A Nonparametric Synthetic Control Chart Using Sign Statistic

Khilare, S. K.; Shirke, D. T.

doi:10.1080/03610920903249576

Cited by 45 publications

(18 citation statements)

References 14 publications

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“…Wu and Yeo developed synthetic control chart for attributes. Khilare and Shirke proposed a nonparametric synthetic control chart using sign statistic for monitoring location parameter. Now, we discuss the synthetic control chart using sign statistic, defined in Equation .…”

Section: The Synthetic Control Chart Using Sign Statisticmentioning

confidence: 99%

Nonparametric Synthetic Control Charts for Process Variation

Khilare

Shirke²

2011

Quality & Reliability Eng

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In this article, we propose nonparametric synthetic and side‐sensitive synthetic control charts for controlling fraction nonconforming due to increase in the process variation. Synthetic control chart is a combination of sign and conforming run length control charts. We compare performance of the proposed control charts with the Shewhart sign and S2 charts. Our performance study shows that the proposed control charts have a higher power of detecting out‐of‐control signal. We also study the steady‐state behavior of a nonparametric synthetic control chart. We present a Markov chain model to evaluate the steady‐state average run length of the synthetic and side‐sensitive synthetic control charts. Copyright © 2011 John Wiley & Sons, Ltd.

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Section: The Synthetic Control Chart Using Sign Statisticmentioning

confidence: 99%

Nonparametric Synthetic Control Charts for Process Variation

Khilare

Shirke²

2011

Quality & Reliability Eng

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“…Das and Bhattacharya (2008) developed a nonparametric control chart for controlling variability and showed that the chart is more efficient than the Shewhart 2 S chart in detecting process variability. Khilare and Shirke (2010) proposed a nonparametric synthetic control chart using sign statistics for monitoring location parameters. Later, Shirke and Khirlare (2012) presented nonparametric synthetic control charts for process variation.…”

Section: Intropductionmentioning

confidence: 99%

A Nonparametric GA-GWMA Sign Chart for Green SCM Optimization

Tsai

2013

2013 IEEE 10th International Conference on E-Business Engineering

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This study presents a novel design of the nonparametric generally weighted moving average (GWMA) sign chart with dynamic genetic algorithm (GA) optimizer applied in green supply chain management (GSCM) to upgrade customers satisfaction of suppliers' production stabilities. In recent years, nonparametric control charts hold a significant place among statistical process control charts. Some researchers have developed various nonparametric control charts and investigated the detection capabilities of these charts. The major advantage of these control charts is that the underlying process does not specifically assume normality or any parametric distribution. Simulation studies show that the nonparametric GWMA sign chart is not flexible but can improve the detection capability in small process shifts.

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“…Wu & Spedding (2001) developed the synthetic control charts for attributes. Khilare & Shirke (2010) proposed a nonparametric synthetic control chart using sign statistic and it performs significantly better than the Shewhart type X and sign control charts. The proposed nonparametric synthetic control chart is a combination of the nonparametric sign chart and the CRL chart.…”

Section: Synthetic Control Chart Using Sign Statisticmentioning

confidence: 99%

Steady-state behavior of nonparametric control charts using sign statistic

Khilare¹,

Shirke

2015

Prod.

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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 time to signal. In this article, we discussed runs rules representation of a nonparametric synthetic control chart using sign statistic for detecting shifts in location parameter. We compared zero-state average time to signal with steady-state average time to signal of the synthetic control chart for symmetric and asymmetric distributions. We also present the m-of-m control chart using sign statistic. For comparison study, we computed average time to signal of the m-of-m control chart, the sign chart (1-of-1 chart) and the synthetic control chart for normal, Cauchy, double exponential and gamma distributions. Steady-state and zero-state performance of the m-of-m control chart with m = 2, 3 compared with the sign chart (1-of-1 chart) and synthetic control chart. The zero-state and steady-state average time to signal of the synthetic and the m-of-m control charts computed using Markov chain approach.

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A Nonparametric Synthetic Control Chart Using Sign Statistic

Cited by 45 publications

References 14 publications

Nonparametric Synthetic Control Charts for Process Variation

Nonparametric Synthetic Control Charts for Process Variation

A Nonparametric GA-GWMA Sign Chart for Green SCM Optimization

Steady-state behavior of nonparametric control charts using sign statistic

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