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How to Perfect a Machining Process
(Or At Least Make It More Trustworthy)
By: Peter Zelinski
There will always be uncertainty. For this reason, it may not be possible to
truly “perfect” a machining process—at least not in literal terms. But what if
the scope of all of the uncertainty in the process could be known in advance?
What if the error was known to be small enough that it wouldn't compromise the
precision that the part required? Such a process could be considered “perfect”
as far as that particular part was concerned. The process could be trusted to
make that part, and this trust alone could deliver substantial savings.
Users of machine tools traditionally have not trusted their processes. There has
always been a gage at the end (if not a series of gages) to check whether the
part had been machined as expected.
But what about using a gage at the beginning?
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| These components of a machine tool's precision affect multiple machine axes, resulting in 21 degrees of freedom or 21 potential sources of error. |
That is, what about inspecting the process first, so the shop can determine in
advance whether the process can make the part?
In the scenario just described, a stand-alone gage such as a CMM no longer has
to police the process on an ongoing basis. Instead, CMM inspection of finished
parts can be used to provide independent validation in just those cases where
the validation is needed. In other cases, the process can simply keep on
producing without the CMM—making those parts that the shop already knows the
process can make.
This practice of inspecting to measure the process instead of the parts is
becoming more common as manufacturers recognize how much they can save not only
by inspecting less frequently, but also by avoiding the scrap that results from
not knowing precisely what a process can do.
Two people who have helped shops implement this inspection strategy work for GE
Fanuc Automation in Charlottesville, Virginia. They are Mark Brownhill, manager
of machine tool services, and Jim Spearman, manager of machine tool solutions.
This article summarizes some of their insights into measuring and optimizing the
capabilities of a machining process.
Step one, they say, is to identify the sources of variability. That is, identify
the many reasons why machining errors occur.
Murphy's Law?
To begin, just the machine tool itself offers plenty of room for error. A
typical three-axis machine tool will have 21 degrees of freedom, which
translates to 21 potential sources of inaccuracy. Then there are the workholding
elements—the fixtures, clamps, chucks, vises and jaws—that add even more degrees
of freedom.
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| Laser measurement of production machine tools can be used either to improve machine accuracy through maintenance, or else to establish each machine's baseline performance. Photo courtesy of Kentucky Rebuild Corp. |
Add to all of this the variability that is inherent in other elements of
the process. The tooling, material, and any necessary measurements and data
entry all introduce opportunities for variation. And variation from job to job
can come from the way the part program is written, as well as just the
programmer's act of selecting a methodology for producing a particular part.
The variability mentioned so far is present before the first piece is machined.
Hit “Cycle Start,” and even more sources of variability come into play. How
repeatable is the machine? How consistently are workpieces loaded? And then
there is the variation that occurs simply as a result of machining, such as tool
wear or tool breakage.
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| The blind hole in the lower half of this photo is used to identify the job on the pallet. Every pallet in the cell has a hole with a different diameter. Measuring the diameter with a probe lets the CNC determine just which pallet this is, and therefore which program should be loaded. The photo, courtesy of Toyoda Machinery, shows a customer of this machine supplier that uses this technique. |
In short, a lot can go wrong. But here's the thing: The error sources are
finite. They are also measurable, and in many cases, they are improvable. To
achieve a process that doesn't have to be policed, the shop simply identifies
and “fixes” as many sources of variability as it reasonably can—perhaps
attacking them in order of their severity. Then, the shop establishes a baseline
level of performance by measuring the variability that still remains. By
improving a process and then measuring what it can do, the shop can predict in
advance precisely which jobs should be assigned to particular machines.
Though there are many sources of variability, they fall into two basic
categories. The distinction is helpful when it comes to addressing them. There
are errors that affect “setup yield,” which are the errors that are present for
the very first piece machined. Then there are the errors affecting “production
yield,” which are the errors that only come into play in the course of producing
a run of parts. Where the first sort of error has to do with the accuracy of the
process, the second sort of error has to do with the repeatability.
More Accurate Production
The accuracy of the process represents much more than just the accuracy of the
machine. However, the machine's accuracy is a fundamental component.
The machine's accuracy can be measured using a laser. Initially, the laser
measurement can help in improving the accuracy through maintenance. At the point
where the machine's accuracy can no longer be improved in this way, the analysis
then becomes valuable for characterizing what the machine can do. A particular
job should be assigned to—and remain assigned to—a machine tool with measured
capabilities good enough to allow the machine to comfortably produce that part.
Another influence on the accuracy of the process comes from human involvement,
and all of the potential for variability and mistakes that this introduces.
Here, maintenance can't help. Instead, achieving a more accurate process often
comes down to finding ways to minimize human beings' roles.
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| A feature such as this ball can eliminate the need to enter CNC offsets by hand. The ball is mounted on the fixture, where it serves as the location reference for the work that fixture holds. By probing this ball to find its X-Y-Z center point, the CNC quickly locates the work without operator intervention. Photo courtesy of The Tech Group. |
The operator is not the only human concerned here. Differences in processing
strategy from programmer to programmer also represent a significant source of
variability—and one that can be controlled. To make this aspect of the process
more consistent, the shop can implement CAM automation that automatically
recognizes part features and assigns tool paths according to the shop's
preferred practices. Not all programming can be automated in this way, but using
this technology can at least improve programming consistency.
