The global manufacturing industry is undergoing a profound transformation. Confronted with persistent labor shortages, complex supply chains and rising tariffs, manufacturers are turning to artificial intelligence (AI) and automation not just as tools of convenience, but as essential ingredients for future success.
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As digital transformation sweeps across every facet of industrial production, a new paradigm of measurement and quality assurance has emerged: Metrology 4.0. Modeled after the principles of Industry 4.0, this evolution redefines metrology not just as a set of measurement techniques but as an intelligent, interconnected system deeply integrated into the fabric of next generation manufacturing.
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Whenever vehicle production equipment fails at a BMW Group plant, every minute counts. The maintenance team must work quickly to identify and resolve the cause of the fault. Now, employees can ask the new digital AI assistant, “Factory Genius”, for help: It can suggest solutions for the specific system problem within seconds, reducing the time required for error diagnosis to a minimum.
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Manufacturing has been a cornerstone of global economic growth since the Industrial Revolution. Today, however, the landscape is undergoing a fundamental transformation. Societal and structural shifts, including aging populations, shrinking labor forces, evolving trade policies and overhauled supply chains, are pushing the industry to rethink how products are made.
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Coherence Scanning Interferometry (CSI), also known as white light interferometry, has emerged as one of the most powerful, non-contact techniques for surface roughness measurement, delivering unprecedented resolution, accuracy, and versatility.
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Additive Manufacturing (AM) is often celebrated for the freedom it offers designers, freedom from tooling, freedom from conventional constraints, freedom to explore geometry at levels once unimaginable. Yet for all its promise, AM has also become trapped in a cycle of what can perhaps be called superficial innovation.
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Margins are under constant threat and businesses need to find ways to reduce costs, improve efficiency and productivity, and drive down waste. Metrology can help alleviate some of these pressures on the business when used efficiently.
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An MIT Technology Review Insights survey of global manufacturers found that 57 % of executives identify data quality as their biggest obstacle to scaling AI, a view shared by half of leaders in electronics and high-tech production.
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Manufacturers often struggle to use measurement results effectively, largely due to their reliance on static 2D reports that lack the level of detail needed for informed decision-making. While having access to rich 3D measurement data is essential to analyze issues thoroughly, managing such data can be cumbersome without a proper data management solution.
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Ensuring dimensional accuracy, repeatability, and quality assurance in additive processes is far more complicated than in traditional subtractive methods.
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