2,820 research outputs found
Risk-Based X-bar chart with variable sample size and sampling interval
Flexibility is increasingly important in production management, and adaptive control charts (i.e., control charts with variable sample size and/or variable sampling interval) have significant importance in the field of statistical process control. The value of the variable chart parameters depends on the detected process parameters. The process parameters need to be estimated based on observed values; however, these values are distorted by measurement uncertainty. Therefore, the performance of the method is strongly influenced by the precision of the measurement. This paper proposes a risk-based concept for the design of an X-bar chart with variable sample size and sampling interval. The optimal set of the parameters (control line, sample size and sampling interval) is determined using genetic algorithms and the Nelder-Mead direct search algorithm to minimize the risks arising from measurement uncertainty
ISBIS 2016: Meeting on Statistics in Business and Industry
This Book includes the abstracts of the talks presented at the 2016 International Symposium on Business and Industrial Statistics, held at Barcelona, June 8-10, 2016, hosted at the Universitat Politècnica de Catalunya - Barcelona TECH, by the Department of Statistics and Operations Research. The location of the meeting was at ETSEIB Building (Escola Tecnica Superior d'Enginyeria Industrial) at Avda Diagonal 647.
The meeting organizers celebrated the continued success of ISBIS and ENBIS society, and the meeting draw together the international community of statisticians, both academics and industry professionals, who share the goal of making statistics the foundation for decision making in business and related applications. The Scientific Program Committee was constituted by:
David Banks, Duke University
Amílcar Oliveira, DCeT - Universidade Aberta and CEAUL
Teresa A. Oliveira, DCeT - Universidade Aberta and CEAUL
Nalini Ravishankar, University of Connecticut
Xavier Tort Martorell, Universitat Politécnica de Catalunya, Barcelona TECH
Martina Vandebroek, KU Leuven
Vincenzo Esposito Vinzi, ESSEC Business Schoo
Optimal statistical designs of multivariate EWMA and multivariate CUSUM charts based on average run length and median run leng
Carta kawalan multivariat ialah alat yang berkuasa dalam kawalan proses yang
melibatkan kawalan serentak beberapa cirian kualiti yang berkorelasi. Carta-carta
multivariat hasil tambah longgokan {MCUSUM) dan multivariat purata bergerak
berpemberat eksponen (MEWMA) sentiasa dicadangkan dalam kawalan proses
apabila pengesanan cepat anjakan tetap yang keciJ atau sederhana dalam vektor min
adalah diingini.
A multivariate control chart is a powerful tool in process control involving a
simultaneous monitoring of several correlated quality characteristics. The multivariate
cumulative sum (MCUSUM) and multivariate exponentially weighted moving average
(MEWMA) charts are often recommended in process monitoring when a quick
detection of small or moderate sustained shifts in the mean vector is desired
Modeling and designing control chart for monitoring time-between events data
Ph.DDOCTOR OF PHILOSOPH
Modelo de apoio à decisão para a manutenção condicionada de equipamentos produtivos
Doctoral Thesis for PhD degree in Industrial and Systems EngineeringIntroduction: This thesis describes a methodology to combine Bayesian control chart
and CBM (Condition-Based Maintenance) for developing a new integrated model. In
maintenance management, it is a challenging task for decision-maker to conduct an
appropriate and accurate decision. Proper and well-performed CBM models are
beneficial for maintenance decision making. The integration of Bayesian control chart
and CBM is considered as an intelligent model and a suitable strategy for forecasting
items failures as well as allow providing an effectiveness maintenance cost. CBM
models provides lower inventory costs for spare parts, reduces unplanned outage, and
minimize the risk of catastrophic failure, avoiding high penalties associated with losses
of production or delays, increasing availability. However, CBM models need new
aspects and the integration of new type of information in maintenance modeling that can
improve the results. Objective: The thesis aims to develop a new methodology based on
Bayesian control chart for predicting failures of item incorporating simultaneously two
types of data: key quality control measurement and equipment condition parameters. In
other words, the project research questions are directed to give the lower maintenance
costs for real process control. Method: The mathematical approach carried out in this
study for developing an optimal Condition Based Maintenance policy included the
Weibull analysis for verifying the Markov property, Delay time concept used for
deterioration modeling and PSO and Monte Carlo simulation. These models are used for
finding the upper control limit and the interval monitoring that minimizes the
(maintenance) cost function. Result: The main contribution of this thesis is that the
proposed model performs better than previous models in which the hypothesis of using
simultaneously data about condition equipment parameters and quality control
measurements improve the effectiveness of integrated model Bayesian control chart for
Condition Based Maintenance.Introdução: Esta tese descreve uma metodologia para combinar Bayesian control chart
e CBM (Condition- Based Maintenance) para desenvolver um novo modelo integrado.
Na gestão da manutenção, é importante que o decisor possa tomar decisões apropriadas
e corretas. Modelos CBM bem concebidos serão muito benéficos nas tomadas de
decisão sobre manutenção. A integração dos gráficos de controlo Bayesian e CBM é
considerada um modelo inteligente e uma estratégica adequada para prever as falhas de
componentes bem como produzir um controlo de custos de manutenção. Os modelos
CBM conseguem definir custos de inventário mais baixos para as partes de substituição,
reduzem interrupções não planeadas e minimizam o risco de falhas catastróficas,
evitando elevadas penalizações associadas a perdas de produção ou atrasos, aumentando
a disponibilidade. Contudo, os modelos CBM precisam de alterações e a integração de
novos tipos de informação na modelação de manutenção que permitam melhorar os
resultados.Objetivos: Esta tese pretende desenvolver uma nova metodologia baseada
Bayesian control chart para prever as falhas de partes, incorporando dois tipos de
dados: medições-chave de controlo de qualidade e parâmetros de condição do
equipamento. Por outras palavras, as questões de investigação são direcionadas para
diminuir custos de manutenção no processo de controlo.Métodos: Os modelos
matemáticos implementados neste estudo para desenvolver uma política ótima de CBM
incluíram a análise de Weibull para verificação da propriedade de Markov, conceito de
atraso de tempo para a modelação da deterioração, PSO e simulação de Monte Carlo.
Estes modelos são usados para encontrar o limite superior de controlo e o intervalo de
monotorização para minimizar a função de custos de manutenção.Resultados: A
principal contribuição desta tese é que o modelo proposto melhora os resultados dos
modelos anteriores, baseando-se na hipótese de que, usando simultaneamente dados dos
parâmetros dos equipamentos e medições de controlo de qualidade. Assim obtém-se
uma melhoria a eficácia do modelo integrado de Bayesian control chart para a
manutenção condicionada
A Statistical Approach to the Alignment of fMRI Data
Multi-subject functional Magnetic Resonance Image studies are critical. The anatomical and functional structure varies across subjects, so the image alignment is necessary. We define a probabilistic model to describe functional alignment. Imposing a prior distribution, as the matrix Fisher Von Mises distribution, of the orthogonal transformation parameter, the anatomical information is embedded in the estimation of the parameters, i.e., penalizing the combination of spatially distant voxels. Real applications show an improvement in the classification and interpretability of the results compared to various functional alignment methods
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