Hyperspectral imaging is firmly established in environmental monitoring and aerospace applications, and the technology is gaining favor across mainstream manufacturing. In sectors including semiconductors, thin films, energy materials, and displays fabrication, hyperspectral imaging provides detailed in-process insights. Precision and yield are paramount in these sectors; hyperspectral imaging optimizes these parameters while also offering high speeds of operation and a nondestructive approach to inspection. Industry’s appetite for hyperspectral imaging coincides with falling costs and greater availability. The benefits of the technique are obvious for many adopters. For example, unlike traditional point-based measurement methods, hyperspectral imaging enables users to capture both spatial and chemical composition data over large areas in real time. It also enables smarter and increasingly automated decision-making. “We, as does most of the industry, regard hyperspectral imaging as the next major step in the evolution of industrial imaging,” said Alexandre Fong, CTO of Hinalea Imaging Corp. “As expectations for product safety and quality evolve, there is a demand for higher image information density. “I really believe we are at a convergence and inflection point with hyperspectral imaging. It has been in the wings as a research tool for some time, but the supporting data from that phase is out there and providing proof of its potential.” Into industry Historically, industries in which material composition and uniformity are critical have been prominent users of hyperspectral technologies. In metallurgy, for example, hyperspectral imaging is used to monitor alloy composition, detect impurities, and ensure material quality. In the paper industry, it is used to analyze fiber distribution, coatings, and defects. And in mining, the technique is used to identify mineral compositions for sorting and extraction. The technology’s long road into manufacturing stems from several factors. A high entry price point, coupled with the complexity of its analysis methodologies, posed a multilayered barrier to adoption. In some cases, technical specifications, such as imaging and analysis speed, resolution, and the repeatability of hyperspectral cameras, presented challenges to prospective users in manufacturing. A nontechnical factor — a general lack of awareness of the technique — also contributed to the delayed rollout of hyperspectral imaging into mainstream manufacturing. DIVE imaging systems uses Specim FX hyperspectral cameras for high-precision, nondestructive, and rapid wafer inspection. Courtesy of Specim. According to Julio Hernández, hyperspectral applications manager at Norsk Elektro Optikk (NEO) AS, the technology has evolved to address most of these issues. Further, owing to recent advancements in computing and data science and machine learning, experts today view hyperspectral imaging as more than good science. Now, it is a viable tool for industry. Oliver Grass, managing director of inno-spec GmbH, a Headwall Group company, said that this opportunity for hyperspectral imaging exists in parallel with the potential for broader adoption in industrial applications. “Until now, the high cost of hardware and the complexity of analyzing hyperspectral data have hindered widespread adoption,” Grass said. “However, the economics are changing, not only because the value of the products being inspected or graded has risen, but also because the barriers to entry are being effectively addressed.” The data is out Thin films, lithium batteries, photovoltaics, and printed circuit board and LED displays fabrication are logical sectors in which to implement hyperspectral imaging systems, according to Hernández. “These industries require high spatial uniformity in chemical properties for quality control, but high-volume production often limits detailed inspections,” he said. Data cubes of active-matrix organic light-emitting diode (AMOLED) displays from smartphone and tablet displays were captured and compared using a Hinalea Imaging VNIR hyperspectral camera to identify spectral and uniformity differences (top). A setup for electroluminescence hyperspectral microscope imaging of photovoltaic materials (bottom). Top image courtesy of Hinalea; bottom image courtesy of Photon etc. HySpex is an early demonstrator of hyperspectral imaging for the evaluation of thin-film coatings. Using its VNIR-1800 hyperspectral cameras, it has conducted assessments on titanium dioxide (TiO2)-coated polymer substrates with varying thicknesses. TiO2-coated surfaces support multiple applications, including solar cells and antifogging and self-cleaning windows. Beyond detecting the presence and position of a component in a captured image, hyperspectral imaging enables users to chemically identify and quantify it. This level of detail is an improvement on the capabilities of conventional color cameras and standard image processing algorithms. It is also essential for revealing phase changes in materials, enabling operators and automated systems to make timely and informed adjustments. According to Minna Törmälä, global marketing manager of spectral imaging firm Specim, compact and easy-to-integrate hyperspectral solutions compare favorably to these other approaches, especially in industrial environments. In such settings, higher resolution and speed enable real-time