Monitoring partially observed average kilo electron-volt emissions using exponentially weighted moving average chart

The average lifespan of particles is a key parameter in nuclear physics, critical for identifying different particle types. Modern particle detectors are highly effective at detecting the arrival of individual radioactive nuclei and observing their decay events. However, challenges arise when matching arrivals with departures, especially when departures are only partially observed. One inefficient approach involves conducting experiments with very low arrival rates to facilitate matching. The kilo electron-volt E(keV) emission is obtained during this radioactive process. We propose a Modified Distance Weighted Exponentially Weighted Moving Average (MDE) control chart for monitoring kilo electron-volt E(keV) data. Control charts are vital in quality control, offering real-time insights into process stability by distinguishing between normal (common-cause) and unusual (special cause) variations. This capability enables precise decision-making, showing when a process is within control or requires intervention, thus preventing unnecessary adjustments and costly errors. By highlighting trends and shifts, control charts foster continuous improvement, identifying areas where processes can be optimized. The proposed control chart is developed for Weibull lifetimes under type-I censoring. For constructing an efficient control charting structure, we employed the conditional median (CM) methods. The goal is to detect changes in the mean of Weibull lifetimes with censored data under both known and estimated parameter conditions. The performance of the proposed MDE chart is evaluated by the average run length (ARL). Besides a simulation study, a real-life data set on kilo electron-volt E(keV) related to the alpha decays of the 177 Lutetium isotope is also discussed. It is observed that the proposed chart is more efficient than existing control charts for monitoring kilo electron-volt E(keV) censored data