A stochastic shift model for economically designed charts constrained by the process stage configuration

An economic model including the labor resource and the process stage configuration is proposed to design g charts allowing for all the design parameters to be varied in an adaptive way. A random shift size is considered during the economic design selection. The results obtained for a benchmark of 64 process stage scenarios show that the activities configuration and some process operating parameters influence the selection of the best control chart strategy: to model the random shift size, its exact distribution can be approximately fitted by a discrete distribution obtained from a relatively small sample of historical data. However, an accurate estimation of the inspection costs associated to the SPC activities is far from being achieved. An illustrative example shows the implementation of the proposed economic model in a real industrial case. (C) 2011 Elsevier B.V. All rights reserved.

Storaged products and presence of acid phosphatase in fat body cells at pre-pupal worker stage of Apis mellifera Linnaeus, 1758 (Hymenoptera, Apidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Monitoring the process mean and variance using a synthetic control chart with two-stage testing

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Prenatal testosterone supplementation alters puberty onset, aggressive behavior, and partner preference in adult male rats

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The Combination of Amoxicillin and Metronidazole Improves Clinical and Microbiologic Results of One-Stage, Full-Mouth, Ultrasonic Debridement in Aggressive Periodontitis Treatment

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Tuberculosis diagnosis after bleach processing for early stage tuberculosis laboratory capacity building

The diagnosis of tuberculosis is seriously hampered in the absence of standard biosafety laboratory facilities for specimen concentration and Mycobacterium tuberculosis culture. Within a laboratory twinning arrangement, heat-fixed direct smear and sediment from 74 bleach-processed and 20 non-processed specimens from Cumura Hospital, Guinea-Bissau, were sent to Lisbon for molecular evaluation of rifampicin resistance. Sequence analysis of a 369 base-pair ppoB locus detected 3.2% (3/94) resistant specimens. To our knowledge, this represents the first report on the molecular analysis of M. tuberculosis from bleach-processed sputum, an alternative to current diagnostic practice in low-resource settings.

Mössbauer spectroscopic study of the early crystallization stage of iron(III) hydroxide particles

Mössbauer spectroscopy was used to investigate the early aging stage of iron(III) hydroxide sols prepared by oxidation of Fe(CO)5 in ethanolic solution, followed by vacuum drying at room temperature. One sample was composed of amorphous particles, while two other samples were partially crystallized, either as a result of solvent change or of spontaneous aging. The main results of Mössbauer measurements in the 80-320 K temperature range are: (a) partially crystallized particles exhibit a strong, S-shaped temperature dependence of the quadrupole splitting, in contrast to a weak and linear variation for amorphous particles; (b) the recoilless fraction temperature dependence is affected by vibration of the particles as a whole, with an effective force constant which is smaller for crystallized particles than for amorphous ones. Furthermore, the former exhibit anf-factor discontinuity near 0°C, which is attributed to melting of a surface layer built up during the crystallization process. © 1986.

The no-central chi-square chart with two-stage samplings

Throughout this article, it is assumed that the no-central chi-square chart with two stage samplings (TSS Chisquare chart) is employed to monitor a process where the observations from the quality characteristic of interest X are independent and identically normally distributed with mean μ and variance σ2. The process is considered to start with the mean and the variance on target (μ = μ0; σ2 = σ0 2), but at some random time in the future an assignable cause shifts the mean from μ0 to μ1 = μ0 ± δσ0, δ >0 and/or increases the variance from σ0 2 to σ1 2 = γ2σ0 2, γ > 1. Before the assignable cause occurrence, the process is considered to be in a state of statistical control (defined by the in-control state). Similar to the Shewhart charts, samples of size n 0+ 1 are taken from the process at regular time intervals. The samplings are performed in two stages. At the first stage, the first item of the i-th sample is inspected. If its X value, say Xil, is close to the target value (|Xil-μ0|< w0σ 0, w0>0), then the sampling is interrupted. Otherwise, at the second stage, the remaining n0 items are inspected and the following statistic is computed. Wt = Σj=2n 0+1(Xij - μ0 + ξiσ 0)2 i = 1,2 Let d be a positive constant then ξ, =d if Xil > 0 ; otherwise ξi =-d. A signal is given at sample i if |Xil-μ0| > w0σ 0 and W1 > knia:tl, where kChi is the factor used in determining the upper control limit for the non-central chi-square chart. If devices such as go and no-go gauges can be considered, then measurements are not required except when the sampling goes to the second stage. Let P be the probability of deciding that the process is in control and P 1, i=1,2, be the probability of deciding that the process is in control at stage / of the sampling procedure. Thus P = P1 + P 2 - P1P2, P1 = Pr[μ0 - w0σ0 ≤ X ≤ μ0+ w 0σ0] P2=Pr[W ≤ kChi σ0 2], (3) During the in-control period, W / σ0 2 is distributed as a non-central chi-square distribution with n0 degrees of freedom and a non-centrality parameter λ0 = n0d2, i.e. W / σ0 2 - xn0 22 (λ0) During the out-of-control period, W / σ1 2 is distributed as a non-central chi-square distribution with n0 degrees of freedom and a non-centrality parameter λ1 = n0(δ + ξ)2 / γ2 The effectiveness of a control chart in detecting a process change can be measured by the average run length (ARL), which is the speed with which a control chart detects process shifts. The ARL for the proposed chart is easily determined because in this case, the number of samples before a signal is a geometrically distributed random variable with parameter 1-P, that is, ARL = I /(1-P). It is shown that the performance of the proposed chart is better than the joint X̄ and R charts, Furthermore, if the TSS Chi-square chart is used for monitoring diameters, volumes, weights, etc., then appropriate devices, such as go-no-go gauges can be used to decide if the sampling should go to the second stage or not. When the process is stable, and the joint X̄ and R charts are in use, the monitoring becomes monotonous because rarely an X̄ or R value fall outside the control limits. The natural consequence is the user to pay less and less attention to the steps required to obtain the X̄ and R value. In some cases, this lack of attention can result in serious mistakes. The TSS Chi-square chart has the advantage that most of the samplings are interrupted, consequently, most of the time the user will be working with attributes. Our experience shows that the inspection of one item by attribute is much less monotonous than measuring four or five items at each sampling.

A branch-and-bound algorithm for the multi-stage transmission expansion planning

This work presents a branch-and-bound algorithm to solve the multi-stage transmission expansion planning problem. The well known transportation model is employed, nevertheless the algorithm can be extended to hybrid models or to more complex ones such as the DC model. Tests with a realistic power system were carried out in order to show the performance of the algorithm for the expansion plan executed for different time frames. © 2005 IEEE.