monitoring. “Traditional imaging methods, such as multispectral and RGB cameras with AI or laser interferometry, are valuable for specific applications, but have limitations,” she said. “For example, multi- spectral cameras are designed to detect specific contaminants using predefined spectral bands, making them highly specialized but less adaptable to new detection needs. RGB cameras with AI analyze materials based on color and shape, but cannot determine their chemical composition.” These approaches, particularly those using deep learning, require large training data sets and offer limited flexibility. Hyperspectral imaging captures more detailed spectral information, supporting its use in broader and more versatile applications. Further, many quality control processes still rely on experienced specialists, Grass said. He emphasized the need to transfer this expertise to automated, impartial systems. In this context, hyperspectral imaging offers a promising solution. Hinalea’s Model 4400, mounted to a ‘magnetic crawler,’ images a decommissioned nuclear reactor head (top). The hyperspectral camera is tested for its ability to detect pipe leaks by identifying the presence of boric acid corrosion (bottom). Courtesy of Hinalea. “While conventional RGB color cameras or multispectral cameras with a limited number of wavelengths may appear less expensive at first, they may need to be replaced when the customer’s needs change, which can significantly [influence] the overall economics,” Grass said. Inspections beyond surface-level In the semiconductor sector, manufacturers and engineers use hyperspectral imaging throughout the lithography and deposition processes to analyze the spatial distribution of thin-film thickness in oxides, resists, and surface parameters. Combining detailed spectral data with high-resolution imaging helps manufacturers to ensure wafer consistency and monitor quality in various stages of production. Hinalea’s hyperspectral system is one of the commercial options supporting this range of applications: Its system is configurable to monitor both critical changes in semiconductor wafer etching processes as well as to inspect the finished product. In wafer inspection, hyperspectral imaging offers significant advantages compared with traditional methods, enabling noninvasive, full-area inspection as an alternative to random sampling. A different technique, photoluminescence mapping, is commonly used to identify variations in material composition, crystal defects, and contamination at a microscopic level. “[Photoluminescence] spectra are acquired using standard classic dispersive spectrometers either point-by-point or line-by-line (push broom) spatial scanning,” said Marc Verhaegen, CTO of Photon etc. “On the other hand, hyperspectral imaging instruments can use wavelength-tunable filters to capture the entire field of view with no spatial scanning, while scanning wavelength bands.” Although these so-called “staring” instruments have mainly been used for semiconductor characterization in academic research, the approach can be faster than using spatial scanning systems when only a limited number of spectral bands are required. Given the distinct capabilities of both techniques, hyperspectral imaging can be used to complement photoluminescence with spectral information. For materials composed of multiple elements — such as perovskite or gallium arsenide photovoltaics, for example — hyperspectral imaging provides important information for determining exact composition, going one step beyond simply determining the presence or absence of compositional variations. Photon etc. has developed a solution platform that supports hyperspectral photoluminescence imaging. Another adopter, Radeberg, Germany-based DIVE imaging systems, has integrated Specim’s FX10 and FX17 hyperspectral cameras into semiconductor manufacturing processes. DIVE offers precise surface and layer analysis of semiconductor wafers. The technology can be used to inspect a 300-mm wafer in just 30 s, helping to reduce cost and waste. Elevating battery and electronics coatings Thickness is a fundamental parameter in thin films, directly affecting functionality and performance. Traditional inspection methods rely on point spectroscopy, which produces an incomplete zigzag inspection pattern. Hyperspectral imaging inspects the entire film or coating, capturing each line and generating spectroscopic data for the whole film at a high spatial resolution. Specim’s GX17 near-infrared hyperspectral camera analyzes the homogeneity and thickness of protective coatings on printed circuit boards. Courtesy of Specim. Specim hyperspectral cameras are used to detect contaminants and measure areal distributions of resists, oxides, nitrides, and more. The metal industry uses these cameras to check the homogeneity of coatings in lithium-ion batteries, evaluate the protective and functional coating inspection of electronic components, and provide surface inspection. In lithium-ion, as well as in other advanced batteries such as solid-state or sodium-ion, the electrode materials contain active material particles and often include conductive additives. Creating a uniform, electrochemically active layer that enables consistent ion and electron flow during charging and discharging cycles is crucial for consistent performance and durability, and to prevent dangerous overheating. “With the rise of electric