The objective of this particular study was to recover valuable metals from waste plasma display panels using high energy ball milling with subsequent acid dissolution. Dissolution of milled (PDP) powder was studied in HCl, HNO3, and H2SO4 acidic solutions. The effects of dissolution acid, temperature, time, and PDP scrap powder to acid ratio on the leaching process were investigated and the most favorable conditions were found: (1) valuable metals (In, Ag, Mg) were recovered from PDP powder in a mixture of concentrated hydrochloric acid (HCl:H2O = 50:50); (2) the optimal dissolution temperature and time for the valuable metals were found to be 60°C and 30 min, respectively; (3) the ideal PDP scrap powder to acid solution ratio was found to be 1:10. The proposed method was applied to the recovery of magnesium, silver, and indium with satisfactory results.
In many cases, a X̅ control chart based on a performance variable is used in industrial fields. Typically, the control chart monitors the measurements of a performance variable itself. However, if the performance variable is too costly or impossible to measure, and a less expensive surrogate variable is available, the process may be more efficiently controlled using surrogate variables. In this paper, we present a model for the economic statistical design of a VSI (Variable Sampling Interval) X̅ control chart using a surrogate variable that is linearly correlated with the performance variable. We derive the total average profit model from an economic viewpoint and apply the model to a Very High Temperature Reactor (VHTR) nuclear fuel measurement system and derive the optimal result using genetic algorithms. Compared with the control chart based on a performance variable, the proposed model gives a larger expected net income per unit of time in the long-run if the correlation between the performance variable and the surrogate variable is relatively high. The proposed model was confined to the sample mean control chart under the assumption that a single assignable cause occurs according to the Poisson process. However, the model may also be extended to other types of control charts using a single or multiple assignable cause assumptions such as VSS (Variable Sample Size) X̅ control chart, EWMA, CUSUM charts and so on.
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