Title: Double generally weighted moving average chart for time between events
Authors: Schalk Human - University of Pretoria (South Africa) [presenting]
Janet Van Niekerk - University of Pretoria (South Africa)
Hossein Masoumi Karakani - University of Pretoria (South Africa)
Abstract: Control charts continue to play a key role in the quality control (QC) environment. However, the Shewhart-type attributes charts are inefficient at detecting small/minor changes. To overcome this shortcoming, an alternative approach is to use time-weighted control charts (also known as memory-based control charts) to monitor the time between events (TBE); these time-weighted control charts use all the information from the start until the most recent sample to decide if a process is in-control (IC) or out-of-control (OOC). To this end, a generalized type of time-weighted control chart is proposed to monitor the TBE. This chart is called the Double Generally Weighted Moving Average Time Between Events (DGWMA-TBE), which includes many of the well-known existing time-weighted control charts as special or limiting cases. Evaluation of the run-length distribution reveals that the proposed DGWMA-TBE chart outperforms the Generally Weighted Moving Average (GWMA), Exponentially Weighted Moving Average (EWMA) and Shewhart charts at detecting small to moderate shifts.