There is also the hardware automation that does address the operator's role. At
the machine tool, automation can take a variety of forms, many of which don't
require the shop to add expensive equipment. Some possibilities include:
- Built-in fixture identification. A fixture can include a feature that
identifies the part number it holds. The CNC can then use this identification to
automatically confirm that the correct program has been called up for that part,
avoiding a potentially costly error. The identification feature might take the
form of a machine-readable label such as a bar code, but it might also take the
form of a feature that is inspected through probing. For example, different
fixtures could have identifier holes of different diameters, allowing the CNC's
measurement of the hole diameter to tell it which program number it should be
running.
- Reference points on the fixture. A tooling ball, or some comparable feature,
can be added to the fixture to establish X-Y-Z reference points for the work.
The program can then include a probing routine for locating this feature just
before machining begins, so that an operator no longer has to measure and enter workpiece offsets by hand.
- Automatic transfer of tool data. Entering tool offset data by hand should also
be avoided. One way to do this is to network the tool measurement device to the CNC for direct transfer of this data. As an alternative, toolholders can be
equipped with electronic ID tags in which tool measurements are stored long
enough for the data to be read in automatically at the CNC.
More Repeatable Production
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| A quick inspection of a machine tool with a ballbar delivers a variety of performance data. This check can be used to confirm that a machine is still performing within its baseline range, and also to predict when maintenance might be needed. Photo courtesy of Renishaw. |
Laser measurement is one of two complementary methods for inspecting the
performance of machine tools. The other is ballbar inspection. While the laser
can be used to establish a machine's performance baseline, the ballbar offers an
easy way to monitor that performance over time. A 30-minute inspection routine
using a ballbar delivers a variety of performance data. By performing this
inspection regularly, a shop can either check for changes or confirm that the
machine is still performing at its baseline level. By monitoring patterns in a
machine's ballbar inspections over time, the shop can even predict when various
maintenance operations may need to be performed.
Inspection with the ballbar takes place outside the cut. Once cutting begins,
certain CNC capabilities become valuable for countering or addressing the sorts
of errors that vary from workpiece to workpiece.
These capabilities include:
- Adaptive control. Because a dull tool draws more current, the CNC's measure of
this current can allow it to determine when a tool needs to be replaced. The
same capability also lets the CNC respond to variations in either the material
properties or the profile of the cut by slowing the feed rate to compensate for
an excessive load.
- Tool management. A shop that has measured the life expectancy of a particular
tool can take advantage of a CNC that has tool management capability. The CNC
tracks the use of a given tool, replacing it automatically when its specific
cutting life has been reached.
- In-process inspection. In addition to its role in locating parts before
cutting, the machine tool probe can also do much of the work of inspecting a
part when the machining is done. It is not true that a machine tool can't
inspect its own work. Errors resulting from tool wear or tool breakage, for
example, can be detected using the probe. Finding these errors before the work
leaves the machine makes it easier to correct them, and the probe measurement
might even allow this error correction to occur as an automatic part of the
program.
Project Success Factors And Pitfalls
Jim Spearman and Mark Brownhill of GE Fanuc Automation offer these additional points on how to select an appropriate process improvement project.
Success Factors
The project is more likely to succeed under these conditions:
- Solving the problem would have an identifiable impact.
- The scope of the project is manageable. If the project feels too big, it probably is.
- The project involves an identifiable defect. A defect should be measurable, not philosophical or subjective.
Common Pitfalls
These hazards are frequent causes of failure:
- Inadequate resources for the project
- Duplicating the aim of another project
- Losing momentum
- Picking a project that is only easy, not critical
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Getting Started
One of the problems of realizing process improvements such as these is knowing
which improvement to make. With any machining process, there is so much that
might be improved upon that it's difficult to know where to begin.
To find a particular problem with the process that is sufficiently important to
make it worth addressing, try asking this question: What does my customer
think is critical to quality? While that question may not identify just one
problem to tackle, it will at least narrow the field. Other important questions
to ask after that relate to whether a problem is measurable, and whether solving
the problem is feasible. (See the shaded box on the previous page.)
Once a problem is identified, the success of the solution will depend not only
on the solution's technical merits, but also on how well the solution is
accepted. Involving the various stakeholders from the beginning of the project
is one way to encourage this acceptance. To help identify the relevant people
for a particular project, ask questions including: Who speaks for
manufacturing? Who speaks for the customer? Who has a view of the overall
process that is broad enough to define the important issues? All of these
people should be brought into the team.
After that, finding the right problem to address is likely to get easier. Once
the process improvement team succeeds—once it manages to make the process
better—then that very success is likely to highlight precisely which
quality-related problem the shop should be looking at next.
Peter Zelinski
Features Editor, MMS Online
Article courtesy of MMS Online
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