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A listing in reverse chronological order of articles by:
Dear friends, we are happy to release this video on fractional factorial design. In this video, Hemant Urdhwareshe has illustrated how to create a five-factor resolution-V design in Minitab (version 17) with an example of a virtual catapult (thanks to sigmazone.com)
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Hello Friends! I am happy to release this video on Kaplan-Meier (KM) nonparametric method to estimate reliability. The KM method is used in situations when the data cannot be modelled using mathematical distributions such as Weibull, Lognormal etc. The KM method is popularly used in medical science to estimate survival probabilities of patients with diseases such as cancer, kidney diseases, etc.
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Dear friends, This is Hemant Urdhwareshe! I am uploading this video, which is different from our other videos! In this video, I have explained the “Confusion Matrix” and related terms such as Sensitivity, Specificity, Accuracy with reference to RT-PCR Test to detect Covid-19 infection. I and my son were isolated for Covid-19 as I was detected Covid-19 positive before my return travel and then isolated for about a fortnight in Egypt! This video is a result of my experience and review of travel rules! I am sure you will find this interesting and thought-provoking!
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This article shows reductio ad absurdum in action. Yes you can achieve any MTBF you want, by mixing products with Weibull life distributions, but you won’t want the consequences. The article also shows the absurdity of specifying MTBF, alone.
[Read more…]Institute of Quality and Reliability is happy to release this video on Power and Sample Size in the context of hypothesis testing. The video also contains application examples of power and sample size calculation for one-sample z-test using Minitab software.
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H.L. Mencken, the sharp-witted satirist and critic of early 20th-century American life, once wrote, “For every complex problem, there is an answer that is clear, simple, and wrong.”1 Mencken, born in Baltimore in 1880, was known for his incisive critiques of societal norms and his skepticism of simplistic solutions to complex issues.
Mencken’s wisdom applies to both everyday life and technical fields. His insights are particularly relevant in the engineering, manufacturing, and reliability disciplines, where the temptation to seek easy answers can lead to costly errors. We’ll start with a relatable everyday example before exploring documented cases in engineering and manufacturing that demonstrate the pitfalls of oversimplified solutions.
[Read more…]Dear friends, We are happy to release this third video in our series on Confidence Intervals! In this video, Hemant Urdhwareshe has explained how to determine confidence intervals for population proportion and standard deviation with day-today application examples! Hemant has also illustrated use of templates for quick calculation!
Links to other related videos:
Confidence Interval (Part-1) for Mean (Sigma Known)
Confidence Interval (Part-2) for Mean (Sigma unknown)
Chi-square Test of One Variance
Dear friends, we are happy to release this Part-2 of our videos on Confidence Intervals. In this video, Hemant Urdhwareshe explains how to estimate confidence interval of population mean when population standard deviation sigma is not known In such cases, we need to use Student’s t-distribution instead of normal distribution and Z-Score.
[Read more…]Dear friends, we are happy to release this video on confidence interval when population standard deviation is known. This is part-1 of our series on confidence intervals.
[Read more…]Dear friends, we are glad to release this interesting video. In this video, Hemant Urdhwareshe explains procedure for probability plotting of failure data in Exponential Distribution using Excel. Hemant is a Fellow of ASQ and is certified as CRE, Six Sigma Master Black Belt, CQE and CMQ/OE by ASQ.
[Read more…]Good fortune is what happens when opportunity meets with planning Thomas Edison
In this article, I will outline how to evaluate an FMEA Plan against the FMEA Quality Objective for FMEA Plans.
One of the most persistent points of confusion in quality engineering is the difference between traditional statistical process capability analysis and the Six Sigma approach. Specifically, why does Six Sigma define a “six sigma” process as having 3.4 defective parts per million (DPPM), when a straightforward application of statistical tables suggests that six standard deviations from the mean should correspond to a far lower defect rate—about 2 parts per billion? The answer lies in what Six Sigma practitioners call the 1.5 sigma shift.
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Dear friends, I am happy to release our 59th video on Exponential Distribution! Exponential Distribution is an appropriate mathematical model when failure or hazard rate is constant. It is often known as “Memoryless” as reliability in any time interval is same! Exponential Distribution has many applications in Reliability Engineering such as electronic components. Many reliability procedures in MIL Standards assume constant failure rate and Exponential Distribution! Hope you find the video interesting and useful! Your feedback is welcome! Do subscribe to our channel to get updates on our new videos and programs!
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Dear All, This is our fourth video on Accelerated Life Testing (ALT). Some of the viewers had requested for procedure to determine the Activation Energy used in Arrhenius Model. This video explains experimental procedure to determine Activation Energy. Hope you find this useful! If you like the video, click on the “Thumbs-up icon” and subscribe to our channel for more videos on Quality and Reliability!
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How to distinguish a renewal process from a “generalized” renewal process? Compare observed monthly returns vs. actuarial returns forecasts using actuarial return rate estimates of TTFF and TBF (Time To First Failure and Time Between Failures). A geophysicist masquerading as an Apple reliability engineer said, “It’s too hard to figure out the probability that a return came from a computer made in an earlier year.” It’s harder if returns could be second, third, or???
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