The manufacturing operations often involve multistage processes where the process capability of each stage is affected by the process capability of its precedent processes. This property is known as the cascade property. The purpose of this paper is to estimate the process capability of the second stage of two-stage process while the cascade property impact is removed using residuals analysis. ...

Variation reduction in multistage assembly processes is an important but challenging issue for quality control. It is desirable to minimize the final product variance from a system level. Fruitful research has been conducted on this issue based on the fixed assembly order. However, the variability of parts can be affected by different assembly order. In this paper, we propose a quality control ...

Speech segregation is an important task of auditory scene analysis (ASA), in which the speech of a certain speaker is separated from other interfering signals. Wang and Brown proposed a multistage neural model for speech segregation, the core of which is a two-layer oscillator network. In this paper, we extend their model by adding further processes based on psychoacoustic evidence to improve t...

54 Abstract—The scientific research deals with organization principles of parallel-hierarchical transform for multistage perception and processing, compression and recognition of information in informational structure and computational systems which make use of computational scheme similar to neural. Unified methodological approach was developed for analysis of parallel processes. This approach...

It is the purpose of this paper to present a methodology of analysis which identifies optimum types and combination of unit treatment processes from the range of available alternatives. The objective is to identify the optimum combination and efficiencies of various unit processes in multistage plant; then meet design criteria. Optimality, as used herein, is defined as meeting a given treatment...

In this chapter, we present the multistage stochastic programming framework for sequential decision making under uncertainty and stress its differences with Markov Decision Processes. We describe the main approximation technique used for solving problems formulated in the multistage stochastic programming framework, which is based on a discretization of the disturbance space. We explain that on...