Chakraborty, NiladriHuman, Schalk WilliamBalakrishnan, N.2018-02-222017-05N. Chakraborty, S.W. Human & N. Balakrishnan (2017) A generally weighted moving average chart for time between events, Communications in Statistics - Simulation and Computation, 46:10, 7790-7817, DOI: 10.1080/03610918.2016.1252397.0361-0918 (print)1532-4141 (online)10.1080/03610918.2016.1252397http://hdl.handle.net/2263/64062Shewhart-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 (TBE). We propose a one-sided Generally Weighted Moving Average control chart to monitor the time between events (TBE); regarded as the GWMA-TBE chart. To aid the implementation of the chart, the necessary design parameters are provided. An extensive performance analysis shows that the GWMA-TBE chart is better than the well-known EWMA and Shewhart charts at detecting very small to moderate changes. Finally, a summary and some conclusions are provided.en© 2017 Taylor & Francis Group, LLC. This is an electronic version of an article published in Communications in Statistics : Simulation and Computation, vol. 46, no. 10, pp. 7790-7817, 2017. doi : 10.1080/03610918.2016.1252397 . Communications in Statistics : Simulation and Computation is available online at : http://www.tandfonline.comloi/lssp20.Time between events (TBE)Generally weighted moving average (GWMA)Average run-length (ARL)GWMA chartMarkov chainSimulationDesignRun lengthsCUSUM schemesInitial response featuresPostprint Article