Author
Niladri Chakraborty
Bio: Niladri Chakraborty is an academic researcher from University of Pretoria. The author has contributed to research in topics: Chart & Control chart. The author has an hindex of 3, co-authored 3 publications receiving 63 citations.
Topics: Chart, Control chart, Mathematics, Computer science, EWMA chart
Papers
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TL;DR: Research of the first author was supported in part by STATOMET at the University of Pretoria, South Africa and National Research Foundation through the SARChI Chair at the School of Pharmacy and Dentistry.
Abstract: Research of the first author was supported in part by STATOMET at the University of Pretoria, South Africa and National Research Foundation through the SARChI Chair at the University of Pretoria, South Africa.
36 citations
TL;DR: In this article, a time-weighted chart is used to monitor the time between events (TB) in attribute charts, which is an alternative to the traditional Shewhart-type attribute charts.
Abstract: Shewhart-type attribute charts are known to be inefficient for small changes in monitoring nonconformities. An alternative way is to use a time-weighted chart to monitor the time between events (TB...
27 citations
TL;DR: Distribution-free control charts gained momentum in recent years as they are more efficient in detecting a shift when there is a lack of information regarding the underlying process distribution as discussed by the authors, and have been shown to be more accurate than traditional control charts.
Abstract: Distribution-free control charts gained momentum in recent years as they are more efficient in detecting a shift when there is a lack of information regarding the underlying process distribution. H...
15 citations
TL;DR: In this paper , the authors proposed GLM-based moving average and double moving average (DMA) schemes formed on standardized residuals derived from a fitted Poisson regression model to monitor industrial operations that focus on the normal response variable.
Abstract: Control charts are widely used tool that provides quality inspectors with sensitive information for maintaining manufacturing process productivity. Numerous model‐based techniques have been presented in the literature to monitor industrial operations that focus on the normal response variable. However, non‐normal response results can occur as a result of quality control operations. In such cases, a new approach based on generalized linear model that provides multiple distribution options for response variables is required to achieve better results. Therefore, this study proposes GLM‐based moving average (MA) and double moving average (DMA) schemes formed on standardized residuals derived from a fitted Poisson regression model. The productivity of suggested methods and the existing exponentially weighted moving average (EWMA) scheme is explored in terms of run length attributes. The simulation outcomes revealed that moving average schemes based on standardized residuals (i.e., SR‐MA and SR‐DMA) outperform their predecessor (i.e., SR‐EWMA). Moreover, the SR‐DMA chart, with small values of span w , has proven to be more effective at detecting minor to moderate shifts in the process mean. Finally, a case study of a 3D manufacturing operation is shown to emphasize the importance of the proposed approaches.
7 citations
TL;DR: In this article , a double sampling-based precedence and weighted precedence tests are introduced and analyzed under the double-sampling framework, and closed-form expressions for the rejection probabilities are derived under the null hypothesis and the Lehmann alternative.
Abstract: A new double sampling-based precedence and weighted precedence tests are introduced and analysed. The joint distributions of two precedence and weighted precedence statistics are obtained under the double-sampling framework. Subsequently, the closed-form expressions for the rejection probabilities are derived under the null hypothesis and the Lehmann alternative. The corresponding power comparison is carried out against the Lehmann alternative and the location-scale alternative through Monte-Carlo simulations. Finally, a couple of detailed illustrative examples are presented.
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TL;DR: Both univariate and multivariate nonparametric control charts are reviewed, unlike the past reviews, which did not include the multivariate charts, here they are reviewed.
Abstract: Control charts that are based on assumption(s) of a specific form for the underlying process distribution are referred to as parametric control charts. There are many applications where the...
106 citations
TL;DR: The methodology to compute the exact run length properties of the proposed chart and the algorithms to obtain the optimal chart parameters through the minimization of the out-of-control average run length are provided.
Abstract: In this paper, a new phase II EWMA-type chart for count data, based on the sign statistic, is proposed and applied to the monitoring of the location of an unknown continuous distribution. The most ...
36 citations
TL;DR: A new nonparametric AEWMA-type chart for count data, based on the sign statistic (denoted as the CAEWMA SN chart), is proposed without requiring any parametric probability distribution for the underlying process.
32 citations
31 citations
TL;DR: This paper proposes some Shewhart-type nonparametric monitoring schemes based on specific distance metrics for surveillance of multivariate as well as high-dimensional processes for quality management in manufacturing and service sectors in the Industry 4.0 era.
Abstract: Monitoring multivariate and high-dimensional data streams is often an essential requirement for quality management in manufacturing and service sectors in the Industry 4.0 era. Identifying a suitab...
28 citations