenance a visionary guardian of your production facilities. For the first time ever, digital solutions now make it possible to anticipate maintenance requirements. Predicting when a part needs to be replaced means preventive measures can be initiated before the relevant component fails. Prescriptive maintenance takes this to the next level by also providing the appropriate solution to an anticipated problem. If the prescriptive maintenance system identifies a machine malfunction that is likely to occur in the future, for example, it autonomously indicates the correct measures to rectify the problem – a helpful aid for service engineers. Machine and environmental data, such as temperature and humidity, needs to be recorded and evaluated using detailed analysis for this type of predictive maintenance – not a problem in an Industry 4.0 production environment. Predictive maintenance simply uses the data continuously recorded by sensors on smart devices for this purpose. Networks transmit these measurements to the IoT platform for comparison with the data from the digital twin – the virtual representation of the actual object. The result of this comparison supplies appropriate maintenance information.
The more data is recorded, the greater the detail of the big data analysis evaluating a machine’s behavior and the more accurate the predictions. In most cases, the Industrial Internet of Things (IIoT) provides the basic network technology for data transmission. If a high-performance edge data center is also used, the relevant data is filtered out and forwarded to a cloud platform for further analysis. This reduces the volume of data and thus the time required to analyze it. Faults or even total failures are minimized far more effectively than with reactive maintenance, which is only initiated once malfunctions have already occurred. Predictive maintenance also clearly has the upper hand over maintenance work at pre-defined intervals. The advantages are plain for all to see. Production continues, the management of spare parts improves and unnecessary costs are eliminated – all benefits that pay off.
Rittal is actively driving the development of predictive maintenance concepts. All products and services required are available – from smart sensors, enclosure monitoring and intelligent cooling solutions through to smart service concepts and computing power from the cloud. Rittal Smart Service combines IIoT-enabled products and sensors for intelligent maintenance with equipment from the new Blue e+ generation. Remote diagnosis improves companies’ machine availability by giving them prompt access to the expertise of Rittal as the manufacturer.