Abstract
The acceptance sampling plans are one of the most important tools for the inspection of a lot of products. Sometimes, it is difficult to study the variable of interest, and some additional or auxiliary information which is correlated to that variable is available. The existing sampling plans having auxiliary information are applied when the full, precise, determinate and clear data is available for lot sentencing. Neutrosophic statistics, which is the extension of classical statistics, can be applied when information about the quality of interest or auxiliary information is unclear and indeterminate. In this paper, we will introduce a neutrosophic regression estimator. We will design a new sampling plan using the neutrosophic regression estimator. The neutrosophic parameters of the proposed plan will be determined through the neutrosophic optimization solution. The efficiency of the proposed plan is discussed. The results of the proposed plan will be explained using real industrial data. From the comparison, it is concluded that the proposed sampling plan is more effective and adequate for the inspection of a lot than the existing plan, under the conditions of uncertainty.
Highlights
In industry, it is necessary to control the presence of defective items in the raw material that may cause rejection of the finished product
Neutrosophic statistics, which is the extension of classical statistics, can be applied when information about the quality of interest or auxiliary information is unclear, indeterminate, uncertain and incomplete
By comparing the proposed plan with the plan under classical statistics, we conclude that proposed sampling plan under the neutrosophic statistics is quite reasonable and effective for the lot sentencing under an indeterminate environment
Summary
It is necessary to control the presence of defective items in the raw material that may cause rejection of the finished product. The fate of the lot is based on the sample information which, leads to accepting or rejecting the submitted batch of the product In some industries, such as the cement industry and metal processing, it is hard or costly to measure the quality of interest to make a decision about the batch, so another variable which is correlated with the variable of interest is selected and measured for the lot sentencing (see [2] for example). Under the uncertainty environment, it may be that some observations in the sample or in the population are uncertain In the latter case, the sampling plan using the regression estimator under classical statistics cannot be appalled. We hope that neutrosophic acceptance sampling plans using the neutrosophic regression estimator will be more helpful for industrial engineers for lot sentencing in indeterminate environments. The results of the proposed plan will be explained by real data from industry
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
