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The variability of the quantity and purity of the recovered materials is a serious drawback for the application of electrostatic separation technologies to the recycling of granular wastes. In a series of previous articles we have pointed out how capability and classic control chart concepts could be employed for better mastering the outcome of such processes. In the present work, the multiple exponentially weighted moving average (MEWMA) control chart is introduced and shown to be more effective than the Hotelling T2 chart for monitoring slow varying changes in the electrostatic separation of granular mixtures originating from electric and electronic equipment waste. The operation of the industrial process was simulated by using a laboratory roll-type electrostatic separator and granular samples resulting from shredded electric cable wastes. The 25 tests carried out during the observation phase enabled the calculation of the upper and lower control limits for the two control charts considered in the present study. The 11 additional tests that simulated the monitoring phase pointed out that the MEWMA chart is more effective than Hotelling's T(2) chart in detecting slow varying changes in the outcome of a process. As the reverse is true in the case of abrupt alterations of monitored process performances, simultaneous usage of the two control charts is strongly recommended. While this study focused on a specific electrostatic separation process, using the MEWMA chart together with the well known Hotelling's T(2) chart should be applicable to the statistical control of other complex processes in the field of waste processing.

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