The extended discrete reliability growth planning model

Abstract

The planned reliability growth curve gives the interim milestone reliability targets in which the system is judged as the reliability growth program progresses across single or multiple test phases. At the end of each test phase the system reliability is assessed and compared to the corresponding value on the planned reliability growth curve. If the assessed reliability is on or above the milestone value, the reliability program continues. If the assessed reliability is below the milestone value changes in the reliability program may be necessary. It is therefore important that the planned reliability growth curve be realistic and based on input parameters and assumptions that adequately reflect the configuration and characteristics of the system. This paper addresses the development of a reliability growth planning model for discrete systems that includes a growth rate parameter which is a user input. The motivation for this paper is that the current DoD reliability growth planning model for discrete systems, the Discrete PM2 model, Refs.10, 11, does not have a growth rate or a comparable quality. The consequence of this is that there is no parameter in the PM2 model in which the user can input, or calculate, that gives the rate of growth and provides a basis for determining the test resources that are necessary and realistic in order to attain the reliability goal or requirement In this paper the Extended Discrete planning model is presented which has the same fundamental inputs as the Extended Continuous Reliability Growth planning, including a growth parameter. This discrete planning models allows for the development of a planned curve that utilizes historical growth rate data and provides a parameter that can aid in the practical allocated of test resources. The Extended Discrete planning model presented in this paper has a number of engineering and management input parameters that together with the growth parameter provide a broader planning capability than exists in current models.