Malela-Majika, Jean-ClaudeRapoo, E.M.Mukherjee, A.Graham, Marien Alet2019-09-202020J.C. Malela-Majika, E.M Rapoo, A. Mukherjee & M.A. Graham (2020)Distribution-free precedence schemes with a generalized runs-rule for monitoring unknown location, Communications in Statistics - Theory and Methods, 49:20, 4996-5027, DOI:10.1080/03610926.2019.1612914.0361-0926 (print)1532-415X (online)10.1080/03610926.2019.1612914http://hdl.handle.net/2263/71432Nonparametric statistical process monitoring schemes are robust alternatives to traditional parametric process monitoring schemes, especially when the assumption of normality is invalid or when we do not have enough information about the underlying process distribution. In this paper, we propose to improve the well-known precedence scheme using the 2-of-(h + 1) supplementary runs-rules (where h is a nonzero positive integer). The in-control and out-of-control performances of the proposed control schemes are thoroughly investigated using both Markov chain and simulation based approaches. We find that the proposed schemes outperform their competitors in many cases. A real-life example is given to illustrate the design and implementation of the proposed schemes.en© 2019 Taylor & Francis Group, LLC. This is an electronic version of an article published in Communications in Statistics Theory and Methods , vol. 49, no. 20, pp. 4996-5027, 2020. doi : 10.1080/03610926.2019.1612914. Communications in Statistics Theory and Methods is available online at : http://www.tandfonline.comloi/lsta20.Nonparametric schemePrecedence control schemeGeneralized 2-of-(h + 1) runs-rules schemesMarkov chain approachSimulationsPostprint Article