The double exponentially weighted moving average (DEWMA), which is known in the literature as Brown′s one‐parameter linear method for forecasting is proposed as a control tool for process monitoring and detecting shifts in the process mean. Obtains a closed‐form expression for the asymptotic standard deviation of the proposed DEWMA control statistic and discusses the determination of its average run length. Provides examples and comparisons between the proposed DEWMA and the standard EWMA. The results reveal that the proposed DEWMA control scheme performs much better than a Shewhart scheme for small and moderate shifts in the process mean and it has average run length properties similar to those for EWMA control schemes. However, DEWMA has smaller variability and it allows more smoothing of the data with no compromise in the sensitivity of detecting shifts in the process mean. It also shifts the range of the design parameters for optimal ARL to larger values as compared with EWMA schemes. Such properties are more desirable for some industrial processes.
We consider solutions Un(X, y) of Laplace's equation which are regular, and of bounded gradient, in the interior and exterior of a smooth closed plane curve c, and coupled across c by the jump conditions [u] 0, [Ou/Ov] 2,,gu, where g is a sufficiently smooth, positive, periodic and prescribed function of the arclength, and u,, 2, are eigenfunctions and eigenvalues to be determined. For large 2, we show that 2, O(n) and that u, is trigonometric asymptotically. Thus, the functions u, generalize the sets of solutions usually employed in solving boundary value problems in "separable" cases, and the results are confirmed in those eases, which arise by special choice of g(s). The method employed is the reduction of the problem to consideration of the eigenfunctions of the homogeneous simple layer potential. We show that iteration leads to an integral equation whose kernel behaves like the Green's function of an ordinary differential equation. Results due to Hammerstein [1] are then applied.
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