Abubakar, S. S., Khoo, M. B., Saha, S., & Lee, M. H. (2021). A new exponentially weighted moving average chart with an adaptive control scheme for high yield processes—An application in injection molding process. Quality and Reliability Engineering International, 37(2), 527-540.
Albers, W., & Kallenberg, W. C. (2006). Alternative Shewhart-type charts for grouped observations. Metron, 64(3), 357-375.
Ali, S. (2021). First passage time control charts assuming power law intensity for time to jointly monitor time and magnitude. Quality and Reliability Engineering International, 37(5), 2034-2064.
Ali, S., Zafar, T., Shah, I., & Wang, L. (2020). Cumulative Conforming Control Chart Assuming Discrete Weibull Distribution. IEEE Access, 8, 10123-10133.
Amiri, A., Sogandi, F., & Ayoubi, M. (2018). Simultaneous monitoring of correlated multivariate linear and GLM regression profiles in Phase II. Quality Technology & Quantitative Management, 15(4), 435-458.
Amjadi, N., & Sabri‐Laghaie, K. (2022). Median‐rate control chart for simultaneous monitoring of frequency and magnitude of events. Quality and Reliability Engineering International, 38(1), 89-109.
Aslam, M., Khan, N., Azam, M., & Jun, C. H. (2014). Designing of a new monitoring t-chart using repetitive sampling. Information sciences, 269, 210-216.
Calvin, T. (1983). Quality control techniques for "zero defects". IEEE Transactions on Components, Hybrids, and Manufacturing Technology, 6(3), 323-328.
Chen, Y. K., & Chen, C. Y. (2012). Cumulative Conformance Count Charts with VariableSample Sizes. International Journal of Trade, Economics and Finance, 3(3), 187-193.
Chen, Y. K., & Chiu, F. R. (2023). AX/T Control Chart-Based CBM Model for Service Facility Maintenance. Arabian Journal for Science and Engineering, 48(5), 7207-722.
Di Bucchianico, A., Mooiweer, G. D., & Moonen, E. J. G. (2005). Monitoring infrequent failures of high‐volume production processes. Quality and Reliability Engineering International, 21(5), 521-528.
Dogu, E., & Noor-ul-Amin, M. (2021). Monitoring exponentially distributed time between events data: self-starting perspective. Communications in Statistics-Simulation and Computation, 1-13.
Goh, T. N. (1987). A control chart for very high yield processes. Quality Assurance, 13(1), 18-22.
Guo, B., Yang, Y., & Castagliola, P. (2024). Optimal design of time-between-event control charts with parameter estimation. Quality Engineering, 1-12.
Hakimia, A., Farughi, H., Amiri, A., & Arkata, J. (2022). Data Consumption Analysis by Two Ordinal Multivariate Control Charts. International Journal of Engineering, 35(11),2196-2204.
He, B., Xie, M., Goh, T. N., & Tsui, K. L. (2006). On control charts based on the generalized Poisson model. Quality Technology & Quantitative Management, 3(4), 383-400.
He, Y., Mi, K., & Wu, C. (2012). A New Statistical High‐Quality Process Monitoring Method: The Counted Number Between Omega‐Event Control Charts. Quality and Reliability Engineering International, 28(4), 427-436.
Hu, X., Castagliola, P., Zhong, J., Tang, A., & Qiao, Y. (2021). On the performance of the adaptive EWMA chart for monitoring time between events. Journal of Statistical Computation and Simulation, 91(6), 1175-1211.
Hu, X., Xia, F., Zhang, J., & Song, Z. (2024). Combined Shewhart–EWMA and Shewhart–CUSUM monitoring schemes for time between events. Quality and Reliability Engineering International, 40(6), 3352-3380.
Janada, K., Soltan, H., Hussein, M. S., & Abdel-Shafi, A. (2022). Angular Control Charts: A new perspective for monitoring reliability of multi-state systems. Computers & Industrial Engineering, 172, 108621.
Kumar, N., Rakitzis, A. C., Chakraborti, S., & Singh, T. (2024). Statistical design of ATS-unbiased charts with runs rules for monitoring exponential time between events. Communications in Statistics-Theory and Methods, 53(3), 815-833.
Lucas, J. M. (1985). Counted data CUSUM's. Technometrics, 27(2), 129-144.
Maleki, M. R., Ghashghaei, R., & Amiri, A. (2016). Simultaneous Monitoring of Multivariate Process Mean and Variability in the Presence of Measurement Error with Linearly Increasing Variance under Additive Covariate Model (RESEARCH NOTE). International Journal of Engineering, 29(4), 514-523.
Mirzaei Novin, M., & Amiri, A. (2023). Simultaneous monitoring of multivariate time between events and their magnitude using multivariate marked Hawkes point process. Quality Technology & Quantitative Management, 21(6), 1004-1024.
Niaz, A., Khan, M., & Ijaz, M. (2025). One‐Sided Modified EWMA Control Charts for Monitoring Time Between Events. Quality and Reliability Engineering International.
Pu, W., & Li, Y. (2023). Evaluating structural failure probability during aftershocks based on spatiotemporal simulation of the regional earthquake sequence. Engineering Structures, 275, 115267.
Qu, L., Wu, Z., Khoo, M. B., & Rahim, A. (2014). Time-between-event control charts for sampling inspection. Technometrics, 56(3), 336-346.
Rahali, D., Castagliola, P., Taleb, H., & Khoo, M. B. (2019). Evaluation of Shewhart time-between-events-and-amplitude control charts for several distributions. Quality Engineering, 31(2), 240-254.
Rahali, D., Castagliola, P., Taleb, H., & Khoo, M. B. C. (2021). Evaluation of Shewhart time‐between‐events‐and‐amplitude control charts for correlated data. Quality and Reliability Engineering International, 37(1), 219-241
Sanusi, R. A., Teh, S. Y., & Khoo, M. B. (2020). Simultaneous monitoring of magnitude and time-between-events data with a Max-EWMA control chart. Computers & Industrial Engineering, 142, 106378.
Shamstabar, Y., Shahriari, H., & Samimi, Y. (2021). Reliability monitoring of systems with cumulative shock-based deterioration process. Reliability Engineering & System Safety, 216, 107937.
Talib, A., Ali, S., & Shah, I. (2024). Max-EWMA chart for time and magnitude monitoring using generalized exponential distribution. Communications in Statistics - Simulation and Computation, 53(4), 1857–1872.
Vardeman, S., & Ray, D. O. (1985). Average run lengths for CUSUM schemes when observations are exponentially distributed. Technometrics, 27(2), 145-150.
Wu, Z., Khoo, M. B., Shu, L., & Jiang, W. (2009a). An np control chart for monitoring the mean of a variable based on an attribute inspection. International Journal of Production Economics, 121(1), 141-147.
Wu, Z., Jiao, J., & He, Z. (2009b). A control scheme for monitoring the frequency and magnitude of an event. International Journal of Production Research, 47(11), 2887-2902.
Xie, M., Goh, T. N., Kuralmani, V., & Kuralmani, V. (2002). Statistical models and control charts for high-quality processes. Springer Science & Business Media.
Zwetsloot, I. M., Mahmood, T., & Woodall, W. H. (2020). Multivariate time-between-events monitoring: An overview and some overlooked underlying complexities. Quality Engineering, 33(1), 13-25.
Zwetsloot, I. M., Mahmood, T., Taiwo, F. M., & Wang, Z. (2023). A real‐time monitoring approach for bivariate event data. Applied Stochastic Models in Business and Industry, 39(6), 789-817.