vehicles and energy storage solutions, monitoring electrode coatings to ensure consistency in battery production is becoming critical,” Törmälä said. According to Grass, ultraviolet hyperspectral imaging is vital for these types of inspections. “A benefit of deeper UV, down to 220 nm in this case, is that manufacturers [can] better characterize thinner films,” he said. Inno-spec has introduced an integrated system that uses a hyperspectral camera operating deeper in the UV than prior solutions. Spectral precision in display inspection According to a Market Research Future report, the global 4K resolution display market was valued at $31.5 billion in 2024 and is projected to grow from $34.4 billion in 2025 to $75.7 billion by 2034, increasing at a compound annual growth rate of 9.2% during this period. Rising consumer demand for high-performance visual experiences in ultrahigh-definition televisions, professional-grade monitors, smartphones, and immersive AR/VR systems is driving this growth. Resolution, contrast, and color accuracy are key differentiators between current and next-generation displays. Precise spectral control is no longer optional. It is essential for both image fidelity and viewer comfort. The careful selection and integration of light-emitting components, particularly LEDs and/or micro-LEDs, are at the heart of determining display quality. The spectral characteristics of these emitters — peak wavelength, full width at half maximum, and spectral purity — directly influence the color gamut, white point accuracy, and overall energy efficiency of the display. The color conversion layers, such as quantum dots or phosphors, antireflective coatings, encapsulation layers, and optical diffusion or enhancement films, must be of uniform thickness and composition to ensure minimal spectral shift over time, accurate pixel-level brightness, and enhanced visibility under varying lighting conditions. To this end, hyperspectral imaging fills a current gap of knowledge in process and quality control. For example, in display tests, conventional methods for measuring color and brightness use cameras with sets of discrete color filters. Such systems often miss subtle spectral differences that influence the trueness of the captured image. Hyperspectral images, however, reveal subtle reflected color differences that are not observable by the human eye or even RGB camera images. The color metrics of tablets or smartphones, for example, are immediately identifiable by a comparison of spectra between pixels. These advantages are critical because even minor deviations in film thickness or chemical makeup in advanced manufacturing lines can lead to color banding, image artifacts, and performance inconsistencies. Hyperspectral imaging enables manufacturers to monitor and optimize deposition processes in real time, to detect subtle variations in material properties that traditional RGB or multispectral cameras cannot resolve. “A high-resolution hyperspectral camera, [either] spectral [or] spatial, can be used to simultaneously monitor these properties with great accuracy using an interferometric approach in addition to the chemical signature identification,” NEO’s Hernández said. “These results can be used in a feedback loop to fine-tune the deposition process and improve the final product.” The next generation of solar cells As quality control in semiconductor and displays manufacturing drives the growth of hyperspectral imaging systems, demand is increasing for advanced characterization tools in the photovoltaic industry. In photovoltaic facades, hyperspectral imaging enables detailed color resolution inspection, which is needed to ensure uniformity and precision — factors that themselves are important for architectural integration. Further, the rise in popularity of materials such as perovskite and perovskite/silicon tandem cells, which are now being produced at large scales, increases the need for precision in photovoltaic inspections. “Unlike traditional silicon solar panels, which typically do not require spectral measurements for quality control, perovskite-based technologies benefit significantly from hyperspectral imaging,” Photon etc.’s Verhaegen said. “This technology enables the assessment of electrical performance, defect detection, and layer thickness in these advanced solar cells, ensuring higher efficiency and reliability.” Photon etc. uses what it calls both “macro-” and “microscopic” hyperspectral imaging to map electroluminescence and photoluminescence, identify defects, and analyze compositional inhomogeneities and degradation processes across large sample areas. These detailed analyses contribute to the development of more efficient and reliable solar energy solutions. From emerging to essential Hyperspectral imaging’s future in manufacturing is technically robust and, increasingly, within reach. As hardware costs fall and integration becomes simpler, this technology is moving beyond niche applications into mainstream use. Its utility to detect, identify, and quantify materials with high spatial and chemical accuracy makes it invaluable in sectors where traditional machine vision and/or human inspection fall short. The final hurdle to a broader adoption is confidence, which is poised to grow through continued collaboration. As trust in the technology builds, so too will economies of scale, further accelerating adoption.
