Quality control in manufacturing is no longer confined to inspection rooms or end-of-line checks. It has evolved into a dynamic, data-driven discipline that operates continuously across the production lifecycle. This transformation is being powered by manufacturing intelligence – the integration of metrology data, advanced analytics, connectivity, and software-driven decision-making into a unified ecosystem.
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Today, point cloud technology is transforming that paradigm. By capturing millions of data points across entire surfaces in seconds, manufacturers can now analyze complete geometries rather than isolated features. This shift from sampling to full-field inspection is redefining how quality is measured, controlled, and improved.
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As additive manufacturing continues its transition from prototyping to full-scale production, the demands on quality control are evolving just as rapidly. This month’s developments across the metrology landscape make one thing clear: inspection is no longer a downstream checkpoint – it’s becoming an integrated, intelligent, and increasingly automated part of the manufacturing process.
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Volkswagen plans to offer 70 percent of all cars produced as fully electric vehicles by 2030. Despite this enormous change to its product portfolio, Volkswagen’s commitment to quality remains unchanged. “Our components must meet high quality standards, whether they are combustion engines or electric motors”, says Holger Giersberg, sub-department head for quality assurance in the foundry and machining division at the Volkswagen plant in Kassel.
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Frontline workers remain central to production, inspection, and maintenance operations in manufacturing and industrial environments. Despite widespread digital transformation across engineering and design functions, many frontline processes still depend on paper-based instructions, fragmented data sources, and manual workflows.
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This article provides insights into how manufacturing companies can harness the potential of 3D scanners within automated environments. It also offers guidance for adopting approaches that balance initial technology investments with future scalability toward end-to-end automation.
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Metrology News recently sat down with Robert Wasilesky, President at Kitov AI North America, to discuss how artificial intelligence is rapidly reshaping industrial quality control. What was once a futuristic concept is now becoming central to factory operations, enabling real-time data interpretation, automated inspection planning, and increasingly predictive quality systems.
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For decades, manufacturing has generated enormous volumes of data, yet much of it has lived a quiet life in databases, reports, and archived quality records. Measurement results were stored for traceability. Machines logged process parameters. ERP and MES platforms tracked orders and output. But these streams rarely converged in a way that allowed production to adapt in real time.
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The Renishaw RCS portfolio includes portable toolkits and in-process probing solutions designed specifically for six-axis industrial robots, allowing manufacturers to validate robot performance, improve positional accuracy and reduce downtime.
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Metrology Brew newsletter features a summary of headline metrology and smart manufacturing news from the past 7 days.
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