Search results for "EWMA chart"

showing 3 items of 3 documents

Efficient anomaly detection on sampled data streams with contaminated phase I data

2020

International audience; Control chart algorithms aim to monitor a process over time. This process consists of two phases. Phase I, also called the learning phase, estimates the normal process parameters, then in Phase II, anomalies are detected. However, the learning phase itself can contain contaminated data such as outliers. If left undetected, they can jeopardize the accuracy of the whole chart by affecting the computed parameters, which leads to faulty classifications and defective data analysis results. This problem becomes more severe when the analysis is done on a sample of the data rather than the whole data. To avoid such a situation, Phase I quality must be guaranteed. The purpose…

Computer scienceSample (material)0211 other engineering and technologies02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]01 natural sciences[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing010104 statistics & probabilitysymbols.namesake[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]ChartControl chartEWMA chart0101 mathematics021103 operations researchData stream miningbusiness.industryPattern recognition[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]OutliersymbolsAnomaly detection[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Artificial intelligence[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]businessGibbs sampling
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Application of Statistical Process Control to Continuous Processes

2002

Control charts represent an efficient and easy tool to assure the state of statistical quality control in a manufacturing process. These tools are also implemented in continuous processes, where the critical parameters are often monitored by on line sensors measuring data with short time intervals. In this paper a continuous process is monitored by using control charts and its dynamic is modeled through linear time series that allow the effects of the autocorrelation to be eliminated. In this way, the control charts can operate on residuals that result identically and independently distributed. A statistical analysis on EWMA, CUSUM and control charts for individual measurements has been car…

Computer scienceautocorrelationAutocorrelationProcess (computing)average run lengthCUSUMControl engineeringStatistical process controlControl chartState (computer science)EWMA chartcontrol chartscontrol charts; autocorrelation; average run lengthTime complexity
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Characterisation and optimal design of a new double sampling <i>c</i> chart

2019

This paper proposes a new double sampling scheme for c control chart (DS-c), which was designed to improve the performance of c chart or to reduce the inspection cost. The mathematical expression required to do an exact evaluation of ARL and ASN is deduced. Further, a bi-objective genetic algorithm is implemented to obtain the optimal design of the DS-c scheme. This optimisation is aimed to simultaneously minimising the error probability type II and the ASN, guaranteeing a desired level for the error probability type I. A performance comparison between the double sampling (DS), fixed parameters (FP), variable simple size (VSS) and exponential weighted moving average (EWMA) schemes for the c…

c-chartOptimal design0209 industrial biotechnology02 engineering and technologyStatistical process controlIndustrial and Manufacturing EngineeringReduction (complexity)Variable (computer science)020901 industrial engineering & automationGenetic algorithmControl chartEWMA chartAlgorithmMathematicsEuropean J. of Industrial Engineering
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