Simulation and optimization of tool-life in manufacturing centers

This paper presents the development of an optimization and a computer-simulation model to evaluate the process plans of a manufacturing center by analyzing the effect of tool failure on system performance. The GPSS/PC simulation program that is used in this study has been built with variables, functions and matrices so that many experiments could be conducted with the model. Sensitivity analysis is presented and the developed model has proven to be useful in determining optimum sequencing of parts for various operating policies.     

Polyaniline-multiwalled carbon nanotube composites: Characterization by WAXS and TGA

Polyaniline/carboxylated multi-walled carbon nanotube (PAni/c-MWNT) nanocomposites have been synthesized by micellar aided emulsion polymerization with various c-MWNTs compositions, viz., 0.5, 1, 5, and 10 wt %. The microcrystalline parameters such as the nanocrystal size (〈N〉), lattice strain (g), interplanar distance (d_hkl), width of the crystallite size distribution, surface weighted crystal size (D_s), and volume of the ordered regions were calculated from the X-ray data by using two mathematical models, namely the Exponential distribution and Reinhold distribution methods. The effects of heat ageing on the microcrystalline parameters of the PAni/c-MWNT nanocomposites were also studied and the results are correlated. The thermal stability and electrical resistivity of the PAni/c-MWNT nanocomposites were examined with thermogravimetric analysis (TGA) and a conventional two-probe method. The TGA data indicate that the thermal stability of the nanocomposites improved after the incorporation of c-MWNTs. The influence of temperature on the resistivity of the nanocomposites was also measured. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci 2008     

Robust design of processes and products using the mathematics of the stochastic frontier (SF)

The International Journal of Advanced Manufacturing Technology - The paper discusses a generic procedure for the parameter design of product and process development using planned and non-planned...     

PriorVAE: encoding spatial priors with variational autoencoders for small-area estimation

Gaussian processes (GPs), implemented through multivariate Gaussian distributions for a finite collection of data, are the most popular approach in small-area spatial statistical modelling. In this context, they are used to encode correlation structures over space and can generalize well in interpolation tasks. Despite their flexibility, off-the-shelf GPs present serious computational challenges which limit their scalability and practical usefulness in applied settings. Here, we propose a novel, deep generative modelling approach to tackle this challenge, termed PriorVAE: for a particular spatial setting, we approximate a class of GP priors through prior sampling and subsequent fitting of a variational autoencoder (VAE). Given a trained VAE, the resultant decoder allows spatial inference to become incredibly efficient due to the low dimensional, independently distributed latent Gaussian space representation of the VAE. Once trained, inference using the VAE decoder replaces the GP within a Bayesian sampling framework. This approach provides tractable and easy-to-implement means of approximately encoding spatial priors and facilitates efficient statistical inference. We demonstrate the utility of our VAE two-stage approach on Bayesian, small-area estimation tasks.     

Efficient recursive least squares parameter estimation algorithm for accurate nanoCMOS variable gain amplifier performances

ABSTRACT

With the aggressive scaling of integrated circuit technology, parametric estimation is a critical task for designers who looked for solutions to the challenges of some Nanoscale CMOS parameters. This paper presented the prediction of primary parameters of CMOS transistor for 16 nm to 10 nm process nodes using both of Bisquare Weights (BW) method and a novel recursive least squares (RLS) parameter estimation algorithm. The proposed RLS algorithm consists of the minimisation of a quadratic criterion relating to the prediction error in order to attain the best estimated parameters of the developed mathematical model. The obtained results thanks to the proposed RLS algorithm were better than those reached using the BW method. Comparisons between Predictive Technology Model (PTM) data and parameters estimated with RLS algorithm were made to check the validity and the consistency of the proposed algorithm. These predicted primary parameters were helpful to estimate and to optimise the performances of the Variable Gain Amplifier (VGA) which was a basic circuit element with a key role in the design of new upcoming receivers.     

Computer-controlled mechanical simulation of the artificially ventilated human respiratory system

A mechanical lung simulator can be used to simulate specific lung pathologies, to test lung-function equipment, and in instruction. A new approach to mechanical simulation of lung behavior is introduced that uses a computer-controlled active mechatronic system. The main advantage of this approach is that the static and dynamic properties of the simulator can easily be adjusted via the control software. A nonlinear single-compartment mathematical model of the artificially ventilated respiratory system has been derived and incorporated into the simulator control system. This model can capture both the static and dynamic compliance of the respiratory system as well as nonlinear flow-resistance properties. Parameters in this model can be estimated by using data from artificially ventilated patients. It is shown that the simulation model fits patient data well. This mathematical model of the respiratory system was then matched to a model of the available physical equipment (the simulator, actuators, and the interface electronics) in order to obtain the desired lung behavior. A significant time delay in the piston motion control loop has been identified, which can potentially cause oscillations or even instability for high compliance values. Therefore, a feedback controller based on the Smith-predictor scheme was developed to control the piston motion. The control system, implemented on a personal computer, also includes a user-friendly interface to allow easy parameter setting.     

