Modelling time-series process of an agricultural crop production process by EWMA quality control chart

Zeina Mueen Mohammed

International Journal of Mathematics in Operational Research, 2022, vol. 23, issue 1, 76-95

Abstract: Control charts are considered to be one of the main tools for analysing and controlling the steps of a product chain process. This research emphasises the control charts' versatility not only in manufacturing, but in taking enough actions for maintaining the quality of the crops with more flexibility. The time-series quality proceedings for crops that utilised the statistical process control (SPC) method serve as a case study in the EWMA control chart. One week of 168 hours of observation data is analysed with a sampling time of one hour. These measurements have been investigated over three models: AR, MA, and ARMA. The results of plotting EWMA for autoregressive (AR), moving average (MA), and ARMA models included eight points at which the process is out of control. It is found that a higher order of AR or MA model shows a lower out-of-control process. This satisfies the concluded point that higher order of the ARMA model means lower out-of-control process points.

Keywords: statistical process control; SPC; control chart; EWMA; AR; MA; ARMA. (search for similar items in EconPapers)
Date: 2022
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