It has previously been shown that smoothing algorithms can provide the basis for a method to detect nuclear material diversions and losses and moreover can also provide a general approach to industrial statistical process control. The present paper extends this result by showing that a set of robust smoothers also produces equivalent methods that can be used in nuclear material safeguards algorithms. Further, it is shown that these smoothers are somewhat more sensitive to loss points than the previously studied smoothers. The method is illustrated on real data.

It has previously been shown that smoothing algorithms can provide the basis for methods to detect nuclear material losses and moreover can also provide a general approach to industrial statistical process control. The present paper extends this result by showing that a set of robust smoothers also produces methods that can be used in statistical process control. Further, it is shown that these smoothers are somewhat more sensitive to out of control points than those methods previously studied. The methods are successfully illustrated on chemical process data.