کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
387316 | 660900 | 2012 | 7 صفحه PDF | دانلود رایگان |
This research considers the process mean wanders according to a first-order autoregressive model. During the in-control period the process mean wanders around its target value, and after the assignable cause occurrence, around an off-target value. The cost model proposed by Duncan was used to select the X bar chart’s parameters and the genetic algorithm to meet their optimum values. The wandering movement required a Markov chain to obtain the properties of the control chart. The autocorrelation among mean values increases the monitoring costs and reduces significantly the chart’s efficiency.
► The process mean is supposed to wander according to a first-order autoregressive model.
► Considers the cost model proposed by Duncan to select the X¯ chart’s parameters.
► The alternative to obtain the average run length and the rate of false alarms consists of building a Markov chain.
► The genetic algorithm is used to find the optimum parameter values.
► The autocorrelation among mean values increases the monitoring costs and reduces significantly the chart’s efficiency.
Journal: Expert Systems with Applications - Volume 39, Issue 17, 1 December 2012, Pages 12961–12967