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Programming of adaptive repair process chains using repair features and function blocks
Spocker, Gunter,Schreiner, Thorsten,Huwer, Tobias,Arntz, Kristian Society for Computational Design and Engineering 2016 Journal of computational design and engineering Vol.3 No.1
The current trends of product customization and repair of high value parts with individual defects demand automation and a high degree of flexibility of the involved manufacturing process chains. To determine the corresponding requirements this paper gives an overview of manufacturing process chains by distinguishing between horizontal and vertical process chains. The established way of modeling and programming processes with CAx systems and existing approaches is shown. Furthermore, the different types of possible adaptions of a manufacturing process chain are shown and considered as a cascaded control loop. Following this it is discussed which key requirements of repair process chains are unresolved by existing approaches. To overcome the deficits this paper introduces repair features which comprise the idea of geometric features and defines analytical auxiliary geometries based on the measurement input data. This meets challenges normally caused by working directly on reconstructed geometries in the form of triangulated surfaces which are prone to artifacts. Embedded into function blocks, this allows the use of traditional approaches for manufacturing process chains to be applied to adaptive repair process chains.
Minsuk Oh,Wonhee Cho,Dong Hoon Lee,Kara M. Whitaker,Pamela J.Schreiner,James G. Terry,Joon Young Kim 한국역학회 2022 Epidemiology and Health Vol.45 No.-
OBJECTIVES: We examined whether pericardial adipose tissue (PAT) is predictive of prediabetes and type 2 diabetes over time. METHODS: In total, 2,570 adults without prediabetes/diabetes from the Coronary Artery Risk Development in Young Adults Study were followed up over 15 years. PAT volume was measured by computed tomography scans, and the new onset of prediabetes/diabetes was examined 5 years, 10 years, and 15 years after the PAT measurements. Multivariable Cox regression models were used to examine the association between the tertile of PAT and incident prediabetes/diabetes up to 15 years later. The predictive ability of PAT (vs. waist circumference [WC], body mass index [BMI], waist-to-height ratio [WHtR]) for prediabetes/diabetes was examined by comparing the area under the receiver operating characteristic curve (AUC). RESULTS: The highest tertile of PAT was associated with a 1.56 times (95% confidence interval [CI], 1.03 to 2.34) higher rate of diabetes than the lowest tertile; however, no association was found between the highest tertile of PAT and prediabetes in the fully adjusted models, including additional adjustment for BMI or WC. In the fully adjusted models, the AUCs of WC, BMI, WHtR, and PAT for predicting diabetes were not significantly different, whereas the AUC of WC for predicting prediabetes was higher than that of PAT. CONCLUSIONS: PAT may be a significant predictor of hyperglycemia, but this association might depend on the effect of BMI or WC. Additional work is warranted to examine whether novel adiposity indicators can suggest advanced and optimal information to supplement the established diagnosis for prediabetes/diabetes.