In this article, an Isolated Truncated Chain deferred Sampling Plan for Weibull product life distribution is proposed when the testing is truncated at a specified time. This type of sampling plan is used to save the testing time. The optimal sample sizes, required for testing product quality to ascertain a true mean life are obtained under a given Maximum Allowable Percent Defective, test termination ratios and acceptance numbers. The operating characteristics formula of the proposed plan was developed. The operating characteristics and mean-ratio were used to assess the performance of the plan. The study revealed that: Weibull distribution have low failure rate; as mean life ratio increase, the failure rate reduces and the minimum sample size increase as the acceptance number, maximum allowable percent defective and experiment time ratio increases; The study concluded that the modified required minimum sample sizes were smaller compared to those in the literature making it a more economical plan to be adopted when time and cost of production is expensive and the testing is destructive.

An Exponentiated Inverted Weibull Distribution (EIWD) has a hazard rate (failure rate) function that is unimodal, thus making it less efficient for modeling data with an increasing failure rate (IFR). Hence, the need to generalize the EIWD in order to obtain a distribution that will be proficient in modeling these types of dataset (data with an increasing failure rate). This paper therefore, extends the EIWD in order to obtain Weibull Exponentiated Inverted Weibull (WEIW) distribution using the Weibull-Generator technique. Some of the properties investigated include the mean, variance, median, moments, quantile and moment generating functions. The explicit expressions were derived for the order statistics and hazard/failure rate function. The estimation of parameters was derived using the maximum likelihood method. The developed model was applied to a real-life dataset and compared with some existing competing lifetime distributions. The result revealed that the (WEIW) distribution provided a better fit to the real life dataset than the existing Weibull/Exponential family distributions.

This paper is aimed at developing a new truncated sampling plan that uses information from precedent and successive lots for lot disposition with a pretention that the life-time of a particular product assumes a Log-logistic distribution. A new Two-pronged Truncated Deferred Sampling Plan (TTDSP) for Log-logistic distribution is proposed when the testing is truncated at a precise time. The best possible sample sizes are obtained under a given Maximum Allowable Percent Defective (MAPD), Test Suspension Ratios (TSR) and acceptance numbers (c). A formula for calculating the operating characteristics of the proposed plan is also developed. The operating characteristics and mean-ratio values were used to measure the performance of the plan. The findings of the study show that: Log-logistic distribution has a decreasing failure rate; furthermore, as mean-life ratio increase, the failure rate reduces; the sample size increase as the acceptance number, test suspension ratios and maximum allowable percent defective increases. The study concludes that the new minimum sample sizes were smaller which makes the plan a more economical plan to adopt when cost and time of production is costly and the experiment being destructive.