Monitoring Tractor Performance Using Shewhart And Exponentially Weighted Moving Average Charts

Abstract

Statistical process control has been widely used in agricultural operations for monitoring and improving process quality. This study aims to evaluate the Shewhart and exponentially weighted moving average (EWMA) control charts to monitor the performance of an agricultural tractor–planter set. The design is completely randomized based on the assumptions of statistical process control and comprises two treatments: day and night shift treatments. The data to assess the performance of the tractor–planter set are collected during the day and night shifts and used to evaluate the operating speed, motor rotation, engine oil pressure and water temperature, and hourly fuel consumption. The dataset comprised 40 samples compiled from the frontal monitor column inside a tractor cab. It is concluded that both Shewhart and MMEP/EWMA control charts can be used to evaluate engine performance based on the quality indicator parameters investigated, regardless of the normality assumption of the datasets.