Maintaining The Edge
- Published: November 2, 2016
Cutting tool maintenance enters the digital age
The term “maintenance” conjures up an image of a overall-clad, oil-stained technician carrying a toolbox. It’s a hands-on occupation. But the advent of the automated shop floor means that even if tool maintenance means someone has to get their hands dirty at some point, they do so with an increasingly impressive array of information to guide them.
Cutting tool maintenance no longer has to be a matter of consulting paper records to see which tools are nearing a maintenance interval, or the end of their useful life. Software packages are available that automatically monitor tool inventory and issue an alert or reminder when action needs to be taken.
But that’s just an initial phase of the kind of automation that can transform the shop floor. Ultimately Industry 4.0, or the “Industrial Internet of Things” (IIoT), promises to equip tools and machines with onboard systems and sensors that enable them to communicate with each other on their own, minimizing human intervention to situations where remedial action is required.
Once a truly autonomous network is established, a lot of tool management can be conducted without human intervention at all, says Don Graham, manager, education and technical services, Seco Tools. As Graham notes, conditions change constantly on the shop floor. “After a system is implemented, the material could change slightly, or a bearing or a spindle in the machine begins to go bad, or somebody changes a tool. Things change and that’s where this electronic interaction and be really beneficial. The system can tune itself on the fly, without human intervention. The tool and the machine can talk back and forth and adjust speed and feed, and improve part quality, tolerance control and tool life.”
Florian Bopple, digital manufacturing expert with Walter Tools in Tubingen Germany, breaks down the development of Industry 4.0 to four distinct phases. The first involves the process of gathering data and making it visible or available. The second is analyzing that data, typically according to an algorithm that has been developed to look for certain patterns or significant correlations.
“The third step is where, out of the analysis that you do, you drive your optimization,” Bopple says. “Either you drive it, or a machine drives it–an algorithm that brings that analysis into action.”
The fourth step is the autonomous operation of connected devices. “This is where everything communicates with each other and delivers the optimization to each other and they pull it through automatically,” Bopple says. “It’s not humans that have to pull through the optimization; a machine does that.”
Automation will benefit tool maintenance and extend tool life by enabling operators to take proactive steps that minimize wear and avoid breakdown or catastrophic failure. This is what many call “predictive” maintenance, but Bopple sees an evolution beyond the merely predictive.
“When you get a lot of data and you use a technology like data mining, it will definitely help you become, on the one hand, predictive–but also prescriptive,” Bopple says. “Prescriptive maintenance is the next step beyond predictive.” While predictive maintenance triggers an alert that says an error or failure is going to occur in, for example, two days, prescriptive maintenance can prevent those errors.
“The predictive approach would be to give a message to the operator that says this tool is about to be worn out; you might want to change it within the next 15 minutes so that there’s no damage to the work piece,” Bopple says. “Prescriptive tells you that there’s an adjustment that will increase the tool life. For instance, you speed up the feed rate a bit and you get a message that tells you the tool life will be hit in 15 minutes if you keep going like that, but it also tells you what you can do to keep that from happening. That’s one out of many possible scenarios.”
Bopple cites Walter’s new tool management software as one example of how the ideal of Industry 4.0 is gradually coming closer to reality. The software, called Tool-ID, enables the operator to transfer tool data from the pre-setting device to the machine itself, by assigning a dynametric code to a tool and associating data about the tool to that code. The data can then be transferred whenever needed to the machine control unit.
“You can do this with every component, depending on how deep you want to go,” Bopple says. “Once the tool or other component is in the manufacturing process, all the data that comes up on it is recorded and can be analyzed, displayed anywhere. You can find out immediately how long or how often a tool holder has been used, how many tools have been used with it, how long you’ve had it.”
If a job shop has a policy of replacing tool holders after three years of use, this kind of automated system can ensure that nothing gets missed and tools don’t accidentally continue to be worked beyond their intended useful life.
Digital systems are increasingly being incorporated into the tools themselves. Most shops are familiar with the idea of digital rather than analog readouts on tools. BIG Kaiser launched boring heads with digital readouts a couple of years ago, but at this year’s IMTS they built on that capability by incorporating memory capacity within the heads as well.
“Each time the head is adjusted, the internal memory records when it was adjusted and by how much,” says Alan Miller, engineering manager and product manager for BIG Kaiser Precision Tooling Inc. “So quality departments, managers, shop foremen can keep track of who’s adjusting, how much they’re adjusting and how that affects the quality of the parts. You can start to get a good feel for how many parts are going to run before the head needs to be adjusted for size. You not only make small adjustments, but you track them to see how it affects part quality over time.”
It will take a long time for the full scope of Industry 4.0 to filter down to the shop floor. Many cutting tool maintenance functions will remain a matter of human intervention until the automated alternative becomes widespread throughout the industry. The technology is still cutting-edge, and the sophistication and expense are a barrier to all but the largest organizations.
Don Graham doesn’t believe that sophistication is a permanent barrier. “What’s going to be required is for larger companies to debug and fine tune the technology,” he says. “Once they’re comfortable with the technology it’ll be into Generation 2 or 3. Then midsized shops will be able to consider it, and once they’re happy with it the smaller shops can embrace it.” SMT