Efficiently achieving optimal quality and yield equals success in today’s advanced manufacturing sector. Manufacturers that meet demanding quality benchmarks rely on innovative optical inspection techniques that harness the power of digitization, automation, and advanced imaging technologies. What was once a labor-heavy process has evolved into fully automated, robust analysis used by industries like automotive, electronics, food and packaging, and environmental monitoring.
The concept of Industry 4.0 focuses on the digitization and automation of manufacturing processes using advanced technologies such as high-speed imaging, AI, spectroscopy, and hyperspectral imaging for defect recognition and material identification. The Fourth Industrial Revolution replaces traditional inspection processes that were time-consuming, labor-intensive, and prone to errors, with on-site or in-line inspection points that require minimal sample preparation.
The evolution of Industry 4.0 has paved the way for Industry 5.0, which aims to improve collaboration between humans and robots. Inspection techniques are crucial in this regard, as the development of better optical inspection techniques has made fully automated operation possible, including logistics, inspection, and process monitoring.
Manufacturing processes continue to evolve, and so do optical technologies. With 100% in-line inspection, optical tools and techniques are critical for high-throughput nondestructive testing, defect detection, inconsistencies, characterization, and measurement processes. A wide variety of optical instruments are used, from handheld devices for on-site inspections to machine vision for high-speed food sorting lines. With high-sensitivity images in color and multispectral formats, line scanning can increase SNR for higher-quality images at lightning-fast speeds. Other techniques such as spectroscopy can provide instant on-site analysis of chemical compositions and characterization, while hyperspectral imaging enables real-time detection of defects, pathogens, and unwanted substances.
Subsurface and internal inspections use machine vision technology that employs two variables, x and y. By using imaging devices on high-speed food sorting lines, the technology scans products and identifies those with hidden defects. The imaging technology has evolved from monochromatic cameras with limited capabilities to now using multispectral high-sensitivity images in full color. This is made possible by multiline spectral image sensors or prism-based multicolor cameras, which require less optical design effort. The addition of line scanning increases SNR for higher-quality images at faster speeds. The use of SWIR technology allows for clear images by penetrating through the surface. The technology also detects reflective light and water absorption, and enables the identification of different materials.
Spectroscopy is one of the most efficient ways to determine different compositions or content. Prior to industrial automation, samples had to be sent off-site for analysis, adding delays to production timelines. Today’s compact spectrometers enable on-site analysis and provide instant information in small form factors for nondestructive in-line and on-site monitoring. This technology saves time and resources, especially in food and beverage, semiconductor, and environmental monitoring applications.
Industries use NIR spectroscopy to identify and characterize chemical compositions, helping manufacturers screen for impurities, maturity indicators, moisture content, and more. Fast, sensitive, and highly accurate, NIR testing heads off potential quality and safety issues.
Hyperspectral imaging captures spatial and spectral data at the same time. When processed, it exposes and pinpoints objects within varying materials or substances. With its cutting-edge capabilities, hyperspectral imaging is particularly invaluable in food production where it delivers real-time detection of foreign objects, pathogens, bone chips, fat content, and unwanted impurities. Such groundbreaking precision ultimately benefits not only businesses but the safety and health of consumers.
Distance imaging methods calculate distance and direction for precision accuracy in automated object selection, touchless interfaces, robot navigation, people counters, and vehicle monitoring. Motion and object detection is possible even in applications that don’t require resolution. Imaging sensors can also detect the distance between objects. As sensors become more sensitive and robust in performance, even higher levels of autonomy can be achieved.
When combining hyperspectral imaging and distance measurement, the (x, y, z) coordinates represent the spatial dimensions of the scene, while the lambda (λ) coordinate represents the spectral dimension, comprising a range of wavelengths. By integrating spectral information with precise spatial data, researchers and professionals can perform superior 3d representations ideal for use in analysis, object recognition, and classification, leading to advancements in mining mapping, infrastructure defects, agriculture, and environmental monitoring.
With advanced optical inspection techniques, manufacturers can have complete control over quality and efficiency while minimizing costs and errors. At Hamamatsu, we’re proud to be a part of these cutting-edge tools and techniques that continue to transform the industry, leading to sustainable ecosystems and a better human experience.
Connectivity, automation, and machine learning propel business to the next level.
Analyzing food safety with spectroscopy: Identify contaminants and quantify chemical composition in food products using IR, UV-Vis, MS, and NMR techniques. Detect mycotoxins in barley, assess soybean quality, monitor hemp production, and combat adulteration in global foods
A fast way to answer “How far?”
Hamamatsu offers a variety of devices for time-of-flight (TOF) LiDAR, including pulsed laser diodes as light sources and Si APDs, InGaAs APDs, and MPPCs (SiPMs) as photosensors.
Photonic technologies play an important role in the development and operation of AGVs, enabling them to navigate their environment, communicate with other systems, and transport materials safely and efficiently.
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