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Conceptually, high-precision manufacturing is a sequence of production and measurement steps, where both kinds of steps require to use non-deterministic models to represent production and measurement tolerances. This paper demonstrates how to effectively represent these manufacturing processes as Partially Observable Markov Decision Processes (POMDP) and derive an offline strategy with state-of-the-art Monte Carlo Tree Search (MCTS) approaches. In doing so, we face two challenges: a continuous observation space and explainability requirements from the side of the process engineers. As a result, we find that a tradeoff between the quantitative performance of the solution and its explainability is required. In a nutshell, the paper elucidates the entire process of explainable production planning: We design and validate a white-box simulation from expert knowledge, examine state-of-the-art POMDP solvers, and discuss our results from both the perspective of machine learning research and as an illustration for high-precision manufacturing practitioners.
The objects of this investigation were sculptures taken from a ca. three hundred years old baroque epitaph of a church in Tonning, a town in Northern Germany. Around 1900 it was found in a disastrous state heavily damaged by wood-worm. At that time, the whole artwork was treated with the tar extract carbolineum as a remedy. Nowadays, this substance has been identified as carcinogenic, and its presence can be perceived by its stench and visually at certain spots on the surface where it has penetrated the covering paint.
A gold-painted sculpture of a massive wooden skull was interrogated with X-rays and fast neutrons to investigate the internal distribution of the carbolineum. The X-ray tomography, with its excellent spatial resolution revealed galleries left over from the worm infestation in the outer areas and cracks in the central region. The golden color coating appeared as a thick and dense layer. In comparison the tomography with fast neutrons, though being of lower resolution and yet unresolved artefacts revealed sections of slightly different densities in the bulk of the wood. These differences we attribute to the differences in the distribution of the impregnant in the wood, visible due to its higher hydrogen content making it less transparent for neutrons.
In the context of the German aviation security research and development project SILUFRA (secure air freight transport chains), BAM has developed a high-resolution and high-energy X-ray imaging technology for the reliable detection of dangerous and illicit materials in densely packed air freight containers. In the developed technology, a novel combination of high-energy (2-7.5 MeV) X-ray betatron as the radiation source and a high-resolution digital detector array (DDA) for the X-ray imaging was utilized to improve the probability of detecting contraband and explosive materials by enhancing the spatial and contrast resolution in the digital X-ray image. In addition, flexible rotations of the high-energy X-ray source and the digital detector array can lead to clarify the suspicious region of interest (ROI) in air freight containers efficiently. Thus, reduces the false alarm rates and the need for expensive manual inspections of the whole container load. In order to evaluate the detection efficiency, we carried out the experimental investigations on a real air freight container loaded with typical cargo materials such as heavy automobile components and electronic products as well as mock-up dangerous and contraband materials. Furthermore, the material discrimination in the radiographic images was evaluated based on the dual high-energy X-ray imaging method. Finally, important applications of the proposed imaging technology to the air cargo security are discussed
Radiologic evaluation techniques are nondestructive testing (NDT) used to detect the bulk of explosives and contraband materials in large objects. As compared to conventional low-energy (<450 key) X-ray imaging, high-energy (>1 MeV) digital X-ray radiography is required for the NOT of large containers because of the need for high penetration through thick materials, sensitivity, and the ability to distinguish between low-and high-Z materials. Mobile, high-energy, and high-resolution radiologic techniques are useful to detect contraband and threat materials in digital radiographic images of containers with complex packing. This paper presents a mobile, high-energy X-ray radiographic technique for the in-field nondestructive inspection of cargo containers. The developed experimental technique consisted of a betatron as a high-energy (7.5 MeV) X-ray source and a high-resolution (400 mu m) matrix detector for the digital X-ray imaging. In order to evaluate the detection efficiency and image quality of the measurement technique, a test specimen was proposed that was made of a 3 mm thick steel container with an inner dimension of 60 x 30 x 40 cm(3) comprising different low-and high-Z materials. Image quality indicators were used to assess the essential image quality parameters such as image basic spatial resolution, effective attenuation coefficient, and signal-to-noise ratio (SNR). Experimental investigations were performed on a 6.1 m sea freight container with mockup dangerous materials in complex packing. Preliminary experimental results showed that the proposed technique was able to distinguish between liquids and solids, as well as detect contraband materials. Furthermore, a remarkable SNR of 400 was achieved in the measured digital X-ray images. The influence of temperature on X-ray radiation dose rate at different X-ray energies was also investigated. Finally, important applications of the proposed technique in the context of maritime security are discussed.