SWIR Camera Lens for Composite Material Inspection: Resin Distribution, Fiber Variation, Voids and Layer Non-Uniformity

Composite materials are engineered to obtain properties that a single constituent cannot provide on its own, but the same multi-material structure that creates high strength, low weight, thermal stability or tailored mechanical performance also makes quality inspection difficult. A composite panel, laminate, prepreg, molded component or reinforced polymer can appear visually acceptable while containing uneven resin distribution, fiber-rich or resin-rich regions, local material variation, insufficient impregnation, trapped moisture, selected void-like regions, layer irregularity or areas whose optical response differs from the validated structure. 900–1700 nm SWIR imaging for composite material inspection can provide useful additional information because polymers, resins, moisture-containing regions and some constituent materials interact differently with short-wave infrared radiation. When these differences create sufficient spectral contrast, SWIR imaging can help manufacturers evaluate material distribution and spatial uniformity that may not be obvious in conventional visible inspection.

The most important engineering principle is that a SWIR camera lens does not automatically make every defect inside every composite visible. Composite inspection performance depends on resin chemistry, reinforcement material, laminate thickness, surface finish, pigment, wavelength, scattering, defect depth, illumination geometry, required field of view and the smallest abnormal region that must be detected. The dedicated Kyptec Automation® SWIR Camera Lens collection provides 8.5 mm, 12.5 mm, 25 mm, 35 mm and 50 mm focal-length options for 900–1700 nm industrial imaging. The current Kyptec Automation® SWIR portfolio is built around 2 MP resolution, 2/3-inch sensor format, F1.4 aperture and C-Mount, giving machine builders several optical geometries for broad composite-sheet inspection, controlled laminate analysis and localized high-detail quality verification.

Composite Inspection Should Begin With the Material Architecture

A composite is not one homogeneous optical object. It may contain resin, reinforcing fibers, fillers, surface films, coatings, adhesives, core materials and several stacked plies. Each constituent can contribute differently to the SWIR image, and the depth from which useful information originates depends on absorption and scattering inside the complete structure. The first task should therefore be to define exactly what the machine must detect: resin-rich regions, resin starvation, non-uniform reinforcement, missing material, local impregnation failure, a near-surface void-like region, moisture ingress or another specific process abnormality.

This is fundamentally different from asking whether SWIR can “see inside composites.” A more useful engineering question is whether the target defect changes the SWIR signal enough to remain distinguishable from normal material variation. The system should be built around that measurable difference.

Resin Distribution Can Produce Spatial SWIR Contrast

Resin systems contain molecular structures that can interact strongly with selected SWIR wavelengths. When the amount of resin within the optically sampled volume changes, reflected or transmitted intensity can also change. A resin-rich area may therefore produce a different response from a fiber-rich or resin-starved region if the spectral difference is sufficiently strong.

This makes resin distribution inspection a promising use of SWIR imaging. Instead of measuring only one average value from the component, the camera can create a spatial map showing how the resin-sensitive response varies across the surface. The machine can then identify gradual gradients, isolated abnormal zones, repeated streaks or edge-related process variation.

The relationship should always be calibrated against known material conditions. A darker SWIR region should not automatically be labelled resin-rich because thickness, surface angle, moisture and reinforcement orientation can also influence intensity.

Resin-Rich and Resin-Starved Regions Require Different Reference Samples

A strong inspection system should include intentionally manufactured reference regions representing normal resin content, low-resin conditions and excessive resin where practical. Those samples allow the machine builder to determine whether the SWIR feature changes monotonically with resin fraction or whether the response becomes nonlinear.

If normal production allows a limited resin-content range, most calibration samples should be concentrated around those boundaries. Dramatically resin-rich and resin-starved samples may be easy to distinguish but do not prove that the system can detect smaller deviations close to the acceptance limit.

Fiber Distribution Can Affect Both Material Signal and Scattering

Reinforcement fibers influence SWIR images through their own optical properties and through their effect on scattering. A region containing a higher fiber fraction can therefore behave differently from a resin-dominated region even when visible colour is similar. Fiber orientation may also influence apparent texture and reflection.

For automated fiber distribution inspection, the machine should distinguish between changes caused by fiber concentration and changes caused merely by orientation. Reference panels should therefore include the normal range of layup angles and reinforcement patterns. A classification system trained only on one orientation can incorrectly interpret an acceptable rotated fiber structure as material non-uniformity.

