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Learn MoreTool life is a critical component of CNC machines. When managed well, it can result in greater productivity, higher quality, less scrap, and significantly less downtime.
Monitoring tool life manually is problematic; it requires an operator to complete an inspection and capture data. Most modern equipment uses software in a tool life management system to measure and control the micro and macro variables required for long tool life.
Tool life monitoring uses machine data to assess the health of a tool and gauge its lifespan. Data is collected from sensors that monitor the tool group when a machine changes to the next tool. This data is sent to a software program or cloud-based machine data platform, where it’s analyzed to predict the condition and lifespan of a tool.
These programs also consider the type of cutting, jobs, and job lengths that impact tool life. This provides operators with the information they need to get the most life from a tool before discarding or sharpening is required.
There are several methods of tool monitoring. Basic tool monitoring centers around traditional preventive maintenance strategies, in which tools are replaced according to established guidelines or OEM recommendations. This process is heavily reliant upon manual measurement and visual observations.
The second method uses waveforms generated by the amplitude of power signals as the machine and tools perform their tasks. By reading these variables, operators can tell when a tool is close to the end of its life. The method isn’t predictive or effective in the prevention of downtime.
The most accurate measure of tool life occurs when it’s part of a machine data platform like MachineMetrics, which uses high-frequency machine data to measure tool life precisely. This use of real-time data and advanced analytics extends tool life while reducing downtime and scrap.
To put it in plain terms the difference the second and third methods mentioned here is analogous to standard versus high definition television.
Tools used in CNC machining are costly. The harder the material and more complex the jobs, the more costly the tools are. Tool life monitoring is essential because it allows companies to maximize their tools' ROI.
Automated machine tool monitoring offers many benefits that impact efficiency and cost. These include:
A picture of a broken endmill and the resulting scrapped part.
Tool life monitoring in FANUC is straightforward. Here are the basic steps:
Image Source: UpMold
FANUC has focused on producing parts, components, software, and systems specifically for the CNC industry. Because of this, its solutions are customized to address problems and issues common to the industry. It provides an ecosystem that helps automate and manage CNC equipment. Nonetheless, there are pros and cons of monitoring tool life in FANUC:
MachineMetrics Tool Monitoring captures machine data straight from Fanuc controls, providing accurate, real-time data on machine performance and health. This data is collected to monitor the machine tool and develop thresholds for when tool failure is imminent.
Further, this data can be used to develop algorithms to predict and prevent catastrophic machine tool failures. How is this possible?
Our team discovered a way to collect data at 1 kHz directly from the control of CNC machines (without using sensors) that can immediately be used as inputs to time series or machine-learning models to predict machine failures.
We refer to this as the MachineMetrics High-Frequency Data Adapter.
Rather than manually collecting part counts or using a basic solution like Fanuc’s, users can leverage high-frequency machine tool data to establish more effective tool life parameters.
Machine tool analytics can be leveraged to optimize processes around the machine, enabling communication and automation that supports the maximization of tool life. For example, operators can be notified of imminent tool failure to proactively replace the machine tool.
This ensures several major benefits:
When BC Machining sought help to address continuing tool breakage and high scrap rates, they engaged MachineMetrics for a solution. BC Machining serves the medical, defense, transportation, and power tool industries where precision is critical.
BC Machining had been experiencing excessive tool breakage in their Swiss CNC machines, creating scrap both at the point of breakage and near-end-of-tool-life when parts can vary out of spec.
Using the MachineMetrics solution of capturing high-frequency data and analyzing it through advanced algorithms, BC was able to identify tool breakages to prevent scrap parts.
The drop in lost parts, sorting, and uncertainty translated into near 100% failure detection and a $72,000 annual savings per machine.
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