For an emerging market a mass and cost-effective production of non-silicon micro devices requires an in-process and accurate 3D monitoring to assure the quality. Optical coherence tomography (OCT) providing high-resolution contactless imaging is used to inspect the surface quality of a laser-machined alumina ceramic layer. Quantitatively the root mean square (rms) roughness is measured by traditional means and provides input parameters to theMonte Carlosimulation of OCT method. We found that the quality of both free and embedded surfaces of the highly-scattering alumina ceramic material can be evaluated by OCT.

The future ceramic micro processing based on tape stacking requires the development of inspection systems toperform high-resolution in-process quality control of embedded manufactured cavities, metal structures anddefects. This paper presents non-destructive techniques for monitoring processes and controlling the differentsteering parameters. Results are shown for optical coherence tomography (OCT), IR-transmission and reflectionmeasurement, and X-ray micro computed tomography. Suitable working conditions are analyzed to improve thedetection performance.

Large-scale and cost-effective manufacturing of ceramic micro devices based on tape stacking requires the development of inspection systems to perform high-resolution in-process quality control of embedded manufactured cavities, metal structures and defects. With an optical coherence tomography (OCT) system operating at 1.3 mu m and a dedicated automated line segmentation algorithm, layer thicknesses can be measured and laser-machined channels can be verified in alumina ceramics embedded at around 100 mu m depth. Monte Carlo simulations are employed to analyze the abilities of OCT in imaging of the embedded channels. The light scattering parameters required as input data for simulations are evaluated from the integrating sphere measurements of collimated and diffuse transmittance spectra using a reconstruction algorithm based on refined diffusion approximation approach.

Light scattering strongly limits the probing depth and speckles degrade the image quality in optical coherence tomography (OCT) detection of embedded features in high-scattering ceramics. For high-precision metrology application we evaluated an OCT system working at a centre wavelength of 1.7μm in order to improve the probing depth, and developed a dedicated image processing algorithm for improving the measurement accuracy and speed. The results are demonstrated for 3D OCT measurement of embedded laser-machined pattern in ceramics.

Quality inspection of materials is one of modern applications of optical coherence tomography (OCT) featuring non-invasiveness and high speed required for in-production control of such materials as paper and alumina ceramics. Some of materials to be controlled are characterized by high scattering which can introduce distortions to the obtained OCT images, therefore additional interpretation can be required in order to evaluate material quality. In order to understand formation of OCT images of highly scattering materials samples and evaluate OCT potential for their quality inspection Monte Carlo simulations could be employed. This paper discusses application of Monte Carlo technique for simulation of OCT inspection of paper and alumina ceramics samples. Implementation of Monte Carlo simulation allows to evaluate the effect of OCT setup parameters and material properties on formation of the OCT-images. Multilayer models of paper and alumina ceramics structures are involved in the study.

Optical coherence tomography (OCT) is a promising tool for detecting micro channels, metal prints, defects and delaminations embedded in alumina and zirconia ceramic layers at hundreds of micrometers beneath surfaces. The effect of surface roughness and scattering of probing radiation within sample on OCT inspection is analyzed from the experimental and simulated OCT images of the ceramic samples with varying surface roughnesses and operating wavelengths. By Monte Carlo simulations of the OCT images in the mid-IR the optimal operating wavelength is found to be 4 mu m for the alumina samples and 2 mu m for the zirconia samples for achieving sufficient probing depth of about 1 mm. The effects of rough surfaces and dispersion on the detection of the embedded boundaries are discussed. Two types of image artefacts are found in OCT images due to multiple reflections between neighboring boundaries and inhomogeneity of refractive index.

Optical coherence tomography (OCT) is useful for materials defect analysis and inspection with the additional possibility of quantitative dimensional metrology. Here, we present an automated image-processing algorithm for OCT analysis of roll-to-roll multilayers in 3D manufacturing of advanced ceramics. It has the advantage of avoiding filtering and preset modeling, and will, thus, introduce a simplification. The algorithm is validated for its capability of measuring the thickness of ceramic layers, extracting the boundaries of embedded features with irregular shapes, and detecting the geometric deformations. The accuracy of the algorithm is very high, and the reliability is better than 1 mu m when evaluating with the OCT images using the same gauge block step height reference. The method may be suitable for industrial applications to the rapid inspection of manufactured samples with high accuracy and robustness.

Optical coherence tomography (OCT) has proven to be a useful tool for investigating internal structures in ceramic tapes, and the technique is expected to be important for roll-to-roll manufacturing. However, because of high scattering in ceramic materials, noise and speckles deteriorate the image quality, which makes automated quantitative measurements of internal interfaces difficult. To overcome this difficulty we present in this paper an innovative image analysis approach based on volumetric OCT data. The engine in the analysis is a 3D image processing and analysis algorithm. It is dedicated to boundary segmentation and dimensional measurement in volumetric OCT images, and offers high accuracy, efficiency, robustness, subpixel resolution, and a fully automated operation. The method relies on the correlation property of a physical interface and effectively eliminates pixels caused by noise and speckles. The remaining pixels being stored are the ones confirmed to be related to the target interfaces. Segmentation of tilted and curved internal interfaces separated by similar to 10 mu m in the Z direction is demonstrated. The algorithm also extracts full-field top-view intensity maps of the target interfaces for high-accuracy measurements in the X and Y directions. The methodology developed here may also be adopted in other similar 3D imaging and measurement technologies, e.g., ultrasound imaging, and for various materials.