Weibull Analysis and Zero-time Failures with ReliaSoft Weibull++
Life data analysts often face the challenge of zero-time failures, which are defined as failures occurring before a product is in the hands of the end customer or out-of-box failures. Processing zero-time failure data can be a complex process since most statistical distributions and analysis software packages do not handle such data well. The analyst must thoroughly understand the appropriateness and implications of including zero-time failures when analyzing life data. Incorrect usage can result in inaccurate forecast results and potentially negative engineering and financial consequences. Simply plugging numbers into a software program will not always result in satisfactory results if the background engineering analysis is not performed as well. The analyst must determine if the zero-time failure data should be used as presented, transformed according to known field exposure correlations or ignored all together.
Life data analysts often face the challenge of zero-time failures, which are defined as failures occurring before a product is in the hands of the end customer or out-of-box failures. Processing zero-time failure data can be a complex process since most statistical distributions and analysis software packages do not handle such data well. The analyst must thoroughly understand the appropriateness and implications of including zero-time failures when analyzing life data. Incorrect usage can result in inaccurate forecast results and potentially negative engineering and financial consequences. Simply plugging numbers into a software program will not always result in satisfactory results if the background engineering analysis is not performed as well. The analyst must determine if the zero-time failure data should be used as presented, transformed according to known field exposure correlations or ignored all together.
- Processing zero-time failures in life data analysis can be a challenging task with much uncertainty.
- There is no established method of how and when to include time-zero data for life analysis.
- Predict reliability by understanding the failure modes, their root causes, relevance to the field and other accompanying factors, such as manufacturing. Tests, stress screening, and accumulated time of the degradation, among others.
- Improve reliability predictions by incorporating zero-time-to-failure data.
- Quickly assess different approaches for handling zero-time data.
- Easily manipulate data and display multiple scenarios for results comparison.