Using Intelligent Machine Control To Optimize Quality Assurance
One of manufacturing’s biggest challenges is filling the knowledge gap left by skilled employees who retire. Intelligent machine control (IMC) increases throughput regardless of who’s operating measurement and production equipment by removing the potential for human error.
Posted: January 12, 2021
TOWARD ZERO DEFECTS COLUMN
BY SCOTT MAHRLE
Achieving productivity gains with smart-manufacturing solutions is all about using the data you’re already generating to solve problems at any of several points during the manufacturing process. Cloud and edge computing, automation, and intelligent maintenance systems (IMS) are all great examples of technologies that support smart manufacturing and rely less on operator input for critical decision making than traditional manufacturing processes.
Likewise, intelligent machine control (IMC) solutions apply smart-manufacturing technology to quality-control processes.
IMC software is used during inspection to collect and analyze measurement data and, when applicable, use that data to course-correct machine tools throughout production. As machine correction is traditionally a manual process that requires operators to make the connection between measurement data and low-quality parts, IMC is among the more forward-thinking smart-manufacturing technologies because it removes the error-prone human element from quality assurance.
Instead, the software uses an automated feedback loop between metrology equipment and CNC machinery. By applying algorithms and statistical analysis to measurement data, the software paints an accurate picture of part quality in the present while predicting how and when quality will diminish in the future.
Creating An Ever-Improving Feedback Loop
Installed on a computer that’s networked to metrology equipment and CNC controllers, IMC software communicates with machinery to create a quality-control feedback loop. Metrology equipment including hand-held devices, on-machine probes, and stationary coordinate measuring machines (CMMs) is compatible with the software.
In a manufacturing environment that uses stationary measurement equipment, parts are fed manually or with automated machinery to CMMs for inspection. Most metal manufacturers that use IMC solutions measure just a fraction of the parts they produce – and this is where the importance of statistical algorithms come into play. The software’s core function is to capture measurement data and perform analysis, i.e., statistical process control, that predicts trends for future performance. In a nutshell, these analysis tools are used to determine if parts are trending toward non-tolerance to the point where a machine adjustment is warranted.
If it is, the software communicates directly with the CNC machine’s controller to make offset adjustments that correct the way parts are machined. Tool offsets are size allowances made for the diameters and lengths of the tooling used to cut parts. CNC programs are typically written with offsets that place the middle point of cutting tools in the center of the toolpath or the programmed cutter-path taken by the tool. As measurement data collected by the software analyzes small changes in machined features that reflect wear on cutting tools, offset adjustments are automatically made to compensate for tool wear to maintain tolerance.
Customization of IMC solutions allows users to determine when offset adjustments should be made. For instance, a part that’s fallen rapidly and drastically out of tolerance isn’t cause for offset correction because it points to the likelihood of a single event that threw a wrench into the works rather than an actual production trend.
Without an automated feedback loop, operators must interpret the data, making judgements to the best of their ability and making offset adjustments manually, at the machine control. Use of the feedback loop ensures changes are made at the right time and magnitude because the automated system monitors trends and watches values, including expected patterns of tool wear.
One of the biggest challenges for just about any manufacturer is filling the hole left by skilled operators who retire from the workforce and take valuable knowledge with them when they go. While skilled operators can be excellent at making decisions about offsets, less experienced operators typically take more time and use more guesswork to solve problems. Automated corrections are more stable because they don’t rely upon input that varies from operator to operator and shift to shift. This is why IMC feedback loops can also be used reliably for unattended machining and inspection.
In addition to applications for fabrication and machining, automated feedback plays a crucial role in the quality of additive manufacturing. Called “in situ monitoring” or “in situ inspection,” feedback loops for additive manufacturing are drastically different from IMC solutions even though the concept is exactly the same. During in situ inspection, measurements are taken within the 3D printing envelope with each pass of the printer so adjustments can be made automatically while the part is still being printed.
Finding The Right Solution
The strength of IMC software lies in its ability to analyze metrology data over time, which is really less about time and more about the number of parts analyzed. In other words, users will more quickly have reliable data for trend analysis if they produce 1,000 parts per day versus 100.
If you’re wondering whether an IMC solution would be a good fit for your operation, it’s important to examine your application, shop size, production volume, and long-term company vision to see if automated feedback is truly going to pay the most dividends. These solutions are most suited for high-volume manufacturers with low part mixtures because that’s the ideal environment for analyzing production trends over the long term.
Job shops, on the other hand, typically serve multiple industries and produce a wide range of parts in small-to-medium lot sizes. As such, the time required to set up each new job to benefit from metrology feedback may be prohibitive. Likewise, you may simply not manufacture enough parts for any given job to analyze production trends.
Legacy machines with different communication protocols are another potential stumbling block to implementation because consistent processes across all machinery must be established to make an IMC solution run like a well-oiled machine.
What To Do Next
Smart manufacturing covers such a broad array of technologies that it can be overwhelming to know where to begin. If you’re machining or fabricating and performing some level of measurement, you’re really only missing the connection that links those two processes.
While IMC isn’t a one-size-fits-all proposition, you may benefit from speaking with solutions providers to see how they’d make your data work harder so you don’t have to. They may be able to configure a cost-effective customized package that meets your specific needs. If you do ultimately opt for implementation, it’s vital that you work with a provider that understands how your company operates today and where you want to be in one year, five years, and beyond.
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