Fiber Orientation and Fiber Fraction Are Not the Same Defect

A composite can have the correct quantity of reinforcement but incorrect orientation, or correct orientation but uneven fiber fraction. These should not be grouped into one generic “fiber defect” class. SWIR intensity may respond strongly to one and weakly to the other depending on the material system.

Where orientation is important, spatial texture and directional features can complement spectral response. Where fiber-to-resin ratio is the main concern, calibrated regional intensity or wavelength ratios may be more valuable. The inspection architecture should reflect the actual manufacturing risk.

Prepreg Inspection Can Benefit From Resin and Moisture Sensitivity

Prepreg materials require controlled resin content and storage condition before layup. Localized resin variation, handling contamination or moisture uptake can affect subsequent processing. SWIR imaging can potentially provide a non-contact method for comparing the optical uniformity of prepreg sheets before further manufacturing.

The objective should not be to infer every chemical property from one image. Instead, the system can compare production material against a validated acceptable population and identify zones whose SWIR response differs enough to warrant rejection or secondary inspection. This can be valuable for wide sheets where one small abnormal region might otherwise be missed by point sampling.

Wide Composite Sheets Require a Lens That Preserves Defect Sampling

For broad composite panels, prepreg webs or continuous reinforced sheets, the Kyptec Automation® KL-1408 8.5 MM SWIR Camera Lens can be evaluated where large field coverage is required. The verified product page specifies 8.5 mm focal length, 900–1700 nm wavelength range, 2 MP resolution, F1.4 aperture, 2/3-inch sensor format and C-Mount.

The engineering limit is the smallest relevant abnormal region. If a very wide field causes a 2 mm resin-starved patch to occupy only a few pixels, its signal can become mixed with surrounding normal material. Broad coverage is therefore valuable only when the required defect remains adequately represented.

Object-Side Sampling Determines Whether Local Non-Uniformity Survives

Consider a 600 mm-wide composite sheet captured across 1600 horizontal pixels. The sampling is approximately 0.375 mm per pixel. A 6 mm abnormal region spans around 16 pixels before optical blur is considered, while a 1 mm region occupies fewer than three pixels. The second defect is far more likely to disappear through averaging.

This is why minimum detectable composite defect size should be specified before selecting the lens. The widest possible FOV is not automatically the strongest inspection configuration.

Layer Non-Uniformity Can Create a Combined Optical Response

A laminate contains multiple plies, and the camera may observe a combined response from several layers rather than one isolated depth. If one ply becomes thicker, thinner, locally absent or compositionally different, the overall SWIR signal may shift. Whether that change is detectable depends on how strongly the affected layer contributes to the measured optical path.

The machine should therefore distinguish between detecting abnormal laminate structure and measuring the exact thickness of an individual buried layer. The former may be achievable with comparatively simple imaging when the abnormality creates enough contrast; the latter can require much stronger calibration and material-specific modelling.

Missing Ply and Misplaced Layer Inspection Require Material Contrast

If two neighboring plies have sufficiently different SWIR behaviour, a missing or substituted layer may change the combined image response. However, if all plies are made from nearly identical materials and the missing layer produces only a small thickness change, the defect may be difficult to detect.

Reference samples containing known missing or misplaced layers should therefore be used whenever this is an important production requirement. Simulated defects are much more informative than assuming detectability from general material properties.

Voids Should Be Treated as an Optical Contrast Problem

A void changes the local material structure by replacing solid material with air or another phase. Whether SWIR imaging detects it depends on void size, depth, laminate transparency, surrounding resin and reinforcement, and illumination geometry. Near-surface or larger void-like regions may alter local reflection, scattering or transmission sufficiently to become visible, while deeply buried microscopic voids may not.

For this reason, SWIR void detection in composites should always be expressed in terms of validated defect capability. The system should be tested using known void sizes and depths close to the manufacturing acceptance limit rather than relying on broad statements that SWIR can reveal all internal voids.

A Void Can Affect a Larger Region Than Its Physical Size

The optical signature around a void may extend beyond the exact physical cavity because local resin distribution, surface deformation or scattering changes around the defect. Consequently, the measured SWIR feature may be larger than the actual void.

This can help detection, but it also means the machine should not automatically convert apparent image diameter into physical void diameter. If quantitative sizing is required, the relationship between optical feature and actual defect dimensions must be calibrated separately.

