The sign SN distribution-free control charts are ecient and sim- ple on-line tools to perform quality monitoring when the normality of observations cannot be assumed a priori. The possibility of design- ing a SN control chart whichever is the distribution of observations allows it to be implemented with success in processes with nite pro- duction horizon (FPH). Today, nite production horizon processes are widespread in industry. Recently, Shewhart SN control charts have been investigated in literature for this kind of quality control prob- lem. In this paper, we investigate the implementation of an EWMA SN control chart for nite production horizon (FPH) processes. The property to have varying control limits at each inspection allows the EWMA SN control chart to be very sensitive to shifts in the loca- tion. A non-homogeneous Markov chain model is used to evaluate the statistical properties of the EWMA SN control chart with vary- ing control limits. An illustrative example shows the implementation of the EWMA SN control chart with observations collected from a quality monitoring procedure in a company bottling soft drinks.

An EWMA sign control chart with varying control limits for finite horizon processes

G. Celano
Membro del Collaboration Group
;
2018-01-01

Abstract

The sign SN distribution-free control charts are ecient and sim- ple on-line tools to perform quality monitoring when the normality of observations cannot be assumed a priori. The possibility of design- ing a SN control chart whichever is the distribution of observations allows it to be implemented with success in processes with nite pro- duction horizon (FPH). Today, nite production horizon processes are widespread in industry. Recently, Shewhart SN control charts have been investigated in literature for this kind of quality control prob- lem. In this paper, we investigate the implementation of an EWMA SN control chart for nite production horizon (FPH) processes. The property to have varying control limits at each inspection allows the EWMA SN control chart to be very sensitive to shifts in the loca- tion. A non-homogeneous Markov chain model is used to evaluate the statistical properties of the EWMA SN control chart with vary- ing control limits. An illustrative example shows the implementation of the EWMA SN control chart with observations collected from a quality monitoring procedure in a company bottling soft drinks.
Quality control; SPC; Process location; Distribution-free; MArkov modelling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/329669
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