Digital transformation Cloud platform and inline quality control: The internet of tool twins

A guest post by Hufschmied Reading Time: 5 min

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Digitisation efforts in metal cutting manufacturing tend to come from machine, control or software providers. This time, a tool manufacturer is presenting new approaches to process optimisation: Hufschmied Zerspanungssysteme offers acoustic inline quality control and an associated cloud platform.

The Sonic Shark in-line acoustic quality control system can store and share its data on the CEW cloud platform.
The Sonic Shark in-line acoustic quality control system can store and share its data on the CEW cloud platform.
(Source: Hufschmied)

To optimise tool use, Hufschmied has opened a secure cloud platform hosted in German data centers for data exchange Under the name Cutting Edge World (CEW). It complements the Sonic Shark quality control system introduced last year. The background: Both offerings together bring a concept to market that Hufschmied Zerspanungssysteme developed together with the University of Augsburg, BMW and other stakeholders as part of the MAI ILQ2020 project.

Sound differences in the ongoing cutting process give experienced machine operators conclusions about the process. They can hear when a tool is worn, or a blank has a defect. However, because it is not possible to have such a machine whisperer present in every shift and on every machine on the shop floor to hear problems at an early stage, Hufschmied has developed an expert system called Sonic Shark. It uses acoustic deviations from the learned reference state to indicate defects in the production process at an early stage. The company is known for its material-optimised tools — for example for CFRP and GFRP — but has also demonstrated many times that machine parameters, tool paths and tools must be brought into harmony with the material and the workpiece in order to optimise the process. Hufschmied has researched how this harmony sounds.

Structure-borne noise and learning software

Depending on the size of the workpiece for which inline quality control is to be implemented, one or more structure-borne sound sensors are attached to the workpiece. A computer next to the CNC machine collects the sensor data. In the first step, it is necessary to train the adaptive software. To establish a reference acoustic, it registers the noise generated when the workpiece is machined with a new tool under optimal conditions. The system creates a sensor database that serves as a reference for comparison down the road. This target data is then compared with the actual data of the respective machining operation, related to the machining process via the machine data, evaluated and visualised on a screen. If deviations beyond defined threshold values occur, a warning is issued.

In practice, the signal curves of the machining processes do not have to be laboriously taught per tool, because Hufschmied also supplies the individual sensor target signals for its tools right away based on the application data and guidelines for tool use (cutting values, speed, feed, etc.). The digital file with this information can be retrieved by the user from the CEW platform via the QR code of the tool.

Find errors early on

By monitoring structure-borne sound, conclusions can be drawn about a whole range of aspects via typical frequency bands: Tool condition, drive, clamping and milling strategy indicate changed conditions through deviations in the sounds. A direct advantage is the detection of signs of wear on the tool. Normally, companies qualify tools in tool life tests and define safety reserves. This reserve is often chosen very generously to avoid quality problems or interruptions to ongoing production. Hufschmied estimates that on average about 40 percent of the tools qualified in this way could have run longer. Tests have shown that Sonic Shark reliably detects wear right down to signs of tool breakage and cutting edge fracture. The control system predicts tool lives with inaccuracies of only ±3 percent. In practice, this means that real-time monitoring reduces the risk of scrap that would result from a prematurely worn tool. At the same time, tools can be used longer without risk and still be changed in good time.

Cloud platform for data exchange

Sonic Shark provides meaningful data on tools and processes. To ensure that this data is not only available locally, Hufschmied has set up the Cutting Edge World (CEW) cloud platform. The option of using this for documentation is also open to users who do not (yet) use online quality control. The reason: Hufschmied also feeds CEW with data. As a result, the user has a database of all the tools they use and can, for example, note down the tool life and processed materials here in order to learn more about the behavior of the tools over time. But the CEW is much more than a storage location for process data. The platform is also used for data exchange to optimize tool use.

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Digital Twin

Hufschmied's detailed quality control with a refined measuring process at more than 90 measuring points of the cutter contours already benefited users of selected tool groups with gauge block labeling in the past. Now the manufacturer is making the gauge blocks and dxf data of every single tool delivered available to interested users in the cloud — a barcode on the tool enables access. Hufschmied customers can retrieve the measurement log via barcode and cloud platform, saving them the hassle of incoming inspection. They also receive a digital twin of their current individual tool - referred to as a tool instance on the CEW platform — which they can use in CAM programming and machining simulations, for example.

Hufschmied uses the cloud location to share tool data, and users can also share tool life and logged process and machine data — between plants, with the tool manufacturer, with material suppliers or machine builders. Those who study the behavior of their machines and tools with certain materials and shapes avoid problems early on and need fewer safety reserves. Sharing these insights with Hufschmied gives the tool manufacturer valuable insight into the life of the products after they have been shipped. The important feedback for his quality control then allows the manufacturer to be even more specific about how to use the tools best.

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Sharing data for process optimisation

The data on the CEW platform is strictly private. External access to data in the Hufschmied cloud must be explicitly authorized in each case. Just as Hufschmied sets a check mark in the system to make additional tool data available to a customer, customers can, for example, release anonymized cutting data, or also store only tool life and processed material for a tool instance. Project rooms can also be set up on the platform for more intensive collaboration in process optimisation. An additional safety aspect besides granular sharing is the fact that cut data, Sonic Shark log and information about the processed material together are very informative for process optimization, but do not allow any conclusions to be drawn about the 3D data of the workpiece. The ability to use shared data to jointly improve machining processes is already being used by a major automotive customer. Another example of its use is a current project in which Hufschmied is carrying out trial machining of a sophisticated CFRP component for a customer. Thanks to digital twins of component and tool, Sonic Shark and machine data in the CEW cloud, this is a completely digitized optimisation project that can be tracked remotely. You could say: IoT now also stands for the Internet of Tools in machining production.