Selection of multiple deferred (dependent) state sampling plans

Kuralmani, V.; Govlndaraju, K.

doi:10.1080/03610929208830851

Cited by 26 publications

(8 citation statements)

References 11 publications

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“…The ARL measure for the chart performance is studied by many authors including . The MDS sampling scheme has been utilized in the SPC by many authors including Ahmad et al, Aslam et al, Azam et al, Khan et al, and Knoth …”

Section: Introductionmentioning

confidence: 99%

Design of a t‐chart using generalized multiple dependent state sampling

Aslam

Raza

Ahmad

2019

Quality & Reliability Eng

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In this article, a new t-chart based on generalized multiple dependent state (GMDS) sampling is proposed for efficient monitoring of a process by assuming that the time between events follows the exponential distribution. The proposed t-chart has two pair of control limits and utilizes the past sample information with the current sample information. The control chart coefficients are estimated by considering different values of the in-control average run lengths. The proposed t-chart is compared with the existing chart by using the out-of-control average run length and extra quadratic loss function. The comparison reveals that the proposed charting strategy has better shift detection ability in process mean. An illustrative example is given for the practical implementation of the proposed chart.

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Section: Introductionmentioning

confidence: 99%

Design of a t‐chart using generalized multiple dependent state sampling

Aslam

Raza

Ahmad

2019

Quality & Reliability Eng

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“…First, single sampling can impose a psychological disadvantage on the supplier, since no further reference or second chance is given for rejected lots (Govindaraju 1990;. Second, in advanced manufacturing processes, supplier production is frequently continuous, so the quality of preceding and/or successive lots is expected to be homogeneous and dependent (Kuraimani and Govindaraju 1992). In this situation, a dichotomous rule that excludes dependent information is ineffective in practice and detrimental to long-term supplier-buyer cooperation.…”

Section: Introductionmentioning

confidence: 98%

A lots-dependent variables sampling plan considering supplier’s process loss and buyer’s stipulated specifications requirement

Wang

Shu

2015

International Journal of Production Research

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A well-established scheme and mechanism for deciding product acceptance is perceived as a win-win situation for the long-term supplier-buyer relationship. In this paper, we develop a lots-dependent variables sampling scheme for product acceptance determination. The dependent state is based on the sample information of the process capability index that incorporates the supplier's process loss and the buyer's demanded specifications requirement. This main scheme is implemented by a three-rule process that accepts or rejects a related lot conditional on the sample results of past lots. The plan-operational parameters satisfying the desired quality levels and constraining the supplier-buyer risks are determined by a non-linear optimisation model. In performance comparisons, our proposed plan demonstrated higher cost effectiveness and discriminatory power than the traditional variables single sampling plan. Finally, industrial applicability of our recommended sampling plans was investigated in a case study.

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“…Balamurali et al [2] developed a Bayesian multiple dependent state sampling plan for the Gamma-Poisson distribution. MDS sampling has been explored by many authors, including references [7][8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Shewhart Attribute and Variable Control Charts Using Modified Multiple Dependent State Sampling

2019

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In this article, modified multiple dependent (or deferred) state sampling control charts for the attribute and the variable quality characteristics are presented. The proposed control charts are designed using the symmetry property of the normal distribution. The control chart coefficients are estimated through simulation at different levels of the parameters using the normal distribution. The proposed control chart scheme is evaluated by calculating the in-control average run lengths and out-of-control average run lengths. Tables are constructed for the selection of parameters for different control limit coefficients under several shift levels for the attribute data as well as the variable data. Examples are included for the practical application of the proposed control chart schemes. The proposed control chart scheme is also compared with the existing control charts. It has been observed that the proposed schemes are better in quick detection of the out-of-control processes.

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Selection of multiple deferred (dependent) state sampling plans

Cited by 26 publications

References 11 publications

Design of a t‐chart using generalized multiple dependent state sampling

Design of a t‐chart using generalized multiple dependent state sampling

A lots-dependent variables sampling plan considering supplier’s process loss and buyer’s stipulated specifications requirement

Shewhart Attribute and Variable Control Charts Using Modified Multiple Dependent State Sampling

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