Single Mixed Sampling Plan Based on Yield Index for Linear Profiles

Wang, Fu‐Kwun; Lo, Shih-Che

doi:10.1002/qre.1892

Cited by 6 publications

(7 citation statements)

References 20 publications

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“…This problem was solved in Klufa (2008), the exact solution is in Kaspříková (2012) -LTPDvar is an add-on package to the R software (see R Development Core Team 2011). Similar problems are solved in Chen and Chou (2001), Kaspříková and Klufa (2015), Wilrich (2012), Ho et al (2012), Yen et al (2014), Klufa (2015), Aslam et al (2015), Wang and Lo (2015), Balamurali et al (2014).…”

mentioning

confidence: 68%

Economic efficiency of the AOQL single sampling plans for the inspection by variables

Klůfa¹

2016

AGR ECON-CZECH

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Th e paper refers to the AOQL (Average Outgoing Quality Limit) single sampling plans when the remainder of the rejected lots is inspected. Th ese rectifying AOQL plans for inspection by variables were created by the author of this paper and published in the Statistical Papers. Th ese new plans were compared with the corresponding Dodge-Romig AOQL plans for inspection by attributes from the economic point of view. Numerical investigations confi rm that under the same protection of consumer, the AOQL plans for inspection by variables are in many situations more economical than the corresponding Dodge-Romig AOQL attribute sampling plans. Th e dependence of the saving of the inspection cost on the input parameters of acceptance sampling (the average outgoing quality limit, the lot size and the process average proportion defective) is analysed in the paper. Moreover, a criterion for deciding if the inspection by variables should be considered instead of the inspection by attributes is suggested in the paper.

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confidence: 68%

Economic efficiency of the AOQL single sampling plans for the inspection by variables

Klůfa¹

2016

AGR ECON-CZECH

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“…The choice of the optimal EWMA parameter is based on minimizing the sum of squares error from previous lots; that is,

S S E = {\sum_{t = 2}^{T} ({\overset{C}{true}}_{p u A}^{E W M A_{t}} - {\overset{C}{true}}_{p u A})}^{2}

. We adopted the R code developed by Wang to determine the value of λ () Step 4Make a decision: accept the lot if

{\overset{true^}{C}}_{p u A}^{E W M A_{t}} \geq c

, where c is critical value; otherwise reject it. Using Equation , the OC function of our proposed plan is derived as

P_{a} ((), C) = P ((), {\overset{true^}{C}}_{p u A}^{E W M A_{t}} \geq c) = 1 - normalΦ ((), \frac{((), c - C_{A Q L})}{\sqrt{(\frac{λ}{2 - λ}) \frac{(2 + 9 G^{2}) {([], ϕ ((), 3 G))}^{2}}{18 m^{2} n {([], ϕ ((), 3 C_{A Q L}))}^{2}}}}),

where C = C puA .…”

Section: Proposed Single Sampling Planmentioning

confidence: 99%

“…Aslam et al presented the EWMA statistic with a process mean for an acceptance sampling plan. Recently, Wang implemented the EWMA model with the yield index S pkA for linear profiles with two‐sided specifications. However, the asymptotic distributions of S pkA and C pkA are totally different.…”

Section: Introductionmentioning

confidence: 99%

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Implementing EWMA Yield Index for Simple Linear Profiles with One-sided Specifications in Product Acceptance Determination

Wang

Huang

Tamirat

2016

Qual. Reliab. Engng. Int.

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In this paper, we propose a new acceptance sampling plan based on the exponentially weighted moving average (EWMA) with the yield index for simple linear profiles with one-sided specifications. The EWMA model provides information about current lots' and preceding lots' quality characteristics. The plan parameters are determined according to the smoothing constant of the EWMA statistic and various risks between the producer and the customer. As the smoothing constant equals one, the proposed plan becomes the traditional single sampling plan. The number of profiles required for lot sentencing using the proposed method is more economical than the traditional single sampling plan. The smaller the value of the smoothing constant, the lower the number of profiles required. A practical example from wind turbine manufacturing is applied to illustrate the performance of the proposed approach.

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“…Subsequently, the ASN of the dependent plan will be lower. Wang and Lo developed a single mixed sampling plan based on the yield index for linear profiles. Based on our knowledge, there is no work on dependent mixed sampling plans and the mixed repetitive sampling plan based on the yield index for linear profiles.…”

Section: Introductionmentioning

confidence: 99%

Dependent Mixed and Mixed Repetitive Sampling Plans for Linear Profiles

Wang

Tamirat

et al. 2017

Quality & Reliability Eng

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In this paper, we present two new dependent mixed sampling plans and a mixed repetitive sampling plan based on the process yield index for linear profiles. A mixed sampling plan includes two stages; the first stage is a combined test by variables and by attributes, and the second stage is tested by attributes only. The first plan is based on the traditional mixed sampling scheme without marginal quality, and the second plan is based on the modified mixed sampling scheme with marginal quality. If a lot is very bad, the probability it can be rejected with the small initial sample is higher for dependent mixed sampling with marginal quality. We compare dependent mixed plans with other types of double sampling plans; the former outperforms the others with respect to average sample number. Additionally, the number of profiles required in the first stage is much smaller than in the second stage. When the inspection is costly and destructive, a mixed repetitive sampling plan includes one stage that combines the inspection by attributes and by variables and allows resampling in some conditions. We compare the mixed repetitive sampling plan with the repetitive sampling plans by attributes and by variables. The probability of acceptance using the mixed repetitive sampling plan performs better than the repetitive sampling plans by attributes and by variables. Three examples are used to illustrate the proposed methods. Copyright © 2017 John Wiley & Sons, Ltd.

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Single Mixed Sampling Plan Based on Yield Index for Linear Profiles

Cited by 6 publications

References 20 publications

Economic efficiency of the AOQL single sampling plans for the inspection by variables

Economic efficiency of the AOQL single sampling plans for the inspection by variables

Implementing EWMA Yield Index for Simple Linear Profiles with One-sided Specifications in Product Acceptance Determination

Dependent Mixed and Mixed Repetitive Sampling Plans for Linear Profiles

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