Industry 4.0 refers to the intelligent and permanent linking and networking of machines and autonomous machine-driven processes in the industry. Also, today’s cable production process is characterised by an increasing level of automation. Intelligent measuring devices continuously measure and transmit measuring values as well as information on the device status via Industry 4.0 interfaces like OPC UA, to control units and to the plant control centre without the need for personnel support. There, the data is processed automatically for immediate production control and process optimisation. Besides, the information is used for preventive maintenance. SIKORA, manufacturer and supplier of innovative measuring and control technology explains how measuring technology is related to Industry 4.0 and how it supports autonomous manufacturing in the future.
Data exchange with IT systems via OPC UA and reproducible quality
Measuring gauges installed in a cable production line continuously supply real-time measurement data, e.g., the cable diameter and ovality to the line control of their production sites. These in turn send production data to a central computer accessible to the entire group of companies and thus lead to reproducible quality in all production sites of the company group. This data exchange is achieved by standardized interfaces like industrial ethernet-based field busses or OPC UA and remote services via the internet can be used for firmware upgrade and audio/video interaction with the user at the remote site.
If the cable is out of specifications, the operator receives a signal to automatically control the line by modifying line speed or extruder rpm to control to the nominal value. The more and precise measurement data available, the faster and more reliable conclusions can be drawn, and the process optimised. The measuring devices are, therefore ‘Industry 4.0 ready’ and ideally suited for use in modern cable production lines with increasing levels of automation.
Remote maintenance
In addition, the measuring system is used for location independence maintenance via remote internet access. Being able to look directly into the device at any time, from anywhere in the world, and get information about the device condition, the operator can optimise the processes. The measuring sensors collect status information via diagnostic program. Thus, SIKORA service personnel have the possibility to draw conclusions on possible error causes and/or to give the customer advice for maintenance, e.g., the gauge head is dirty and has to be cleaned. Remote access via Internet is possible to make software updates and run diagnostic software.
Future: Preventive and predictive maintenance
Looking into the future, technological developments link Operational Technology (OT), e.g., what happens locally in the production line such as material consumption, with Information Technology (IT) and enable the historical collection of data, even across plant boundaries. Here we will introduce the term preventive maintenance, which derives information from the diagnostic program and the experience of the service technician. This maintenance program is based on location-independent diagnosis for the highest availability of the devices. For example, the operator received every 3 weeks an error message with the note to check the cleanliness after 2 weeks. As a result, the operator cleans the laser device every 2 weeks, so that no error occurs.
In contrast, predictive maintenance means that the operator knows that something is going to happen, so he can take care before something happens. For example, a diameter gauge head can give dirtiness alarm. At a next line stop the gauge head can be cleaned. Thus, cleaning can be done if needed, aside from specified intervals.
In sum, by implementing measuring and control technology in cable production lines SIKORA allows their customers to have mobile access to product parameter data, control measuring values and trace quality problems back to errors in the extrusion process. Moreover, it offers location independent maintenance by using intelligent software technology. This all contributes to autonomous manufacturing for optimum processes and the highest efficiency.
