University of Tehran Journal of Sciences, Islamic Republic of Iran 1016-1104 27 3 2016 07 01 A New Bootstrap Based Algorithm for Hotelling’s T2 Multivariate Control Chart 269 278 57658 EN A. Mostajeran 1Department of Statistics, University of Isfahan, 81744, Isfahan, Islamic Republic of Iran N. Iranpanah 1Department of Statistics, University of Isfahan, 81744, Isfahan, Islamic Republic of Iran R. Noorossana 2Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Islamic Republic of Iran Journal Article 2015 09 06 <span>Normality is a common assumption for many quality control charts. One should expect misleading results once this assumption is violated. In order to avoid this pitfall, we need to evaluate this assumption prior to the use of control charts which require normality assumption. However, in certain cases either this assumption is overlooked or it is hard to check. Robust control charts and bootstrap control charts are two remedial measures that we could use to overcome this issue. In this paper, a new bootstrap algorithm is proposed to construct Hotelling’s T²control chart. The performance of proposed chart is evaluated through a simulation study. Our results are compared to the traditional Hotelling’s T²control chart results and the bootstrap results reported by Phaladiganon <em>et al</em>. [13] using in-control and out-of-control average run lengths denoted by ARL₀ and ARL₁, respectively. The latter case is obtained when the process mean is subject to sustained shifts. Numerical results indicate that the proposed algorithm performs better than the above mentioned methods. The new bootstrap algorithm is also applied to a real data set.</span> https://jsciences.ut.ac.ir/article_57658_500019848ae5b7748d79c3943f38f2f9.pdf