Application Examples for Weibull++

Weibull++ for life data analysis
Update

Latest Release
10.1.6 ♦ 24-Oct-2016

 

Purchase Options

Single-user and floating licenses. Multi-product suites and token-based licenses are also available.           [Learn More...]

ReliaSoft's Weibull++ life data analysis software provides an extensive array of tools to help you understand and communicate how a product will perform over time. Some of the many useful applications include the ability to:

These examples demonstrate some of the types of analyses you can perform with this application. For additional product documentation, including the Quick Start Guide, visit the Synthesis eDocs & ePubs Library.

Examples Using Standard Folios

Example 1:

Complete and Right Censored Data Analysis

Ten identical units are reliability tested at the same application and operation stress levels for 120 hours. The objective is to use the complete and right censored data from the test to determine the unreliability for a mission duration of 226 hours and the warranty time for a reliability of 85%.

Example 2:

Analyzing Complete Data

Six units are tested to failure. The objective is to use the complete data from the test to obtain a probability plot with 90% 2-sided confidence bounds and a pdf plot.

Example 3:

Analyzing Sudden Death Data

A manufacturer uses data from a sudden death test to demonstrate the reliability for a product with a 70% lower one-sided confidence level. Four groups of 5 units each are tested sequentially until the first failure in each group.

Examples Using Specialized Folios

Example 4:

Degradation Analysis Example

Five turbine blades were tested for crack propagation. The test units were cyclically stressed and inspected every 100,000 cycles for crack length. Failure is defined as a crack of length 30 mm or greater.

Example 5:

Warranty Analysis

A company keeps track of its shipments and warranty returns on a month-by-month basis. Using the warranty analysis folio, determine the parameters for a 2-parameter Weibull distribution and predict the number of products from each of the three shipment periods that will be returned under warranty in October.

Example 6:

Factory Equipment Failure Log

A manufacturer is tracking the failures occurring in the product line. When a failure occurs in a machine, the time of occurrence and the time of repair are recorded for the machine and the parts that failed. Using Weibull++’s event log folio, determine the failure and repair distributions.

Example 7:

Non-Parametric Life Data Analysis

A group of 55 units are put on a life test during which the units are evaluated every 50 hours. Use the simple actuarial method to determine reliability estimates for each failure time.

Example 8:

Non-Parametric Recurrent Event Data Analysis for Transmission Repair

Repairs are tracked on automatic transmissions in a sample of 34 cars in a preproduction road test. The objective is to determine the mean cumulative number of repairs per car by 24,000 test miles (equivalently 5.5 x 24,000 = 132,000 customer miles).

Example 9:

Parametric Recurrent Event Data Analysis Example

The repairs made to a system are tracked over a period of time. Each repair is capable of addressing any damage accumulated up to the time of the current failure. The objective is to determine how effective the repairs are.

Further Examples

Example 10:

Competing Failure Modes Analysis

An electronic component has two failure modes. One failure mode is due to random voltage spikes, which cause failure by overloading the system. The other failure mode is due to wear-out failures, which usually happen only after the system has run for many cycles. Using competing failure modes analysis, the overall reliability for the component at 100,000 cycles is determined.

Example 11:

Failure Modes RBD Analysis

A particular component can fail due to six independent primary failure modes: A, B, C, D, E and F. The component fails if mode A, B or C occurs. If mode D, E or F occurs alone, the component does not fail; however, the component will fail if any two (or more) of these modes occur (i.e., D and E; D and F; E and F). The objective is to analyze each data set using the 2-parameter Weibull distribution with MLE and to determine the lower 1-sided 90% confidence interval on the reliability of this component at 100 hours.

Weibull++ Reliability Life Data Analysis ALTA Accelerated Life Testing Data Analysis DOE++ Experiment Design and Analysis RGA Reliability Growth and Repairable System Analysis BlockSim System Reliability and Maintainability Analysis RENO for Risk Analysis via Discrete Event Simulation Lambda Predict Reliability Prediction Xfmea FMEA and FMECA RCM++ Reliability Centered Maintenance MPC MSG-3 Maintenance Program Creation XFRACAS Web-based FRACAS Orion eAPI Web-based Asset Management ALTA Accelerated Life Testing Data Analysis BlockSim System Reliability and Maintainability Analysis DOE++ Experiment Design and Analysis MPC MSG-3 Maintenance Program Creation Lambda Predict Reliability Prediction RCM++ Reliability Centered Maintenance RENO for Risk Analysis via Discrete Event Simulation RGA Reliability Growth and Repairable System Analysis Weibull++ Reliability Life Data Analysis Xfmea FMEA and FMECA XFRACAS Web-based FRACAS Orion eAPI Web-based Asset Management ALTA Accelerated Life Testing Data Analysis BlockSim System Reliability and Maintainability Analysis DOE++ Experiment Design and Analysis MPC MSG-3 Maintenance Program Creation Lambda Predict Reliability Prediction RCM++ Reliability Centered Maintenance RENO for Risk Analysis via Discrete Event Simulation RGA Reliability Growth and Repairable System Analysis Weibull++ Reliability Life Data Analysis Xfmea FMEA and FMECA XFRACAS Web-based FRACAS Orion eAPI Web-based Asset Management    ReliaSoft.com Footer

Copyright © 1992 - ReliaSoft Corporation. All Rights Reserved.
Privacy Statement | Terms of Use | Site Map | Contact | About Us

Like ReliaSoft on Facebook  Follow ReliaSoft on Twitter  Connect with ReliaSoft on LinkedIn  Follow ReliaSoft on Google+  Watch ReliaSoft videos on YouTube