This paper considers the problem of an acceptance sampling plan for a truncated life test when the lifetime follows the generalized Rayleigh distribution. For different acceptance numbers, confidence levels, and values of the ratio of the fixed experiment time to the specified mean life, the minimum sample sizes necessary to ensure the specified mean life are found. The operating characteristic values of the sampling plans and producer's risk are discussed. Some tables are presented and the use of the tables is illustrated by a numerical example.Consumer's risk, generalized Rayleigh distribution, operating characteristic curve, producer's risk, truncated life tests,
In this article, acceptance sampling plans are developed for the Burr type XII distribution percentiles when the life test is truncated at a pre-specified time. The minimum sample size necessary to ensure the specified life percentile is obtained under a given customer's risk. The operating characteristic values (tables) of the sampling plans as well as producer's risk are presented. The R package named spBurr is developed to implement the sampling plans. Two real datasets regarding the oil breakdown of an insulating fluid under high test voltage and the first failure times of small electric carts used for internal transportation and delivery are given as illustration.
This paper deals with the problem of determining the optimal selling price and order quantity simultaneously under EOQ model for deteriorating items. It is assumed that the demand rate depends not only on the on-display stock level but also the selling price per unit, as well as the amount of shelf/display space is limited. We formulate two types of mathematical models to manifest the extended EOQ models for maximizing profits and derive the algorithms to find the optimal solution. Numerical examples are presented to illustrate the models developed and sensitivity analysis is reported
The paper develops two new control charts and process capability ratios based on the skew normal distribution to monitor the process average and evaluate the process capability of non-normal data. Both control charts reduce to Shewhart-type control charts when the underlying distribution of quality characteristic is symmetric. A simulation study is conducted to compare the performances of the proposed control charts with those of existing control charts. Simulation results indicate that considerable improvement over those of existing control charts can be achieved when the proposed control charts are used to monitor the process average of non-normal data. Two examples are presented for illustration.
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