In the manufacture of metal fasteners in a progressive die operation, and other industrial situations, important quality dimensions cannot be measured on a continuous scale, and parts are classified into groups using a step gauge. This article proposes a version of exponentially weighted moving average (EWMA) control charts applicable to monitoring the grouped data for process shifts. The run l...

Editor’s Note: This article and the first two accompanying discussions were presented orally at the Technomeirics session of the 33rd Annual Fall Technical Conference in Houston, Texas, October 25-27. 1989. The conference was cosponsored by the Chemical and Process Industries and the Statistics Divisions of the American Society for Quality Control and the Section on Physical and Engineering Sci...

Abbas et al. (Abbas N, Riaz M, Does RJMM. Enhancing the performance of EWMA charts. Quality and Reliability Engineering International 2011; 27(6):821–833) proposed the use of signaling schemes with exponentially weighted moving average charts (named as 2/2 and modified 2/3 schemes) for their improved design structures. A two-sided control structure of these schemes is given in the paper. The co...

In many practical situations, multiple variables often need to be monitored simultaneously to ensure the process is in control. In this article, we develop a feasible multivariate monitoring procedure based on the general Multivariate Exponentially Weighted Moving Average (MEWMA) to monitor the multivariate count data. The multivariate count data is modeled using Poisson-Lognormal distribution ...

.Classifying streaming data requires the development of methods which are computationally efficient and able to cope with changes in the underlying distribution of the stream, a phenomenon known in the literature as concept drift. We propose a new method for detecting concept drift which uses an Exponentially Weighted Moving Average (EWMA) chart to monitor the misclassification rate of an strea...

Rate measurements are required for many purposes, e.g. for system analysis and modelling or for live systems that react to measurements. For off-line measurement all data is available in advance. Here, time delay between data collection and data analysis is not an issue. On-line measurement, however, measures rates on the fly. Thus, measurement algorithms that provide their output as timely as ...