Porosity and Discrete Voids Are Different Inspection Problems

Distributed porosity creates many small air inclusions and may alter average scattering or transmission over a region, while a discrete void produces a localized defect. One algorithm may therefore monitor regional texture or spectral response for porosity-like conditions while another searches for connected localized abnormalities.

The acceptance criteria should reflect the manufacturing specification. A composite with acceptable average material response can still contain one unacceptable local void, while a void-free region can still show excessive distributed porosity.

Reflection Geometry Is Often Practical for Composite Surfaces

Where the part is thick or only one side is accessible, reflection-based SWIR imaging is usually easier to integrate. Illumination strikes the composite and the camera records returned radiation. This geometry can be sensitive to resin distribution, surface-near material differences and selected subsurface effects.

The challenge is surface reflection. Glossy resin, polished laminate or release-film surfaces can generate specular highlights that overwhelm subtle material contrast. Illumination angle and camera position should therefore be chosen to reduce direct glare while preserving useful SWIR return.

Transmission Geometry Can Reveal More Through Suitable Thin Laminates

When the composite is sufficiently transmissive and optical access exists on both sides, transmission imaging can allow SWIR radiation to sample a larger fraction of the laminate thickness. This can increase sensitivity to internal layer differences or selected void-like regions.

Transmission becomes progressively more difficult as the structure grows thicker or contains highly absorbing reinforcement. The actual laminate should therefore be tested at its maximum production thickness before transmission is selected as the final architecture.

Composite Thickness Changes the Apparent Spectral Response

Even a perfectly uniform material can look different when laminate thickness changes. A thicker optical path may increase absorption and scattering, causing lower transmission or altered reflectance. If a machine compares components of several thicknesses using one global threshold, legitimate product variation can appear defective.

The system should therefore either maintain thickness-specific recipes or prove that its chosen normalized feature remains stable across the approved thickness range.

The Kyptec Automation® KL-1410 Can Balance Panel Coverage and Local Defect Detail

For medium-width laminate regions, the Kyptec Automation® KL-1410 12.5 MM SWIR Camera Lens can provide a balanced optical configuration. Its verified specification includes 12.5 mm focal length, 900–1700 nm operation, 2 MP resolution, 2/3-inch format, F1.4 aperture and C-Mount.

This can be useful when an OEM needs to capture a meaningful laminate area while maintaining more pixels across localized resin or reinforcement abnormalities than a broader configuration would provide.

A 25 mm SWIR Lens Can Support Controlled Composite Analysis Zones

Where one smaller composite region should occupy a larger part of the sensor, the Kyptec Automation® KL-1412 25 MM SWIR Camera Lens can be evaluated for tighter framing. This can be particularly useful for inspecting critical bond zones, local laminate transitions, material coupons or narrow production strips where spatial detail is more important than overall panel coverage.

The 25 mm focal length does not make a void or resin variation inherently more visible. Its advantage is to allocate more sensor sampling to the physical region containing the defect.

Resin Cure State Can Influence SWIR Response but Requires Dedicated Validation

Chemical changes during resin curing can alter material optical properties, but the exact magnitude and direction depend on resin formulation and process conditions. A SWIR composite inspection system may therefore be able to distinguish defined cure-state populations when a repeatable spectral difference exists.

This should not be confused with universal cure measurement. The machine must be calibrated using actual under-cured, correctly cured and over-processed samples where those conditions are relevant. Temperature and surface condition should also be controlled because they can shift the response.

Moisture Inside Composites Can Become a Confounding or Useful Signal

Water has strong SWIR absorption, so moisture trapped in or absorbed by composite material can produce significant contrast. This can be beneficial when moisture ingress itself is a defect, but it can become a confounding variable when the system is intended primarily to measure resin distribution.

A resin-rich region and a wetter region may both become darker at certain wavelengths. Multi-wavelength analysis can help separate these effects if the material provides enough independent spectral information. Validation should deliberately include realistic moisture variation rather than discovering it during production.

Fiber-Reinforced Polymer Inspection Should Include Surface Finish Variation

Composite components may be matte, glossy, machined, molded, coated or covered with release-film texture. These finishes can change how SWIR illumination is reflected. A calibration trained only on one pristine finish may therefore fail after normal manufacturing variation is introduced.

The good-product population should include realistic surface states, and the classifier should rely on material-sensitive features that remain stable across acceptable finish variation wherever possible.

