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Variable-attribute mixed sampling plans by intervened random effect Poisson Distribution
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Variable-attribute mixed sampling plans by intervened random effect Poisson Distribution
Variable-attribute mixed sampling plans by intervened random effect Poisson Distribution
Journal Article

Variable-attribute mixed sampling plans by intervened random effect Poisson Distribution

2010
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Overview
The decision whether to accept or reject the manufactured lot is to be made in any company in the last part of the production process. Several parameters such as AQL, LQL, IQL, MAPD are used in the construction of sampling plan. There are many methods available for acceptance testing, but Acceptance Sampling plans which take into account the Acceptable Quality Level (AQL) and Lot Tolerance Percent Defective (LTPD or LQL) are considered to be the most statistically valid. In this department the engineer has to decide on the nature of sampling plan to be adopted. Mixed sampling plan (MSP) is a double-sampling procedure involving variables inspection of the first sample and subsequent attributes inspection in the second sample if the variables inspection of the first sample does not lead to acceptance. Classical studies in the construction sampling plans are based on Poisson distribution as baseline distribution. Radhakrishnan and Sekkizhar (2007a, 2007b and 2007c) introduced intervened random effect Poisson distribution (IRPD) in the place of Poisson distribution for the construction of attribute sampling plans. Quality engineers are always interested in improving the quality level of the product to enhance the satisfaction of the customers and hence, they keep changes in the production process. IRPD is helpful for modeling such situations. This paper presents a procedure for constructing the MSP using IRPD using producer and consumer risks. Having the single sampling plan as attribute plan, the plan is constructed through acceptable and limiting quality level. Tables are constructed for easy selection of the plan.
Publisher
Bharathidasan Institute of Management, Centre for Contemporary Management Research (CECMAR)