Evaluation of the Run-Length Probability Distribution for CUSUM Charts: Assessing Chart Performance

Luceño, Alberto; Puig-Pey, Jaime

doi:10.1080/00401706.2000.10485714

Cited by 22 publications

(13 citation statements)

References 32 publications

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“…In contrast to the above approach, the CUSUMs we suggest in the present paper have in-control run length distributions and false alarm rates that may be studied using existing methods, tables, and software for conventional CUSUM schemes (Hawkins and Olwell, 1998;Luceño and Puig-Pey, 2000). In addition, existing results and methods may be used to design the proposed CUSUMs to have the desired in-control ARL and false alarm rate.…”

Section: Introductionmentioning

confidence: 82%

A self-starting procedure for monitoring process quality in multistage manufacturing systems

Zantek¹,

Wright²,

Plante³

2006

IIE Transactions

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Manufacturing systems typically contain processing and assembly stages whose output quality is significantly affected by the output quality of preceding stages. The deficiencies of using standard statistical process-monitoring procedures in such systems have been highlighted in the literature. This article proposes a procedure to monitor process and product quality in multistage systems. By accounting for the quality of the input to each stage, the procedure not only detects the presence of out-of-control conditions but also helps to identify the stages responsible for such departures. We extend previous research to the common case where the process parameters are unknown. An extensive performance study shows that the procedure is effective in detecting out-of-control conditions and that it convincingly outperforms existing methods. We illustrate the use of the procedure using production line data from a major electronics manufacturer.

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Section: Introductionmentioning

confidence: 82%

A self-starting procedure for monitoring process quality in multistage manufacturing systems

Zantek¹,

Wright²,

Plante³

2006

IIE Transactions

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“…Equation (10) can be solved recursively on L(s), 0 ≤ s ≤ γ. An efficient algorithm is provided in [18].…”

Section: B First Passage Time Under P ∞mentioning

confidence: 99%

“…conditional batch size distribution is approximated using, [32], as (18) where, ϕ represents the standard Gaussian pdf. Since the overshoot distribution is exponential, for light tailed Z k ,…”

Section: Distribution Of the Batchmentioning

confidence: 99%

Generalized Analysis of a Distributed Energy Efficient Algorithm for Change Detection

Banerjee

Sharma

Kavitha

et al. 2011

IEEE Trans. Wireless Commun.

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We propose an energy efficient distributed cooperative Change Detection scheme called DualCUSUM based on Page's CUSUM algorithm. In the algorithm, each sensor runs a CUSUM and transmits only when the CUSUM is above some threshold. The transmissions from the sensors are fused at the physical layer. The channel is modeled as a Multiple Access Channel (MAC) corrupted with noise. The fusion center performs another CUSUM to detect the change. The algorithm performs better than several existing schemes when energy is at a premium. We generalize the algorithm to also include nonparametric CUSUM and provide a unified analysis. Our results show that while the false alarm probability is smaller for observation distribution with a lighter tail, the detection delay is asymptotically the same for any distribution. Consequently, we provide a new viewpoint on why parametric CUSUM performs better than nonparametric CUSUM. In the process, we also develop new results on a reflected random walk which can be of independent interest.

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“…As a result of this research new charts were developed. For example, the EWMA chart [3,4], CUSUM chart [5,6] and the synthetic-X [7][8][9][10]. These charts exhibit better performance in detecting small shifts, although they are more complex to use.…”

Section: Introductionmentioning

confidence: 96%

Synthetic-X¯control charts optimized for in-control and out-of-control regions

Aparisi

Luna

2009

Computers & Operations Research

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Evaluation of the Run-Length Probability Distribution for CUSUM Charts: Assessing Chart Performance

Cited by 22 publications

References 32 publications

A self-starting procedure for monitoring process quality in multistage manufacturing systems

A self-starting procedure for monitoring process quality in multistage manufacturing systems

Generalized Analysis of a Distributed Energy Efficient Algorithm for Change Detection

Synthetic-X¯control charts optimized for in-control and out-of-control regions

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