Edge Regions Should Be Qualified Separately

Composite edges often contain exposed layer boundaries, resin accumulation, trimming marks or geometric curvature that differs from the central panel. A uniform threshold across the complete image can therefore create false defects near edges.

A stronger system defines separate regions for central laminate, edges, holes, corners and known structural transitions. Each zone can use acceptance logic appropriate to its normal optical response.

Fiber Wrinkles and Waviness May Require Texture Analysis

Fiber waviness can change directional image texture even if overall composition remains correct. SWIR material contrast alone may therefore be insufficient; spatial processing can help identify orientation changes or localized reinforcement disturbance.

Directional filters, local texture statistics or edge orientation measurements can complement the spectral image. The strongest machine-vision approach combines material-sensitive SWIR information with the geometric pattern produced by the defect.

Multi-Wavelength Imaging Can Separate Resin, Moisture and Reinforcement Effects

A single wavelength may show strong contrast but provide limited information about its cause. If a resin-rich region and a moisture-rich region both appear dark, examining their relative response at a second wavelength can improve discrimination.

A ratio such as R = I₁/I₂ can help suppress common illumination variation while emphasizing the different spectral behaviour of materials. Additional wavelengths should be added only when they improve separation of the hardest defect pair. More bands increase system complexity and should not replace strong material testing.

Flat-Field Correction Is Important Across Large Composite Panels

Wide-field illumination is rarely perfectly uniform. If the left side of a panel receives 10% more SWIR energy than the right, a raw-intensity algorithm can interpret that difference as a material gradient.

Dark correction and flat-field normalization can reduce fixed detector and illumination variation. A spatially uniform reference should be captured using the same wavelength and optical configuration used for production. This becomes especially important when the purpose is to detect gradual resin distribution changes across a broad sheet.

Long Focal Lengths Can Help Around Large Composite Manufacturing Equipment

Composite processing equipment can include presses, molds, rollers, heating zones and robotic handling that limit camera placement. The Kyptec Automation® KL-1414 35 MM SWIR Camera Lens and Kyptec Automation® KL-1416 50 MM SWIR Camera Lens provide narrower focal-length options for inspection stations where a controlled field must be viewed from additional stand-off.

These longer focal lengths are particularly useful when the target is a defined laminate zone rather than an entire large sheet. Their value is geometric rather than spectral: they allow the OEM to maintain tighter framing while keeping the camera away from process hardware.

F1.4 Can Help When Composite Attenuation Reduces Available Signal

Some laminates can attenuate SWIR radiation substantially, particularly in transmission or narrowband configurations. The F1.4 maximum aperture available across the current Kyptec Automation® SWIR lens family can provide useful photon collection when exposure time is limited.

The final aperture still needs to balance signal against depth of field. Curved molded parts or panels with dimensional variation may require additional focus tolerance, so maximum aperture should not be selected automatically.

Process Monitoring Can Be More Valuable Than Final Defect Sorting

A composite SWIR inspection system can reveal how material distribution changes during manufacturing rather than merely sorting finished parts. If resin response gradually changes across consecutive panels, the system may indicate process drift before the product exceeds final limits.

Spatial and temporal trends can therefore be used for statistical process monitoring. Cross-web gradients, recurring resin-rich zones, periodic reinforcement anomalies or increasing moisture response can help production engineers identify a developing process problem sooner.

Acceptance Criteria Should Be Defined in Physical Manufacturing Terms

A useful inspection specification should state the smallest resin-starved area, maximum permitted regional variation, minimum void-like region, acceptable fiber distribution tolerance or maximum out-of-family area. Phrases such as “detect composite defects” are too broad to engineer reliably.

Once the physical defect is defined, the optical system can be qualified using representative samples around that boundary. This converts SWIR imaging from an exploratory technique into a measurable production inspection.

Why Kyptec Automation® Is a Strong Optical Platform for Composite Material Inspection

The Kyptec Automation® SWIR Camera Lens collection provides machine builders with 8.5 mm, 12.5 mm, 25 mm, 35 mm and 50 mm focal-length options for 900–1700 nm industrial imaging. Verified current product information confirms representative models with 2 MP resolution, 2/3-inch sensor format, F1.4 aperture and C-Mount.