Performance of Layered Steered Space–Time Codes in Wireless Systems

Layered Steered Space–Time Codes (LSSTC) is a recently proposed multiple-input multiple-output (MIMO) system that combines the benefits of vertical Bell Labs space–time (VBLAST) scheme, space–time block codes (STBC) and beamforming. In this paper, we derive the error performance and capacity of a single-user LSSTC system. The analysis is general enough to any layer ordering and modulation schemes used. In addition, the derived analysis is general for any LSSTC structure in which layers may have different number of antenna arrays and may be assigned power according to any power allocation. Furthermore, we analytically investigate the tradeoff between the main parameters of the LSSTC system, i.e., diversity, multiplexing and beamforming. Our results give recursive expressions for the probability of error for LSSTC which showed nearly perfect match to the simulation results. Results have also revealed the possibility of designing an adaptive system in which it was shown that combining beamforming, STBC, and VBLAST has better performance than VBLAST at high SNR range.     

Effect of bit-to-bit dependence on packet error rate using asynchronous DS-CDMA for mobile packet radio networks

The probability of packet success for asynchronous direct sequence code division multiple access (DS-CDMA) over the multipath fading channel is investigated under different fading conditions and for different cases. We studied the bit-to-bit dependence caused by the multipath fading and by the multiple access interference (MAI) originating from the chip and phase offsets between the desired and interfering signals. We investigated the effect of using the Gaussian versus the improved Gaussian process on the computation of probability of packet success as well as the effect of the bit-to-bit dependence within a packet. The improved Gaussian approximation provides more accurate values for the probability of bit error for any number of simultaneous users, while it also allows us to incorporate the effects of bit-to-bit dependence into the calculations of the probability of packet success.This paper was presented in part at the 17th Biennial Symposium on Communiations, Kingston, June 1994. This work was supported by a strategic grant (STR-0100720) from the Natural Sciences and Engineering Research Council (NSERC) of Canada.     

Traps centers and deep defects contribution in current instabilities for AlGaN/GaN HEMT's on silicon and sapphire substrates

AlGaN/GaN high electron mobility transistors (HEMTs) with Si and Al₂O₃ substrates reveals anomalies on I_ds-V_ds-T and I_gs-V_gs-T characteristics (degradation in drain current, kink effect, barrier height fluctuations, etc.). Stress and random telegraph signal (RTS) measurements prove the presence of trap centers responsible for drain current degradation. An explanation of the trapping mechanism responsible for current instabilities is proposed. Deep defects analysis performed by capacitance transient spectroscopy (C-DLTS), frequency dispersion of the output conductance (G_ds(f)), respectively, on gate/source and drain/source contacts and RTS prove the presence of deep defects localized, respectively, in the gate and in the channel regions. Defects detected by C-DLTS and G_ds(f) are strongly correlated, respectively, to barrier height inhomogeneities and kink anomalies. Gate current analysis confirms the presence of (G-R) centers acting like traps at the interface GaN/AlGaN. Finally, the localization of these traps defects is proposed.     

On the Performance of FFT/DWT/DCT-based OFDM Systems with Chaotic Interleaving and Channel Estimation Algorithms

The efficiency of data transmission over fading channels in orthogonal frequency division multiplexing (OFDM) systems depends on the employed interleaving method. In this study, we propose an improved chaotic interleaving scheme which aims to improve the performance of OFDM system under fading channel. In the proposed scheme, the binary data is interleaved with chaotic Baker map prior to the modulation process. In the sequel, significant degree of encryption is being added during data transmission. The performance of the proposed approach is tested on the conventional fast Fourier transform OFDM, discrete wavelet transform OFDM, and discrete cosine transform OFDM with and without chaotic interleaving. Furthermore, an expectation–maximization (EM) algorithm is proposed for improving channel impulse response (CIR) estimation based on a maximum likelihood principle. The proposed scheme makes use of EM algorithm to update the channel estimates until convergence is reached. The simulation results show the efficiency of the proposed algorithms under Rayleigh fading environments where the symbol error rate essentially coincides with that of the perfect channel case after the fifth EM iteration.