• Title/Summary/Keyword: 모델모수기반 관리도

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Model Parameter Based Fault Detection for Time-series Data (시계열을 따르는 공정데이터의 모델 모수기반 이상탐지)

  • Park, Si-Jeo;Park, Cheong-Sool;Kim, Sung-Shick;Baek, Jun-Geol
    • Journal of the Korea Society for Simulation
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    • v.20 no.4
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    • pp.67-79
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    • 2011
  • The statistical process control (SPC) assumes that observations follow the particular statistical distribution and they are independent to each other. However, the time-series data do not always follow the particular distribution, and most of cases are autocorrelated, therefore, it has limit to adopt the general SPC in tim series process. In this study, we propose a MPBC (Model Parameter Based Control-chart) method for fault detection in time-series processes. The MPBC builds up the process as a time-series model, and it can determine the faults by detecting changes parameters in the model. The process we analyze in the study assumes that the data follow the ARMA (p,q) model. The MPBC estimates model parameters using RLS (Recursive Least Square), and $K^2$-control chart is used for detecting out-of control process. The results of simulations support the idea that our proposed method performs better in time-series process.

Development of Historical Data Selection Model Using Non-parametric test in Public Sector - focused on Reinforced Concrete Works of Multi-housing Projects - (비모수 검정기반 공공부문 실적단가 선정모델 개발 -공동주택 철근콘크리트 공종을 중심으로-)

  • Lee, Hyun-Ki;Jeon, Jae-Yong;Park, Sung-Chul;Hong, Tae-Hoon;Koo, Kyo-Jin;Hyun, Chang-Taek
    • Korean Journal of Construction Engineering and Management
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    • v.9 no.1
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    • pp.87-95
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    • 2008
  • The government wants to apply the construction cost estimating method based on historical data published in the first six months of 2004. Construction companies, however, require the proposed cost estimation model, to be improved which makes it difficult to predict a reasonable construction costs. This paper presents an improved historical data selection model after analyzing the problem of previous method throughout comparing contracted unit prices of reinforced concrete works selected by the previous model to market prices. The model which can select more feasible data would assist participates such as general contractors and sub-contractors to earn a proper profits.

Selection of Probability Distribution of Pavement Life Based on Reliability Method (신뢰성 개념을 이용한 적정 포장 수명분포 선정)

  • Do, Myung-Sik;Kwon, Soo-Ahn
    • International Journal of Highway Engineering
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    • v.12 no.1
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    • pp.61-69
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    • 2010
  • In this paper, we present the methodology about an optimal probability distribution selection as well as survival rate estimation with the national highway database from 1999 to 2008. Probability paper methods are adopted to estimate the parameters of each hazard model. The goodness-of-fit test, such as the Anderson-Darling statistics, was performed. As a result, we found that Lognormal distributionan is an appropriate distribution of newly constructed sections as well as overlayed sections. We also ascertained that the results of survival rate for pavement life between the proposed method and observed data are similar. Such a selection methodology and measures based on reliability theory can provide useful information for maintenance plans in pavement management systems as long as additional life data on pavement sections are accumulated.

Assessing Infinite Failure Software Reliability Model Using SPC (Statistical Process Control) (통계적 공정관리(SPC)를 이용한 무한고장 소프트웨어 신뢰성 모형에 대한 접근방법 연구)

  • Kim, Hee Cheul;Shin, Hyun Cheul
    • Convergence Security Journal
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    • v.12 no.6
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    • pp.85-92
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    • 2012
  • There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outliers, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical Process Control (SPC) can monitor the forecasting of software failure and there by contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of log Poission, log-linear and Parto distribution.

The Assessing Comparative Study for Statistical Process Control of Software Reliability Model Based on Musa-Okumo and Power-law Type (Musa-Okumoto와 Power-law형 NHPP 소프트웨어 신뢰모형에 관한 통계적 공정관리 접근방법 비교연구)

  • Kim, Hee-Cheul
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.8 no.6
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    • pp.483-490
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    • 2015
  • There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

Multi-Agent based Operation System Modeling for Automated Container Terminals (자동화 컨테이너 터미널을 위한 멀티에이전트 기반의 운영시스템 모델링)

  • Kang K W.;Yu S. Y.;Mo S. J.;Yim J. H.
    • Journal of Navigation and Port Research
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    • v.29 no.6 s.102
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    • pp.567-572
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    • 2005
  • Trade between nations has been globalized since establishing the WTO(World Trade Organization). By lowering trading barriers under the WTO's system, trade in goods has been gradually increased It requires global logistic system that transports goods in between nations. To save cost of product, cargo of product is containerized and container ships to carry container cargo is going to be bigger: In the market, there are many vendors to provide artificial intelligent modules to operate container terminal. In order to integrate automated container terminal system easily and successfully, this thesis proposes high-level XML/ JMS( eXtensive Markup Language/Java Message Service) communication model and multi-agent based system architecture to share knowledges, solve problems, and active objectives by cooperating between autonomous and intelligent agents that are developed by 3rd party companies in the market. This thesis analyzed current situation of advanced automated container terminal with case studies on implemented systems and difficulties to develop automated container terminal system, reviewed technologies of intelligent agent, communication and automation that unmaned automated container terminal is required.