That breadth is particularly useful for composite manufacturing because inspection geometries vary from wide prepreg sheets and laminate panels to narrow critical zones and localized molded-component features. Kyptec Automation® gives OEMs a focused SWIR optical family that can be selected according to material width, defect size, machine stand-off and required sampling while keeping the wavelength architecture consistent across different inspection stations.

Frequently Asked Questions About SWIR Composite Material Inspection

1. Can SWIR detect uneven resin distribution in composite materials?

Potentially, yes. If resin concentration changes the 900–1700 nm response sufficiently relative to the reinforcement and normal process variation, an SWIR image can reveal spatial differences associated with resin-rich or resin-starved regions. The relationship should be calibrated using known reference laminates rather than assigning resin content directly from image darkness.

2. Can SWIR identify resin-starved areas before a composite part is finished?

Potentially, particularly in prepreg, partially processed or optically accessible laminate stages where resin distribution influences the measured SWIR signal. Inspection earlier in the process can be valuable because abnormal regions can potentially be identified before additional manufacturing value is added.

3. Can a SWIR camera lens detect fiber-rich regions in a laminate?

It may, when changing fiber-to-resin ratio produces a repeatable spectral or scattering difference. Fiber orientation can also alter the image, so calibration samples should include acceptable orientation variation to prevent normal reinforcement direction from being mistaken for an abnormal fiber fraction.

4. Can SWIR detect fiber waviness?

SWIR can potentially reveal fiber-related texture or directional changes when the reinforcement contributes enough optical structure to the image. Detecting waviness normally requires spatial or texture analysis in addition to spectral intensity because the defect concerns orientation as much as composition.

5. Can SWIR detect voids inside composite laminates?

Some void-like regions can be detected if they are sufficiently large, sufficiently near the optically accessible region and create adequate contrast. Deep microscopic voids in strongly absorbing or scattering laminates may not be visible. Minimum void capability should therefore be established using known reference defects.

6. Does SWIR detect porosity the same way it detects a large void?

Not necessarily. Distributed porosity may alter average scattering or regional optical response, while a discrete void creates a localized feature. The algorithms and acceptance metrics for these two defect types can therefore be different.

7. Can SWIR inspect multiple layers inside a composite laminate?

Potentially, but SWIR usually records the combined optical contribution of the layers accessible at the selected wavelength. It should not automatically be assumed that each buried ply can be measured independently. Missing or abnormal layers are easiest to detect when they create a strong difference in the total optical response.

8. Can SWIR detect a missing ply in a composite laminate?

Possibly, particularly when the missing ply causes a meaningful change in material composition, optical thickness or reinforcement structure. A known missing-ply sample should be inspected during development because detectability depends strongly on laminate design and defect depth.

9. How does composite thickness affect SWIR inspection?

Increasing thickness generally increases the amount of material interacting with the radiation and can reduce transmission while changing reflectance and scattering. A model developed on one thickness should not automatically be applied to substantially thicker or thinner parts unless that transfer has been validated.

10. Can moisture interfere with resin-distribution inspection?

Yes. Water can create strong SWIR absorption and may change the same image regions used to estimate resin variation. If moisture is a realistic production variable, it should be included during calibration so the algorithm can distinguish or compensate for it.

11. Can SWIR inspect carbon-based or highly absorbing composite structures?

Highly absorbing reinforcement can severely limit penetration and transmission, making internal inspection more difficult. SWIR may still provide useful surface or near-surface information depending on the material, but capability should be established on the actual composite rather than assumed from generic composite terminology.

12. Is reflection or transmission better for composite inspection?

Reflection is often easier for thick components and one-sided machine access, while transmission can provide stronger through-thickness information for sufficiently transmissive thin laminates. The correct geometry depends on laminate thickness, reinforcement, target defect depth and available machine access.

13. When is the Kyptec Automation® KL-1408 useful for composite inspection?

The Kyptec Automation® KL-1408 8.5 MM SWIR Camera Lens can be evaluated when broad sheets, prepreg webs or larger laminate regions must be imaged in one field. The OEM should confirm that the smallest critical resin or fiber abnormality remains large enough in pixels at the selected FOV.

14. When can the Kyptec Automation® KL-1412 be useful for composite defect inspection?

The Kyptec Automation® KL-1412 25 MM SWIR Camera Lens can be useful when one controlled region should occupy more of the sensor. This can improve spatial sampling for localized resin variation, ply abnormalities or selected void-like regions without implying deeper material penetration.

