Cutting tool
Tool wear on cutting tools can be read continuously from machine and process data with IoT. Operators detect breakage, chatter and wear earlier, protect expensive blanks and have replacements to hand when a tool is used up.
Cutting tool at a glance
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Verified projects featuring Cutting tool




Monitor coolant and automate level checks




From machine data acquisition to predictive maintenance






Tool dispensing from the IoT cloud





Data-driven optimisation and seamless monitoring of milling processes








Robots as asset-as-a-service: a rental model for industry
Tool wear: detect it early and have cutting tools ready in time
In the solution examples, Schaeffler Digital Solutions links an industrial PC to the machine control. The autinityHub software reports short-term events such as tool breakage, chatter during machining or excessive tool wear, and automatically creates a maintenance order in SAP when values deviate. With Industrial Edge for Machine Tools, Siemens records not only currents and position values but also which tool was changed when and what geometry it had. In a Wandelbots testbed, a learning application in the SAP Business Technology Platform detects the degree of wear of tools on the robot head from performance data. Supply is handled by connected vending machines that report withdrawals to SAP via 4G and 5G.
The examples come from metal and electronics, automotive and mechanical engineering, as tool wear detection, quality control and inventory management. CERATIZIT, whose 1,000 Tool-O-Mat machines in 22 countries communicate with SAP, connected them to the cloud with Materna, and on-site interventions have since become very rare. With Siemens' edge apps, a milling process is first optimised virtually so that expensive titanium blanks and special tools are not lost in trials. ifm uses the io-key to monitor the coolant of a hacksaw via the cellular network so that the saw blade does not run dry and wear out.
Podcast episodes featuring Cutting tool
The Amazon for cutting tools delivers tools from the IoT cloud 24/7
Shopfloor networking strategy: Schaeffler Group creates messaging infrastructure with Schaeffler Digital Solutions
Real-time data from machine tools and cutting tools – digital twin of the machining cycle and machine learning
Tool wear: frequently asked questions
How can tool wear be detected with IoT?
Tool wear can be identified from changes in machine and process data such as currents, position values or vibration. Schaeffler Digital Solutions' autinityHub software records all operating data and sends notifications in the event of excessive tool wear or chatter during machining. The data comes from an industrial PC connected to the machine control, even on older machines from different manufacturers. If values deviate from their targets, a maintenance order is created in SAP automatically.
How does IoT-based tool breakage detection work?
An IoT system reports tool breakage by continuously comparing the machine's operating data with target values and sending an immediate notification when a short-term event occurs. Alongside long-term analyses, Schaeffler Digital Solutions' autinityHub provides automatic alerts for tool breakage and quality fluctuations. The user is informed directly, or the system automatically creates a maintenance order in SAP. No programming skills are needed for installation or use.
How does a connected tool vending machine work?
A connected tool vending machine dispenses tools on site and reports every withdrawal to the central system. CERATIZIT stocks its Tool-O-Mat machines with up to 840 products, and they are operated with an ordinary company ID card. Together with Materna, the machines were connected to the cloud: consumption data flows into the SAP system overnight via 4G and 5G, and updates and tool catalogues are sent back. Faults can be resolved remotely, for example with a reboot.
Why should coolant be monitored on cutting machines?
If coolant runs short, the tool wears heavily, on a hacksaw for example the saw blade. The tank there holds only around 50 litres, and drag-out on the material and evaporation lower the level quickly. ifm measures it with a level sensor, and the io-key sends the value via the cellular network to moneo without any existing IT infrastructure. If the level drops, warnings go to the responsible colleague by email or Teams, and inspection rounds are no longer needed.
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