Abstract
Traditional Hotelling T 2 control chart is sensitive to the masking and swam** effect. Recently, an alternative robust control chart based on a new robust estimator known as minimum vector variance (MVV) estimator, denoted as T 2 MVV , was introduced in Phase II data. In general, T 2 MVV was able to detect out-of-control signal and simultaneously control false alarm rate even as the dimension increased. However, the estimated upper control limits (UCL) of T 2 MVV were large compared to the traditional chart. To tackle this problem, we multiplied the constant correction factors to obtain consistency at multivariate normal data and guarantee asymptotic unbiased of MVV estimators. The improved MVV estimators were applied in Hotelling T 2 chart by using real data from aircraft industry. The result showed great improvement in the control limit values while maintaining its good performance in terms of probability of detection.
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Ali, H., Syed-Yahaya, S.S., omar, Z. (2014). The Application of Consistent Minimum Vector Variance (MVV) Estimators on Hotelling T 2 Control Chart. In: Kasim, A., Wan Omar, W., Abdul Razak, N., Wahidah Musa, N., Ab. Halim, R., Mohamed, S. (eds) Proceedings of the International Conference on Science, Technology and Social Sciences (ICSTSS) 2012. Springer, Singapore. https://doi.org/10.1007/978-981-287-077-3_27
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DOI: https://doi.org/10.1007/978-981-287-077-3_27
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