The most popular tool used in the industry for monitoring a process is the Shewhart control chart. The major disadvantage of the Shewhart control chart is that it is not very efficient in detecting small process average shifts. To increase the sensitivity of Shewhart control charts to small shifts additional supplementary runs rules has been suggested. In this paper we introduce and study the m...

Nonparametric control charts can provide a robust alternative in practice to the data analyst when there is a lack of knowledge about the underlying distribution. A nonparametric exponentially weighted moving average (NPEWMA) control chart combines the advantages of a nonparametric control chart with the better shift detection properties of a traditional EWMA chart. A NPEWMA chart for the media...

Usually, in monitoring schemes the nominal value of the process parameter is assumed known. However, this assumption is violated owing to costly sampling and lack of data particularly in healthcare systems. On the other hand, applying a fixed control limit for the risk-adjusted Bernoulli chart causes to a variable in-control average run length performance for patient populations with dissimilar...

Scenarios, or Message Sequence Charts, offer an intuitive way of describing the desired behaviors of a distributed protocol. In this paper we propose a new way of specifying and synthesizing finite-state protocols using scenarios: we show that it is possible to automatically derive a distributed implementation from a set of scenarios augmented with a set of safety and liveness requirements, pro...

For product manufacturing, control charts are important tools. Different types of control charts are used to monitor different measures of product characteristics. Among the numerous charts, the popular one is the Hotelling’s T 2 chart. It is designed while taking into account the most sensitive measures such as sample covariance matrix and sample mean vector. However, the chart becomes ineffec...

This working paper series is intended to facilitate discussion and encourage the exchange of ideas. Inclusion here does not preclude publication elsewhere. It is the original work of the author(s) and subject to copyright regulations. ABSTRACT We believe that conflicting decision signals resulting from examining Shewhart Mean and Variability Control Charts produce undesirable consequences. Ther...

Call it the department chair’s dilemma: How do you get a swarm of independently minded minions moving in concert toward some useful goal? The problem may be inherently insoluble in a professorial setting, in part because the notion of academic motion is purely metaphoric. But encouraging signs of progress have emerged for a more literal analog. Researchers in control theory are perfecting a rep...

1 60 2 61 3 62 4 63 5 64 6 65 7 66 8 67 9 68 10 69 11 70 12 71 13 72 14 73 15 74 16 75 17 76 18 77 19 78 20 79 21 80 22 81 23 82 24 83 25 84 26 85 27 86 28 87 29 88 30 89 31 90 32 91 33 92 34 93 35 94 36 95 37 96 38 97 39 98 40 99 41 100 42 101 43 102 44 103 45 104 46 105 47 106 48 107 49 108 50 109 51 110 52 111 53 112 54 113 55 114 56 115 57 116 58 117 59 118 A Multivariate Sign EWMA Control ...

The significant features of Tukey’s control chart include characteristics such as: easy setup, use of single observation to monitor process, and suitability to monitor destructive testing processes. The control limit width and sampling interval should be determined before Tukey’s control chart can be used. In this study, Duncan’s cost function is modified to construct an economic design model o...

Recent studies have shown that the 2 T control chart with variable sampling intervals (VSI) and/or variable sample sizes (VSS) detects process shifts faster than the traditional 2 T chart. This article extends these studies for processes that are monitored with VSI and VSS using double warning lines ( DWL T − 2 ). It is assumed that the length of time the process remains in control has exponent...