Optimal average sample number of the SPRT chart for monitoring fraction nonconforming |
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Authors: | Salah Haridy Zhang Wu Ka Man Lee Nadia Bhuiyan |
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Institution: | 1. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore;2. Department of Mechanical and Industrial Engineering, Concordia University, Montreal, Quebec, Canada H3G 1M8;3. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong |
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Abstract: | The Sequential Probability Ratio Test (SPRT) control chart is a powerful tool for monitoring manufacturing processes. It is highly suitable for the applications where testing is destructive or very expensive, such as the automobile airbags test. This article studies the effect of the Average Sample Number (ASN) (i.e., the average sample size) on the chart’s performance. A design algorithm is proposed to develop the optimal SPRT chart for monitoring the fraction nonconforming p of Bernoulli processes. By optimizing the ASN and other charting parameters, the average detection speed of the SPRT chart is almost doubled. It is also found that the optimal SPRT chart significantly outperforms the optimal np and binomial CUSUM charts, in terms of Average Number of Defectives (AND), under different combinations of the design specifications. It is observed that the SPRT chart using a relatively smaller ASN and a shorter sampling interval (h) has a higher overall detection effectiveness. |
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Keywords: | Sequential Probability Ratio Test (SPRT) Control chart Average Sample Number (ASN) Average Number of Defectives (AND) Sampling interval |
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