Your Reliability Engineering Professional Development Site
Understanding the different types of data and thier respective uses is critical for product delveopment testing and analysis.
Each type of eo f data plays a a role in ensuring that products meet quality standards and fulfill user needs.
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Accelerated Life Testing (ALT) on subcomponents and durability testing for whole products are two strategies used to assess the reliability of products. ALT involves subjecting a product to conditions beyond its normal service parameters to uncover faults and potential failure modes in a short time, allowing engineers to make predictions about its service life and maintenance intervals. On the other hand, durability testing for whole products involves testing the entire product under normal operating conditions to assess its long-term reliability and performance.
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Using highly accelerated stress screening to identify supplier defects before the product is shipped saves time and money.
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The history of Design of Experiments (DOE) can be traced back to the work of various individuals, including Genichi Taguchi, a Japanese engineer and statistician. Taguchi made significant contributions to the field, particularly in the area of robust design, which aimed to improve the quality of products and processes. His work was influenced by the need for quality improvement in post-World War II Japan. Taguchi’s methodology, known as the Taguchi methods, was based on the concept of “robust parameter design,” which aimed to make processes and products insensitive to environmental factors or other variables that were difficult to control.
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Designing a proper test for the life of an electromechanical compoent involves several steps and considerations. Here are six steps that provides an outline to create a meaningful component life test.
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Accelerated life testing (ALT) is a method used to enhance product reliability by subjecting prototypes to stress levels significantly higher than those encountered in actual use.
By increasing the stress on the component, failure is induced more rapidly, which is equivalent to speeding up the passage of time. This approach is particularly useful when waiting for failures to occur at their normal rate is not feasible, such as when a manufacturer needs to release a product to the market soon and cannot afford to spend several years performing a reliability test.
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A short video defining accelerated life testing or ALT.
An introduction to ALT or accelerated life testing. ALT is a method used to enhance product reliability by subjecting prototypes to stress levels significantly higher than those encountered in actual use. In short, it’s a way to accelerate time.
[Read more…]Some history:
The executives of the Powertrain Organization (transmissions, chassis, engines) wanted a methodology where teams (design engineering, manufacturing engineering, and production) could work on recurring chronic problems. In 1986, the assignment was given to develop a manual and a subsequent course that would achieve a new approach to solving identified engineering design and manufacturing problems.
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A short video discussing the importance to engineering test data analysis of confidence intervals.
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Probably every engineer has heard once in his experience terms FMEA and RCA.
What is FMEA?
FMEA is a systematic method for identifying and preventing potential failure modes in a product or process. It helps in proactively addressing failure risks, improving reliability, and enhancing safety. FMEA is crucial in various industries, including automotive, aerospace, and manufacturing, to ensure product quality and customer satisfaction.
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Well, this article will be a little bit challenging and full of statistical terms. I would categorize the “Hypothesis testing” as most of common use in statistical analysis.
First time of usage happened in 1700s, but actual popularisation at early 20th century:
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Background:
A histogram – is an approximate representation of the distribution of numerical data. The term was first introduced by Karl Pearson:
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A brief introduction to the statistical hypothesis test called the t-test. Useful when examining if there is a difference between the means of two groups.
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Why is confidence level so important in engineering test data analysis?
From the name itself it gives us a very good hint; Confidence level is giving the confidence in data analysis. In the next graph, you can find 10 samples and fitted Weibull 2p distribution with 95% of Confidence level:
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