When it comes to the optimization of production processes, the Internet of Things opens many new possibilities for industry companies. Industrial IoT does not only allow easier and more efficient device and machine control, it also allows for easier analysis. Thanks to predictive maintenance, errors and wear can be recognized before a machine fails. This manufacturer shows from practical experience how IoT efficiently and smartly automates production, processes and maintenance.
Machines must function without flaw. While this applies to the single coffee machine in a café, it is even more important in the case of large industrial companies, where a number of complex production processes are interlinked. Failure of a machine can even lead to complete process standstill. It is therefore ever more important for industrial production to be able to predict the right time to change expendable materials and parts subject to wear. Too early leads to higher costs and resource intensive – too late is fatal.
Up to now, many companies were flying blind. Analogue data was the only way to know if a machine required maintenance – service records and information on wear and tear could only be estimated. The actual condition of a machine is a Black Box. On the one hand, this can lead to service and maintenance being carried out more often than required, and on the other, machines can fail because their defects could not be predicted in advance. This leads to time-consuming repairs at a cost to the entire production process. The result: Higher costs and disruptions in the production process.
This is where the Internet of Things comes into play – shining light into the Black Box – in other words, industry companies are now finally able to gain a transparent overview of their machine data. Thanks to intelligent use of this sensor data, M2M communication and the efficiency of learning machines can be improved with the help of IoT / IIoT.
Nowadays, application ranges are becoming more and more specific and at the same time more versatile: Intelligent condition monitoring and remote services allow production processes to be supervised remotely and even remotely controlled. Service technicians are no longer required on-site in the machine hall in order to determine and repair problems in the production process. Technologies such as augmented reality even allow a plant to be viewed through the eyes of the machine operator.
Thanks to the data generated, precise reports can be created detailing machine or device status. Data analysis and predictive maintenance also allow precise predictions on wear and tear and potential failures. In other words: lower failure rates and trouble-free production processes, flexible monitoring and potential for new data-based business models.
Uses for IoT / IIoT don’t end at the factory gates. Sold together with the machine or plant, IoT solutions represent strong added value and additional service for the customer and can be used as a strong competitive advantage over the competition.
Finetool International Holding AG, a leading provider of fine-blanking and forming technology, provides an example of how Industrial IoT is successfully implemented in practice. For its presses and production lines, the Swiss market leader required an IoT solution combining intelligent condition monitoring and predictive maintenance and, together with Device Insight, a monitoring and analysis platform was created in the matter of a few months based on CENTERSIGHT – “FEINmonitoring”.
In order to be able to read machine data, a special mobile gateway was installed in the control unit to gather operating data from one or more presses or fine-blanking systems, process this data in advance and then send it to the cloud-based IoT platform CENTERSIGHT. Possible errors and alerts are then displayed in the dashboard in real time. Service technicians have universal access to the data and can, thanks to the remote service function, be connected digitally. In other words, personnel-intensive inspections are a thing of the past.
Get deep insights into the Industrial IoT solution FEINmonitoring in our case study.