Metrology has always been at the core of precision manufacturing. As Industry 4.0 advances, generative AI transforms metrology by introducing dynamic data analytics tools that improve measurement accuracy, refine quality control, and meet the growing complexity of modern manufacturing demands.
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As the world leader in crash test dummies, new designs with more high-tech features are appearing daily. PolyWorks|Inspector helps Humanetics share information and stay ahead of the curve.
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Researchers have developed a faster and more accurate method for acquiring and reconstructing high-quality 3D surface measurements. The approach could greatly improve the speed and accuracy of surface measurements used for industrial inspection, medical applications, and robotic vision.
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Digital transformation in manufacturing integrates all areas of the business with advanced technologies, thus fundamentally changing how manufacturers work and add value for their customers.
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The use of AI in the manufacturing process for predictive decision-making is still in its infancy. As these technologies become more advanced, we will continue to see greater adoption of AI across manufacturing operations, not only predicting the likelihood of a product or part failing, but also to predict supply chain issues
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Before adopting FMS, a manufacturer relying on traditional twin-arm CMMs with touch probes might struggle to access the features of complex new parts requested by the customer. This often requires the measured part to be repositioned, leading to longer cycle times and increased operational costs.
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In the world of precision manufacturing, Coordinate Measuring Machines (CMMs) stand as pillars of quality control and assurance. These sophisticated devices have become indispensable tools for verifying the dimensions of manufactured parts with incredible accuracy.
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Digital transformation includes where you acquire the data, how you store and access it, and how it is displayed to those who need it.
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Metrology provides manufacturers with the ability to measure and validate the critical dimensions, tolerances, and geometric features of components. This ensures that every product meets the specified quality standards and performs as intended.
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Predictive quality represents a profound transformation in how businesses manage product quality and operational efficiency. By harnessing the power of data, analytics, and real-time monitoring, organizations can predict and prevent quality issues before they arise, leading to cost savings, enhanced product quality, and greater efficiency.
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