A wavelet-based procedure for process fault detection

To detect faults in a time-dependent process, we apply a discrete wavelet transform (DWT) to several independently replicated data sets generated by that process. The DWT can capture irregular data patterns such as sharp "jumps" better than the Fourier transform and standard statistical procedures without adding much computational complexity. Our wavelet coefficient selection method effectively balances model parsimony against data reconstruction error. The few selected wavelet coefficients serve as the "reduced-size" data set to facilitate an efficient decision-making method in situations with potentially large-volume data sets. We develop a general procedure to detect process faults based on differences between the reduced-size data sets obtained from the nominal (in-control) process and from a new instance of the target process that must be tested for an out-of-control condition. The distribution of the test statistic is constructed first using normal distribution theory and then with a new resampling procedure called "reversed jackknifing" that does not require any restrictive distributional assumptions. A Monte Carlo study demonstrates the effectiveness of these procedures. Our methods successfully detect process faults for quadrupole mass spectrometry samples collected from a rapid thermal chemical vapor deposition process     

Simulation of programmable logic controller

The development and test of a PLC control program takes time, increases equipment down-time, and might damage hardware due to program errors. All of these problems can be eliminated if there is a computer simulation system for testing control programs off line. This paper presented a new method, called Direct Sequential Method, for simulating PLCs. This method resolves a ladder logic sequentially by applying a series of logic deductions. This simulation system has been implemented in C and tested successfully.     

Improved Poisson intensity estimation: denoising application using Poisson data

Recently, Timmermann and Nowak developed algorithms for estimating the means of independent Poisson random variables. The algorithms are based on a multiscale model where certain random variables are assumed to obey a beta-mixture density function. Timmermann and Nowak simplify the density estimation problem by assuming the beta parameters are known and only one mixture parameter is unknown. They use the observed data and the method of moments to estimate the unknown mixture parameter. Taking a different approach, we generate training data from the observed data and compute maximum likelihood estimates of all of the beta-mixture parameters. To assess the improved performance obtained by the proposed modification, we consider a denoising application using Poisson data.     

An investigation of bulk recycling planning for an electronics recycling facility receiving industrial returns versus residential returns

Since most end-of-life electronics equipment contain hazardous materials such as lead solder alloys or lead-impregnated glass, it is important to divert them from landfills. For end-of-life products that are not repairable and do not contain reusable parts, bulk recycling is an alternative to recover base materials. In this paper, we contrast production and recycling planning and distribution decisions, activities, and costs. We reveal that while a traditional production facility connects suppliers and customers, a recycling facility connects both "input" and "output" customers. As a result, decisions in short-term bulk recycling planning include what products to accept, what products to process and reprocess, and what products to carry in inventory. Many recyclers set prices to receive "input" based on experience. For various prices to receive "input", we use a new analytical model to investigate the sensitivity of the short-term bulk recycling planning decisions in products from two different sources: industrial returns versus residential returns. The results of the case study show that different decisions are recommended for the industrial returns versus the residential returns when the total quantity of the incoming products is equal.     

A vectorial boundary element method analysis of integrated optical waveguides

In this paper, a new vectorial boundary element method is introduced and applied to the modal analysis of dielectric waveguides with piecewise homogeneous refractive indexes. The procedure, which is free of spurious modes, determines the full field distribution from the longitudinal fields at the refractive index boundaries. Singular kernels are evaluated through series solutions while the electric field discontinuity at corners is accommodated through either a grid refinement technique or a semianalytic approach. Our formalism generates propagation constants and modal field distributions for several representative refractive index profiles with far higher accuracy than standard finite-difference or finite-element procedures.