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Abstract
This paper proposes methods for determining the optimal choice of design parameters (including control limits, sample size, exponential weights for past observations, and sampling interval) for the multivariate exponentially weighted moving average (MEWMA) control chart. Extending the Lorenzen-Vance flexible cost model (Lorenzen and Vance (1986)) to develop economic designs for MEWMA control chart parameters, we then add statistical constraints to obtain economic statistical designs. The choice of parameters is dependent on the average run length (ARL) when the process is in control and out of control. Evaluating the ARL values for the MEWMA chart through simulation, we determine optimal chart parameters given cost information. Results are presented on model sensitivity (in terms of expected cost and out-of-control ARL) to misspecification of the size of the shift in the process mean vector. We also consider the impact of perturbing the sampling interval on expected cost.
Additional information
Notes on contributors
Kevin Linderman
Dr. Linderman is an Assistant Professor in the Department of Operations and Management Science in the Carlson School of Management. He is a Member of ASQ. His email address is [email protected].
Thomas E. Love
Dr. Love is an Assistant Professor in the Department of Operations Research and Operations Management in the Weatherhead School of Management. He is a Member of ASQ.
