On reassessment of the HWMA chart for process monitoring

Muhammad Riaz, Shabbir Ahmad, Tahir Mahmood*, Nasir Abbas

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

In the recent literature of process monitoring, homogeneously weighted moving average (HWMA) type control charts have become quite popular. These charts are quite efficient for early detection of shifts, especially of smaller magnitudes, in process parameters such as location and dispersion. A recent study pointed out a few concerns related to HWMA charts that mainly relate to its steady-state performance. It needs to be highlighted that the initial studies on HWMA focused only on the zero-state performance of the chart relative to other well-known memory charts. This study reinvestigates the performance of the HWMA chart under zero and steady states at various shifts. Using the Monte Carlo simulation method, a detailed comparative analysis of the HWMA chart is carried out relative to the exponentially weighted moving average (EWMA) chart with time-varying limits. For several values of design parameters, the in-control and out-of-control performance of these charts is evaluated in terms of the average run length (ARL). It has been observed that the structure of the HWMA chart has the ability to safeguard the detection ability and the run-length properties under various delays in process shifts. More specifically, it has been found that HWMA chart is superior to the EWMA chart for several shift sizes under zero state and is capable of maintaining its dominance in case the process experiences a delay in shift. However, the steady-state performance depends on the suitable choice of design parameters. This study provides clear cut-offs where HWMA and EWMA are superior to one another in terms of efficient monitoring of the process parameters.
Original languageEnglish
Article number1129
Number of pages13
JournalProcesses
Volume10
Issue number6
DOIs
Publication statusPublished - 5 Jun 2022
Externally publishedYes

Keywords

  • exponentially weighted moving average chart
  • homogeneously weighted moving average chart
  • steady state
  • zero state

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