Steady-State Behavior of Nonparametric Synthetic Control Chart Using Signed-Rank Statistic

Vilas Y Pawar, Digambar Tukaram Shirke, Shashikant Kuber Khilare

Abstract


If process is running for a long period in an in-control condition, it will reach in a steady-state condition. In order to study the long term properties of a control chart, it is appropriate to investigate the steady-state average run length. In this paper we study zero-state and steady-state behaviour of a nonparametric synthetic control chart using signed-rank statistic. The zero-state average time to signal and steady-state average time to signal are computed using Markov chain approach. In Comparison study, steady-state average time to signal is compared with zero-state average time to signal for various symmetric distributions. Usefulness of the proposed control chart explored through by giving numerical example.


Keywords


: Nonparametric, signed-rank, synthetic, runs rule, steady-state and average time to signal.

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DOI: http://dx.doi.org/10.18187/pjsor.v14i1.2029

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Title

Steady-State Behavior of Nonparametric Synthetic Control Chart Using Signed-Rank Statistic

Keywords

: Nonparametric, signed-rank, synthetic, runs rule, steady-state and average time to signal.

Description

If process is running for a long period in an in-control condition, it will reach in a steady-state condition. In order to study the long term properties of a control chart, it is appropriate to investigate the steady-state average run length. In this paper we study zero-state and steady-state behaviour of a nonparametric synthetic control chart using signed-rank statistic. The zero-state average time to signal and steady-state average time to signal are computed using Markov chain approach. In Comparison study, steady-state average time to signal is compared with zero-state average time to signal for various symmetric distributions. Usefulness of the proposed control chart explored through by giving numerical example.


Date

2018-03-09

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol. 14 No. 1, 2018



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810