15. Does a longer focal length let SWIR see deeper into a composite?

No. Penetration depth is governed mainly by wavelength and material absorption and scattering. Longer focal length changes field of view and image scale. It can help a small defect occupy more pixels but does not inherently make SWIR radiation penetrate farther into the laminate.

16. Can one SWIR inspection recipe work for different composite layups?

It should not be assumed. Different ply counts, reinforcement orientations, resin systems and laminate thicknesses can change the optical response significantly. Each approved layup should be validated, and separate inspection recipes may be necessary.

17. Can SWIR monitor composite resin distribution continuously during manufacturing?

Potentially, yes, when the material is optically accessible and the process presents it consistently. Continuous imaging can track spatial resin-sensitive metrics across successive sheets or web positions and provide early warning of developing process non-uniformity.

18. How should I define the minimum defect size for SWIR composite inspection?

Define the smallest resin-starved region, fiber anomaly, void-like area or layer non-uniformity that has a real effect on product acceptance. Then calculate how many sensor pixels represent that physical size at the proposed field of view. The defect should have enough sampling to survive optical blur, noise and material variability.

19. What information should I provide before selecting a SWIR camera lens for composite inspection?

Provide the composite type, resin and reinforcement system, laminate thickness, target defect, minimum defect dimensions, inspection width, required FOV, working distance, sensor format, part speed, whether reflection or transmission is possible and the available mounting space. These inputs allow focal length to be selected around the actual quality-control problem.

20. Why is Kyptec Automation® a strong choice for SWIR composite material inspection?

Kyptec Automation® offers a dedicated SWIR Camera Lens collection spanning 8.5 mm, 12.5 mm, 25 mm, 35 mm and 50 mm focal lengths for 900–1700 nm imaging. Current verified product information confirms representative models with 2 MP resolution, 2/3-inch sensor format, F1.4 aperture and C-Mount. This gives composite-equipment OEMs useful flexibility to design broad web inspection, medium-field laminate analysis, tightly framed defect inspection or longer-working-distance stations within one focused SWIR optical portfolio.

Conclusion

A SWIR camera lens for composite material inspection becomes most valuable when the manufacturing requirement concerns material distribution and hidden optical variation rather than surface appearance alone. Resin-rich regions, resin starvation, reinforcement variation, selected void-like defects, laminate inconsistencies and moisture-related abnormalities can potentially change the 900–1700 nm response of a composite in ways that provide useful automated inspection contrast. The strength of that contrast, however, depends entirely on the actual resin system, reinforcement, laminate thickness, defect depth and optical geometry, which means every application should begin with representative material testing rather than broad assumptions about SWIR penetration.

The strongest engineering process is to define each failure mode separately. Resin distribution should be calibrated against known resin-content conditions; fiber variation should be distinguished from normal orientation; missing or irregular layers should be tested with representative laminate structures; void-like regions should be qualified by size and depth; and moisture variation should be included deliberately because it can either be a useful defect signal or a confounding variable. Reflection and transmission geometries should be compared where possible, and the minimum commercially significant defect should determine the required object-side sampling.

The Kyptec Automation® SWIR Camera Lens collection provides a strong optical foundation for building these systems because the current family spans 8.5 mm, 12.5 mm, 25 mm, 35 mm and 50 mm focal lengths across 900–1700 nm. Shorter focal lengths can support wider prepreg or laminate inspection, intermediate optics can balance panel coverage with local defect resolution, and longer focal lengths can concentrate sensor sampling on smaller high-value regions or support additional machine stand-off. With representative models specified around 2 MP resolution, 2/3-inch format, F1.4 aperture and C-Mount, Kyptec Automation® provides OEMs with a focused SWIR lens portfolio that can be matched to very different composite-manufacturing geometries without resorting to product-model stuffing.

For composite-equipment manufacturers and industrial buyers, the central design principle is therefore to prove which material or structural variation creates usable SWIR contrast, define the smallest unacceptable region, and then choose the SWIR camera lens so that the defect remains both spectrally distinguishable and spatially resolved under real production conditions. When resin chemistry, reinforcement architecture, wavelength, laminate thickness, FOV, working distance, illumination and process variability are engineered together, Kyptec Automation® SWIR Camera Lenses provide a technically strong platform for automated inspection of resin distribution, fiber variation, selected void-like regions and layer non-uniformity in demanding composite manufacturing environments.