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Tool life has always been a difficult problem for users to measure. Are you often unable to measure the timing of tool change? we don’t want to change the tool too early to shorten the life, meanwhile, we don’t want to cause losses due to broken tools. In the past, we often relied on experience to judge the life of the tool, but the accuracy rate was very uncertain. In fact, the tool life can be predicted through smart cutting, and significantly reduce the cost of early tool change or tool breakage.
The tool lifespan refers to the amount of cutting time a tool can endure before it becomes damaged. It is typically determined based on the measured tool wear, and judgments are often made according to machining conditions and the experience of on-site operators.
Generally, the tool life mentioned in the machining industry is almost calculated through the experience of the experienced operator, the test data provided by the tool manufacturer, or the standard calculation by using PMKNSH-ISO513, but in the ever-changing processing environment, it is difficult to have accurate tool life. The main variables include the shape of the workpiece, the type of material, the type of tool, the coating, the cutting fluid, the quality of the tool, the accuracy and rigidity of the spindle tool holder, the overall performance of the machine tool, the program path, the motor matching, etc. There are many variables, Therefore, the most direct method is to put the sensor into the tool for real-time monitoring.
Such big data is accumulated to analyze the cutting trend, and it will be found that the tool life must be presented in a dynamic way, in order to accurately find out the optimal direction from so many variables and even quickly reduce the processing cost.
Cutting force refers to the force generated on the workpiece and the tool during the cutting process, which is equal in size and opposite in direction. It will directly affect the quality of the workpiece, the life of the tool, and the power consumption of the machine tool. Generally, the cutting force value can be obtained by means of instrument measurement. The size can also be calculated using the formula.
Through instrument measurement, just looking at the picture above, these cutting forces are for the quality of each tool, and no problem can be seen in the data. Only two wave peaks can be seen from one cutting force to know the signal from the entry to the exit.
Through the production of thousands of workpieces, it can be concluded that the cutting force has a gradual and slow upward trend. From the above figure, we can understand the importance of historical data accumulation.
The blue cutting force is the original cutting parameter of the shop owner. Before processing 4,000 pieces, the cutting force will increase in an unstable trend. The owner has broken the tool when machining more than 4,000 pieces in the past, so from formal experience, the life of this tool is machining 4,000 workpieces.
After the measurement of the smart tool holder, in these unstable cutting processes, as long as the tool could continuously machine, it can actually process more than 5,000 pieces. But not all tools can process so many, and the amount of quality variation from the first to the five-thousandths is very high, so the number of workpieces that can be machined under mass production will vary.
After smart cutting optimization, we can see that the green cutting force data has very smooth force stability from the first to the 6,000th piece, which means that the quality variation is very low, and the tool life is also significantly improved. The lifespan score after optimization has also reached 7,500 pieces.
According to the above figure, it can be known that the optimized tool is No. 3H, which only accounts for 9% of the whole process. After calculating the overall cost-effectiveness of the machine tool, the mass production of this set of workpieces can save 7,800 euros per year, which is about NTD$27 10,000, this is only the benefit of optimizing one tool. If 2H, 8V-1 and 11H are individually optimized for smart cutting, the cost savings will be considerable, which is also the benefit of having all cutting processes fully digitized.
The main picture provided by Machsync
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