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Exponentially weighted moving average distance square scheme for joint monitoring of process mean and variance

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dc.contributor.author Razmy, A.M.
dc.date.accessioned 2018-02-26T04:44:00Z
dc.date.available 2018-02-26T04:44:00Z
dc.date.issued 2017-12-07
dc.identifier.citation 7th International Symposium 2017 on “Multidisciplinary Research for Sustainable Development”. 7th - 8th December, 2017. South Eastern University of Sri Lanka, University Park, Oluvil, Sri Lanka. pp. 256-263. en_US
dc.identifier.isbn 978-955-627-120-1
dc.identifier.uri http://ir.lib.seu.ac.lk/handle/123456789/3055
dc.description.abstract In quality control, joint monitoring of process mean and variance has become more popular due to the disadvantages of monitoring mean and variance alone. This paper introduce a new joint monitoring scheme for process mean and variance. In this new scheme, exponential moving average technique is applied to the statistics D2t developed in the Shewhart distance scheme by Razmy (2010). The optimal design parameter were found through simulations for designing this new scheme. The design techniques of this scheme are illustrated with an example. A big advantage of this new scheme is, unlike most existing joint monitoring schemes, the design parameters of this scheme are independent on the sample size thus the quality engineers have fewer constraints in implementing this scheme. en_US
dc.language.iso en_US en_US
dc.publisher South Eastern University of Sri Lanka, University Park, Oluvil, Sri Lanka. en_US
dc.subject Average run length en_US
dc.subject Control limit en_US
dc.subject Exponential weighted moving average en_US
dc.subject Joint monitoring en_US
dc.title Exponentially weighted moving average distance square scheme for joint monitoring of process mean and variance en_US
dc.type Article en_US


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