Statistics Roundtable: Divide and Conquer in Reliability Analyses
All product is not created equal. Some units are more likely to fail in service than others. Thus, in reliability evaluations, you need to identify subpopulations with different failure susceptibility....
Statistics Roundtable: The Pros of Proactive Product Servicing
Just like athletes can experience an injury that takes them out of a game, systems can experience component failures that require downtime and repair....
Statistics Roundtable: Improving Reliability Through Warranty Data Analysis
Today's emphasis on proactive improvement calls for building high reliability into products at design. The goal is to avoid field failures during a product's estimated lifetime....
Statistics Roundtable: How to Analyze Reliability Data for Repairable Products
Leveraging powerful - yet simple - methods for reliability data analysis of repairable products or systems can help you stay on the right track....
Planning Reliability Assessment
Let’s say you have designed a new metal spring and want to estimate the time by which 10% of such springs will fail. How many units do you need to test and for how long?...
Planning life tests for reliability demonstration.
How many units do I need to test and for how long to demonstrate high reliability?? Engineers and managers ask statisticians this question all the time because they need information about reliability before making important decisions....
Planning Life Tests for Reliability Demonstration
How many units do I need to test and for how long to demonstrate high reliability? Engineers and managers ask statisticians this question all the time because they need information about reliability before making important decisions....
Speedier Reliability Analysis
Customers demand high reliability in new products. The fact that product development usually lasts no more than one year, from design to production, means that accelerated life tests (ALTs) are critical. ALTs are one element of a reliability assurance...
Reliability Analysis by Failure Mode
Reliability improvement should be a major consideration when conducting product life data analysis. One method of determining the failure mode responsible for failure is to perform separate analyses for each mode and combine the results, as opposed to...
Column: Frontiers of Quality: Statistical Tools for Six Sigma
What to emphasize and de-emphasize in training
These tools and closely related concepts, such as the design of experiments, are key elements of Six Sigma training and comprise up to half of the standard curriculum. The goal of standard Six Sigma statistical training is to give Green Belts and Black Be...
Column: Statistics Roundtable: Using degradation data for product liability analysis.
A case study shows how this type of data can provide more precise results in assessing reliability
High reliability systems require individual components to have extremely high reliability for a long time. Often, the time for product development is short, imposing severe constraints on reliability testing. Traditionally, methods for the analysis of...
Reliability Improvement Issues and Tools
Weibull distributions can also represent products with either a decreasing hazard rate ( less than 1) or increasing hazard rate ( greater than 1). When equals 1 the Q U A L I T Y P R O G R E S S I M A Y 1 9 9 9 I 135 Selling Reliability to Upper Manageme...
The Absolute Sample Size is What Counts
The author emphasizes and illustrates the important--and not always fully appreciated--point that the amount of information contained in a random sample depends upon the absolute size of that sample and not its size relative to that of the...
