Industry 4.0 envisions the smart factory of the future

Related Vendors

GF Machining Solutions Mikron Agie Charmilles AG

Building on existing intelligence

If that all seems like a giant leap from the First Industrial Revolution of the 18th and 19th centuries when rural societies in Europe and North America became industrial and urban, that is because it is.

Industry 4.0 builds on that milestone period as well as the Second Industrial Revolution of the late 19th and early 20th centuries when advancements in manufacturing and production technology enabled widespread adoption of preexisting technological systems, and the late 1950s to the present day Third Industrial Revolution change from mechanical and electronic technology to digital technology.

In the machine tool industry, Industry 4.0 is also about extending existing system intelligence into adjacent systems and, from there, into complex manufacturing systems where the machine manufacturer, the suppliers and the owner may be constantly connected for providing remote service and process improvements. GF Machining Solutions’ R-Connect, the machine tool industry’s most in-depth remote machine tool analysis, is a good example, Perez states. The technology demonstrates how manufacturing’s digital transformation is creating opportunities for manufacturers to increase their machine uptime while operating in the best condition.

The first phase of R-Connect, Live Remote Assistance, allows customer-authorised remote assistance and connects the customer in real time with the local diagnostics center and GF Machining Solutions plants in real time. It allows remote inspection of the machine tool with diagnostic performed by a technician or the customer. Any resulting maintenance is performed on site by a service engineer.

“In the near future, R-Connect will be a bridge to technologies that could, for example, predict the lifetime of machine components and consumables,” Perez says in summary. “In line with Industry 4.0, R-Connect is just one more step toward eliminating process downtime, improving machine performance, and ensuring a fully predictive manufacturing process and product quality.”

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