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Proactive planning for predictive tool failure
Proactive planning for predictive tool failure

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Christa Kettlewell
Allied Machine

Tool life is often a top priority when working in a high production environment. To some degree, it does not matter if you have the fastest or the best tool; it is more important to have a tool that fails consistently in the exact same way, but the question then becomes how do you achieve this? How can you proactively plan for predictable tool failure?
There are many factors that contribute to failing consistently from the tools themselves to outside factors like coolant, machine maintenance, material hardness, etc. While it is unrealistic to hit 100% repeatability, it is key to keep as many factors as you can the same from job to job and part to part. Establishing repeatability makes it easier to prevent catastrophic failure that will damage the workpiece and tooling, which becomes much more expensive than just taking the tool out early even if that is before it is completely worn out. Therefore, cost savings is one of the biggest benefits of consistent tool life. It is better to change an insert out ahead of time instead of pushing it to max life and potentially damaging components of the tool or components of the machine—causing more setup time and more machine downtime.
Given the benefits that establishing a controlled process can provide, below are some tips to help you better achieve this.
  • Proper coolant maintenance and filtration. From bacteria and machine lubricants to acidity and cutting debris, coolant contaminants can hinder the protective layer coolant provides for both the material and the cutting edge of the tools. Whether using a refractometer to evaluate concentration levels or water test strips to measure pH levels, it is always cheaper to maintain coolant than replace the entire system or risk damaging tools.
  • Perform preventive maintenance. To achieve consistent tool life, it is necessary to perform preventive maintenance of the machine tool components and fixtures. Vibrations and lack of rigidity due to worn out components can be detrimental to new carbide tooling that shops are encountering in modern manufacturing. Overall, it is important to schedule and maintain records to save in tooling and machine downtime.
  • Source materials from consistent vendors. While it is difficult to buy materials from the same vendors because of COVID and supply chain issues, it is important to try to buy from the same vendors because differences in materials cause tools to work differently. When sourcing from different vendors, it is important to monitor incoming Mill Turn Reports (MTR) to ensure chemical compositions are comparable and make the necessary changes to programs to prolong tool life.
  • Focus on tool holders. With general purpose machining, tool holders are typically not the driving factor leading to a reduction in tool life. Nevertheless, for consistent results at higher spindle speeds, it is necessary to have a balanced tool holder and assure that the tool is assembled with minimal total indicator runout (TIR) in order to yield positive results. The cleaning of tool holders as well as the actual spindle of the machine are also important aspects of tool holding components as a layer of oil drying on these surfaces can induce TIR to the assembly, which creates additional radial loads to the tools and can cause failures and inconsistent results.
  • Consistent tooling means consistent results. In order to do this, it is key to source tools from manufacturers that have good quality systems to produce parts of the same quality every time. If there is a switch in manufacturers, processes will be affected even if the tools are dimensionally the same because quality and performance standards will vary depending on manufacturer.
Aside from these top factors to consider when planning for predictive tool failure, you can also work to baseline your tools. Whenever you are running off a project for the first time, the first couple of tools you are putting into the part need to be monitored to ensure that speeds and feeds are optimized and that repeatability is established. If it repeats after a couple of tools, that is your baseline; you can reach “x” amount of parts per tool.

Other things to consider are load limiters and part counters. For predictive tool failure in job shops, use load limiters. If one tool is consistently running at 80% load, when load begins to steadily climb to the upper end, you will know when inserts are dull and need to be changed. Part counters can be integrated into the programs. By establishing a baseline as discussed above, you will know what the tool can do and then program that into the machine. Because the actual program is counting as parts are processed, there is no error like if an operator is counting the parts; the program will stop, and no additional parts can be run unless the tool is changed.

Ultimately, not all shops are using or are capable of using predictive tool failure in their processes, but collecting data and tracking tools is a good starting point. If you are not tracking tool life or keeping a log, it is challenging to determine how long tools last or how to make them last longer. Structural steel shops in particular could benefit from collecting data; oftentimes, they are running large components in the same material at the same speeds and feeds, but because there is little tracking, tools end up breaking. Simply tracking data and running spot checks on tools could save shops money and time in addition to establishing a method for predictive tool failure.

Knowing your limitations in addition to simply being prepared are key in predictive tool failure. It may sound simple, but exceeding the limits of the machine, operator, process, tools or application will result in a less than satisfied result. Being more knowledgeable about an application—whether that is through data collection or proper training—allows you to better establish the desired repeatability.

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