117 research outputs found
Continuous modelling of machine tool failure durations for improved production scheduling
Unforeseen machine tool failures due to technical issues can cause downtimes leading to delays during production. To reduce delays, rescheduling of the production is, in most cases, necessary. However, warranting such a change requires reliable knowledge about the duration of the failure. This article presents a method to provide this knowledge by estimating the duration of a machine tool failure based on previous failure durations. Using the cross-industry standard process for data mining (CRISP-DM) and statistical methods, the embedded model for failure classification and duration is continuously improved. The method is thoroughly tested using multiple distributions, parameters and a practical use case. The results show high potential for predicting the duration of machine tool failures, which consequently could lead to improved quality of rescheduling. © 2020, The Author(s)
Cubic boron nitride: a new prospective material for ultracold neutron application
For the first time, the neutron optical wall-potential of natural cubic boron
nitride (cBN) was measured at the ultracold neutron (UCN) source of the
research reactor TRIGA Mainz using the time-of-flight method (TOF). The samples
investigated had a wall-potential of (305 +/- 15) neV. This value is in good
agreement with the result extracted from neutron reflectometry data and
theoretical expectations. Because of its high critical velocity for UCN and its
good dielectric characteristics, cubic boron nitride coatings (isotopically
enriched) will be useful for a number of applications in UCN experiments
Forward modeling of collective Thomson scattering for Wendelstein 7-X plasmas: Electrostatic approximation
In this paper, we present a method for numerical computation of collective Thomson scattering (CTS). We developed a forward model, eCTS, in the electrostatic approximation and benchmarked it against a full electromagnetic model. Differences between the electrostatic and the electromagnetic models are discussed. The sensitivity of the results to the ion temperature and the plasma composition is demonstrated. We integrated the model into the Bayesian data analysis framework Minerva and used it for the analysis of noisy synthetic data sets produced by a full electromagnetic model. It is shown that eCTS can be used for the inference of the bulk ion temperature. The model has been used to infer the bulk ion temperature from the first CTS measurements on Wendelstein 7-X
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