• 제목/요약/키워드: point process

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Estimation of Change Point in Process State on CUSUM ($\bar{x}$, s) Control Chart

  • Takemoto, Yasuhiko;Arizono, Ikuo
    • Industrial Engineering and Management Systems
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    • 제8권3호
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    • pp.139-147
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    • 2009
  • Control charts are used to distinguish between chance and assignable causes in the variability of quality characteristics. When a control chart signals that an assignable cause is present, process engineers must initiate a search for the assignable cause of the process disturbance. Identifying the time of a process change could lead to simplifying the search for the assignable cause and less process down time, as well as help to reduce the probability of incorrectly identifying the assignable cause. The change point estimation by likelihood theory and the built-in change point estimation in a control chart have been discussed until now. In this article, we discuss two kinds of process change point estimation when the CUSUM ($\bar{x}$, s) control chart for monitoring process mean and variance simultaneously is operated. Throughout some numerical experiments about the performance of the change point estimation, the change point estimation techniques in the CUSUM ($\bar{x}$, s) control chart are considered.

2차원 품질보증데이터 모델링 (Two­Dimensional Warranty Data Modelling)

  • Jai Wook Baik;Jin Nam Jo
    • 품질경영학회지
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    • 제31권4호
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    • pp.219-225
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    • 2003
  • Two­dimensional warranty data can be modelled using two different approaches: two­dimensional point process and one­dimensional point process with usage as a function of age. The first approach has three different models. First of all, bivariate model is appealing but is not appropriate for explaining warranty claims. Next, the rest of the two models (marked point process, and counting and matching on both directions independently) are more appropriate for explaining warranty claims. However, the second one (counting and matching on both directions independently) assumes that the two variables (variables representing the two­dimensions) are independent. Last of all, one­dimensional point process with usage as a function of age is also promising to explain the two­dimensional warranty claims. But the models or variations of them need more investigation to be applicable to real warranty claim data.

Comparison of Change-point Estimators in Hazard Rate Models

  • Kim, Jaehee
    • Communications for Statistical Applications and Methods
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    • 제9권3호
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    • pp.753-763
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    • 2002
  • When there is one change-point in the hazard rate model, a change-point estimator with the partial score process is suggested and compared with the previously developed estimators. The limiting distribution of the partial score process we used is a function of the Brownian bridge. Simulation study gives the comparison of change-point estimators.

A Bayesian Inference for Power Law Process with a Single Change Point

  • Kim, Kiwoong;Inkwon Yeo;Sinsup Cho;Kim, Jae-Joo
    • International Journal of Quality Innovation
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    • 제5권1호
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    • pp.1-9
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    • 2004
  • The nonhomogeneous poisson process (NHPP) is often used to model repairable systems that are subject to a minimal repair strategy, with negligible repair times. In this situation, the system can be characterized by its intensity function. There have been many NHPP models according to intensity functions. However, the intensity function of system in use can be changed because of repair or its aging. We consider the single change point model as the modification of the power law process. The shape parameter of its intensity function is changed before and after the change point. We detect the presence of the change point using Bayesian methodology. Some numerical results are also presented.

The Likelihood for a Two-Dimensional Poisson Exceedance Point Process Model

  • Yun, Seok-Hoon
    • Communications for Statistical Applications and Methods
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    • 제15권5호
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    • pp.793-798
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    • 2008
  • Extreme value inference deals with fitting the generalized extreme value distribution model and the generalized Pareto distribution model, which are recently combined to give a single model, namely a two-dimensional non-homogeneous Poisson exceedance point process model. In this paper, we extend the two-dimensional non-homogeneous Poisson process model to include non-stationary effect or dependence on covariates and then derive the likelihood for the extended model.

축교정기를 위한 자동굽힘공정제어기 설계 (Automatically Bending Process control for Shaft Straightening Machine)

  • 김승철
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1998년도 추계학술대회 논문집
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    • pp.54-59
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    • 1998
  • In order to minimize straightness error of deflected shafts, a automatically bending process control system is designed, fabricated, and studied. The multi-step straightening process and the three-point bending process are developed for the geometric adaptive straightness control. Load-deflection relationship, on-line identification of variations of material properties, on-line springback prediction, and studied for the three-point bending processes. Selection of a loading point supporting condition are derved form fuzzy inference and fuzzy self-learning method in the multi-step straighternign process. Automatic straightening machine is fabricated by using the develped ideas. Validity of the proposed system si verified through experiments.

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직접압연 공정에서 품질계측을 위한 공정변수의 선정 (Determination of the process variables for quality monitoring in direct rolling processes)

  • 배세철;박영준;조형석
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.1364-1367
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    • 1996
  • Recently, direct rolling process, called as strip casting process, has been interested in to save production cost by reducing forming processes. In direct rolling process, since a steel strip of thickness 1-5(mm) can be produced directly from molten metal, it can eliminate secondary hot rolling process. On the other hand, since many process variables are existed in this process and relation of these variables is very complex, it is difficult to realize the process design and the quality control. In this paper, as first step to overcome above difficulties, the quantitative relationship of the process variables affected to quality of the strip has been carried out through the numerical analysis. Also, we determined the process variable to monitor the quality in the direct rolling process. As a result, we show that the solidification final point, called as Nip point, was related directly to quality of the strip.

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Hardware-In-the-Loop 시스템을 이용한 태양광 시스템 연구 (PV System using HIL System)

  • 최주엽;최익;김병만
    • 한국신재생에너지학회:학술대회논문집
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    • 한국신재생에너지학회 2005년도 제17회 워크샵 및 추계학술대회
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    • pp.665-665
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    • 2005
  • The existing DSP for utility interactive photovoltaic generation system control generally uses floating point process type. Because it is easy to use for number crunching, however, it is too late and too expensive. Fixed point process DSP TMS320F2812, has high control speed and is rather inexpensive. A very complicated real system can be simulated using hardware-in-the-loop (HIL) system in a virtual environment Therefore, HIL system can speed up research and development process with a little effort. Also current DSP for utility interactive photovoltaic generation system adopts floating point process type, which is easy to use for number crunching. However, fixed point process DSF, TMS320F2812, has high control speed and is rather inexpensive. This paper presents more efficient method for MPPT control using TMS320F2812 along with HIL System.

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Estimation of the Change Point in VSS X Control Charts

  • Lee, Jaeheon;Park, Changsoon
    • Communications for Statistical Applications and Methods
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    • 제10권3호
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    • pp.825-833
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    • 2003
  • Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose a maximum likelihood estimator of the process change point when a Shewhart $\bar{X}$ chart with variable sample size (VSS) scheme signals a change in the process mean. Also we build a confidence interval for the process change point by using the likelihood function.