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Quality Technology & Quantitative Management Volume 3, 2006 - Issue 3
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Original Articles

A Comparative Study of Exponential Time between Events Charts

J. Y. LiuDepartment of Industrial and Systems Engineering, National University of Singapore, SingaporeView further author information
,
M. XieDepartment of Industrial and Systems Engineering, National University of Singapore, SingaporeView further author information
,
T. N. GohDepartment of Industrial and Systems Engineering, National University of Singapore, SingaporeView further author information
&
P. R. SharmaOCBC Bank, SingaporeView further author information
Pages 347-359 | Received 01 Mar 2005, Accepted 01 Jan 2006, Published online: 09 Feb 2016

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Nirpeksh Kumar, Athanasios C. Rakitzis, Subha Chakraborti & Tribhuvan Singh. (2024) Statistical design of ATS-unbiased charts with runs rules for monitoring exponential time between events. Communications in Statistics - Theory and Methods 53:3, pages 815-833.
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Eralp Dogu & Muhammad Noor-ul-Amin. (2023) Monitoring exponentially distributed time between events data: self-starting perspective. Communications in Statistics - Simulation and Computation 52:3, pages 1104-1118.
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XueLong Hu, YuLong Qiao, PanPan Zhou, JianLan Zhong & Shu Wu. (2023) Modified one-sided EWMA charts for monitoring time between events. Communications in Statistics - Simulation and Computation 52:3, pages 1041-1056.
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YuLong Qiao, JinSheng Sun, Philippe Castagliola & XueLong Hu. (2022) Optimal design of one-sided exponential EWMA charts based on median run length and expected median run length. Communications in Statistics - Theory and Methods 51:9, pages 2887-2907.
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Nirpeksh Kumar, Subha Chakraborti & Philippe Castagliola. (2022) Phase II exponential charts for monitoring time between events data: performance analysis using exact conditional average time to signal distribution. Journal of Statistical Computation and Simulation 92:7, pages 1457-1486.
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Nirpeksh Kumar. (2022) Statistical design of phase II exponential chart with estimated parameters under the unconditional and conditional perspectives using exact distribution of median run length. Quality Technology & Quantitative Management 19:1, pages 1-18.
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Vasileios Alevizakos & Christos Koukouvinos. (2020) A double exponentially weighted moving average chart for time between events. Communications in Statistics - Simulation and Computation 49:10, pages 2765-2784.
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Nirpeksh Kumar. (2020) Conditional analysis of Phase II exponential chart for monitoring times to an event. Quality Technology & Quantitative Management 17:3, pages 285-306.
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Dorra Rahali, Philippe Castagliola, Hassen Taleb & Michael B. C. Khoo. (2019) Evaluation of Shewhart time-between-events-and-amplitude control charts for several distributions. Quality Engineering 31:2, pages 240-254.
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N. Kumar, S. Chakraborti & A. C. Rakitzis. (2017) Improved Shewhart-Type Charts for Monitoring Times Between Events. Journal of Quality Technology 49:3, pages 278-296.
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Nirpeksh Kumar & Subha Chakraborti. (2017) Bayesian Monitoring of Times Between Events: The Shewhart t-Chart. Journal of Quality Technology 49:2, pages 136-154.
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Jun Yang, Huan Yu, Yuan Cheng & Min Xie. (2015) Design of exponential control charts based on average time to signal using a sequential sampling scheme. International Journal of Production Research 53:7, pages 2131-2145.
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Eduardo Santiago & Joel Smith. (2013) Control Charts Based on the Exponential Distribution: Adapting Runs Rules for the t Chart. Quality Engineering 25:2, pages 85-96.
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