How IoT Integration Enhances Quality and Speed, Part 2 – Quality Magazine

CMMs can improve shop floor precision measurements. Image Source: Mitutoyo
In plain language, Internet of Things (IoT) integration is the process of connecting sensors and objects with one another—and with applications and databases, says David Wick, manager of product management, ZEISS Industrial Quality Solutions.
CMMs are already benefiting from IoT through the integration of multiple plug-and-play tactile and non-contact sensors with metrology software and measurement databases, says Wick. This integration helps sensors and objects communicate directly with applications and databases.
When coordinate measuring machines (CMMs) enter the picture, manufacturers can improve product quality and manufacturing speed. This combination helps sensors to collect and report real-time data, significantly reducing machine downtime and the production of out-of-spec products.
As the manufacturing sector faces staff shortages, this integration allows for automated adjustments to machine tools if they trend towards producing out-of-tolerance parts, thereby reducing scrap and rework.
“With shortages of skilled labor and resources—and as the Internet of Things (IoT) brings increased connectivity — manufacturers are seeking a more streamlined and speedier measurement process, one that eliminates the need to move parts away from the production line for verification,” says Gene Hancz, CMM product manager, Mitutoyo America Corp.
Dan Skulan, general manager, industrial metrology, Renishaw, says that “information automation”—where IoT boosts communication between devices—ensures that measurement data lands directly within the production machinery, increasing overall speed and accuracy.
“IoT has increased the ability of all devices in a manufacturing environment to communicate with each other more effectively… eliminating the delays and possible loss of context that happens with human transfer of information,” says Skulan.
With the advent of IoT and AI, along with analytical information, there’s a marked improvement in flexibility and overall product quality, experts say. The ability to monitor CMM usage and maintenance needs in real-time also makes CMMs more reliable.
Real-time data collection also offers broader organizational benefits, experts say.
“The key advantage is that a customer can see if specific steps in their production process are yielding a part within the desired specification, right now,” Wick says. This immediate feedback loop enables manufacturers to make necessary adjustments on the fly, minimizing scrap costs and development time. Wick also points out the strategic advantage in larger organizations, where real-time data collection facilitates the comparison of measurement results across machines or even across global plants, thereby “accelerating quality improvement across the organization.”
Real-time data and analysis keep production standards high, as they allow for immediate corrections. Experts say that artificial intelligence (AI), takes this a step further, predicting potential issues and giving teams a chance to address them before they escalate.
“Real-time analytics with the aid of AI can identify trends that can predict an out of tolerance state before they happen, prompting immediate attention,” Hancz says. This significantly reduces the risk of producing out-of-specification parts.
Real-time information conversion into actionable steps, otherwise known as in-process control, also boosts quality.
“Real-time information can quickly be converted to action that can be taken with minimal parts being run while you wait,” Skulan explains. Teams can use near-machine CMMs or gaging systems to facilitate in-process control, often integrating CMM-type measurements directly on CNC machines. This strategy enables teams to measure parts before machining, so they are produced correctly.
Genevieve Diesing is a contributing editor for Quality.
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