Search

Traditional multiple deferred state (MDS) sampling plan by variable is not able to decide about lots of products whose proportion parameter (p) is uncertain. In this study, fuzzy MDS (FMDS) variable sampling plan is proposed when p is not precise for the inspection of normally distributed quality characteristics in two cases known and unknown standard deviation. The plan parameters are obtained by the optimization problem, in which the objective function is considered to minimise sum of the fuzzy producer's and consumer's risks and the constraints are formulated by use of two-point approach under the specific fuzzy values of the producer's and consumer's risk, indexed by fuzzy limiting and acceptable quality levels. The proposed plan includes variable fuzzy single sampling plan (FSSP) as a special case. The obtained results show that the operating characteristic curve of FMDS variable plan seems to be closer to the ideal one with smaller required average sample number compared to variable FSSP. An industrial example is presented to illustrate the proposed plan in real applications. [ABSTRACT FROM AUTHOR]

Traditional multiple deferred state sampling plan by attribute is an inspection with crisp parameter. In this plan, in addition to using the current lot information, the future successive lots information can also be utilized on sentencing the current lot. In this study, a fuzzy multiple deferred state (FMDS) sampling plan by attribute is proposed when the proportion of defective items (p) is uncertain. So, the fuzzy probability theory is applied to construct the operating characteristic curve of mentioned plan. Then, we concentrate more on a special feature of FMDS(0,1,2) plan. We show that the proposed plan is well-defined because it converts to classic case when p is not imprecise. In order to be fully informed, some examples will also be discussed. The comparisons between the FMDS(0,1,2) plan and the existing fuzzy single sampling plan (FSSP) with zero and one acceptance number show that the proposed plan is more powerful than the FSSP in distinguishing good and bad quality of the lot. It also enjoys the least sum of the consumer and producer risks. [ABSTRACT FROM AUTHOR]