Testing quality based on asymmetric capability index C pmk and its pharmaceutical application

Statistical hypotheses testing is a useful technique for determining the level of the production process capability. Testing the process capability index Cpmk can be very challenging due to the complexity of the distribution of its natural estimator, even if the underlying distribution is normal. To handle processes with asymmetric specification limits, this paper proposes a simulated Monte Carlo test on capability index Cpmk based on its natural estimator. Detailed steps of an algorithm are provided to simulate the components for making a reliable decision in testing quality. Furthermore, a real application is investigated in a pharmaceutical company to demonstrate how the proposed simulation approach performs.