Achieving high processing quality for chemical mechanical planarization (CMP) in semiconductor manufacturing is difficult due to the distinct process variations associated with this method, such as drift and shift. Run-to-run control aims to maintain the targeted process quality by reducing the effect of process variations. The goal of controller learning is to infer an underlying output–input reverse mapping based on input–output samples considering the process variations. Existing controllers learn reverse mapping by minimizing the total mapping error for sample data. However, this approach often fails to generate inputs for unseen target outputs because conditional input distributions on target outputs are not captured in the learning. In this study, we propose a controller based on a least squares generative adversarial network (LSGAN) that can capture the input distributions. GANs are deep-learning architectures composed of two neural nets: a generator and a discriminator. In the proposed model, the generator attempts to produce fake input distributions that are similar to the real input distributions considering the process variation features extracted using convolutional layers, while the discriminator attempts to detect the fake distributions. Competition in this game drives both networks to improve their performance until the generated input distributions are indistinguishable from the real distributions. An experiment using the data obtained from a work-site CMP tool verified that the proposed model outperformed the comparison models in terms of control accuracy and computation time.
Due to the advancement of wireless internet and mobile positioning technology, the application of location-based services (LBSs) has become popular for mobile users. Since users have to send their exact locations to obtain the service, it may lead to several privacy threats. To solve this problem, a cloaking method has been proposed to blur users’ exact locations into a cloaked spatial region with a required privacy threshold (k). With the cloaked region, an LBS server can carry out a k-nearest neighbor (k-NN) search algorithm. Some recent studies have proposed methods to search k-nearest POIs while protecting a user’s privacy. However, they have at least one major problem, such as inefficiency on query processing or low precision of retrieved result. To resolve these problems, in this paper, we propose a novel k-NN query processing algorithm for a cloaking region to satisfy both requirements of fast query processing time and high precision of the retrieved result. To achieve fast query processing time, we propose a new pruning technique based on a 2D-coodinate scheme. In addition, we make use of a Voronoi diagram for retrieving the nearest POIs efficiently. To satisfy the requirement of high precision of the retrieved result, we guarantee that our k-NN query processing algorithm always contains the exact set of k nearest neighbors. Our performance analysis shows that our algorithm achieves better performance in terms of query processing time and the number of candidate POIs compared with other algorithms. 相似文献
The upper and lower limits of the electrostrictive constants, dielectric permittivities, spontaneous polarizations, and piezoelectric coefficients were calculated for ceramic PbTiO(3) from theoretical single-crystal constants. Experimental ceramic data fall between these upper and lower limits. The large piezoelectric anisotropy d(33)/d(31) of ceramic PbTiO(3 ) was shown to be related to the single-crystal PbTiO(3) electrostrictive anisotropies Q(11)/Q(12 ) and Q(44)/Q(12). The possibility of a change in sign of the ceramic d(31) coefficient due to a slight variation in the single-crystal electrostrictive anisotropies was discussed. The single-crystal and predicted ceramic hydrostatic electrostrictive constants were found to be equal. Using this result the ceramic hydrostatic g(h ) coefficient is always smaller than the single-crystal g (h), but the ceramic hydrostatic d(h) coefficient can be either larger or smaller than the single-crystal d(h) depending on the dielectric anisotropy (epsilon (11)/epsilon(33)) of the single-crystal. 相似文献
A modified embedded-atom method (MEAM) interatomic potential for the Fe–H binary system has been developed using previously developed MEAM potentials of Fe and H. The potential parameters were determined by fitting to experimental data on the dilute heat of solution of hydrogen in body-centered cubic (bcc) and face-centered cubic (fcc) Fe, the vacancy–hydrogen binding energy in bcc Fe, and to a first-principles calculation for the lattice parameter and bulk modulus of a hypothetical NaCl-type FeH. The potential accurately reproduces the known physical properties of hydrogen as an interstitial solute element in bcc and fcc Fe. The applicability of the potential to atomistic approaches for investigating interactions between hydrogen atoms and other defects such as vacancies, dislocations and grain boundaries, and also for investigating the effects of hydrogen on various deformation and mechanical behaviors of iron is demonstrated. 相似文献
This research investigated the characteristics of fluid dynamic bearings (FDBs) in a HDD spindle motor with an hourglass-shaped sleeve. We demonstrated experimentally that the hourglass-shaped sleeve generated through the ball-sizing process is a major source of large repeatable runout and non-repeatable runout in a HDD spindle system. We also numerically proved the effect of hourglass-shaped sleeves on pressure, friction torque, stiffness and damping coefficients, critical mass, and shock response. Finally, we proposed a robust design for FDBs with hourglass-shaped groove depths to compensate for the decrease in the static and dynamic performance of FDBs with hourglass-shaped sleeves. The proposed hourglass-shaped groove depth improves the performance of FDBs with both straight and hourglass-shaped sleeves. 相似文献
We develop a miniaturized batch-type screw mixer (BSM) for uniform mixing of polymer resin and nanoparticles, based on the stretching of material elements. This stretching is induced by the combination of recirculating cross-sectional flows in deep channels of the screw and high shear stress developed at flight regions. The BSM is used to produce a polymer nano-composite composed of multi-walled carbon nanotubes and polydimethylsiloxane resin. The mixing performance of the BSM is characterized quantitatively by estimating two different types of mixing efficiencies (i.e., dispersive mixing and distributive mixing) via transmitted light microscope images. The developed BSM highly improves the mixing performance rather than that of a conventional ultrasonic mixing device. 相似文献