Author : Suresh Kumar and Bijan Sarkar

The life data analysis is an important piece of the pie, but performing just the analysis is not enough to achieve reliable products. Rather, there are a variety of activities involved in an effective reliability program and in arriving at reliable products. In this paper two sets of photovoltaic modules were tested for the estimation of reliability. Whether either design meets the desired reliability goal. A comparison of sample averages using a student’s t test reveals no statistical difference between the average cycles for Designs. But as a simple measure of central tendency, the sample average gives no information about the spread or shape of the distribution of failure times. Could the two designs’ averages be the same, but their reliability be quite different? Reliability must be designed into products and processes using the best available science-based methods. Reliability practices must begin early in the design process and must be well integrated into the overall product development cycle. Design For Reliability (DFR) approach is suitable that describes the entire set of tools that support product and process design (typically from early in the concept stage all the way through to product obsolescence) to ensure that customer expectations for reliability are fully met throughout the life of the product. So a Scientific approach is adopted for comparing the reliability of the two designs. For this the Weibull analysis is performed. By performing a simple linear regression, parameter estimates can be obtained that will enable to make inferences about the two designs reliability.

Keywords: Weibull Statistics, Scale parameter, Shape parameter,Failure rate, Reliability function, Weibull cumulative distribution function.

Article published in International Journal of Current  Engineering  and Technology, Vol.3,No.1 (March- 2013)