To increase flexibility or to develop covariate models in various ways, new parameters can be added to existing families of distributions or a new family of distributions can be compounded with well-known standard normal distribution. In this paper, a trigonometric-type distribution was developed in order to come up with flexible distribution without adding parameters, considering Exponential distribution as the baseline distribution and Sine-G as the generator. The proposed distribution is referred to as Sine Exponential Distribution. Statistical features, including the moment, moment generating function, entropy, and order statistics were obtained. The proposed distribution's parameters were estimated using the Maximum Likelihood method. Using real datasets, the model's importance was demonstrated. The newly developed model was proven to be better than its competitors.
Some industrial data often come with uncertainty, which in some cases depends on the decision of those responsible for taking the measurement in the production process. While the fuzzy approach helps to tackle the ambiguity that arises in the measurement, an interval type-2 fuzzy set deals with such uncertainty better due to its flexibility over the control limits of its control chart. This paper aims to develop an Interval Type-2 fuzzy Exponentially Weighted Moving Average Control Chart (IT2FEWMA) under the fuzzy type-2 condition. This development will facilitate monitoring small and moderate shifts in the production process in conditions of uncertainty.
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