Across industries and disciplines, one challenge remains constant: how to prioritize the right improvement projects to drive meaningful, measurable progress. Whether you work in continuous improvement, reliability, quality, or manufacturing engineering, you have more ideas and opportunities than time or resources to pursue them. This is where the Theory of Constraints (TOC) shines. Developed by Dr. Eliyahu Goldratt, TOC offers a focused methodology for identifying the best opportunities for improvement, allocating resources wisely, and sustaining continuous advancement.

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by Hemant Urdhwareshe Leave a Comment

SPC-1: Statistical Process Control Chart Selection, and Application Example on Excel

Dear friends, Institute of Quality and Reliability (IQR) is happy to release this first video in our series on statistical process control charts. In the video, Hemant Urdhwareshe, Director of IQR and Fellow of ASQ explains criteria for selection of control charts, and has illustrated how to plot X-bar and Range chart using Microsoft Excel with an application example. Hemant has also explained briefly the interpretation rules to detect special causes. The video is little long but request viewers to watch it till end for best viewing experience.

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Fractional Factorial Design with Center Point: Design and Analysis

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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by Larry George 1 Comment

Reliability Estimation Efficiency? Without Lifetime Data?

What is the efficiency of your reliability estimators and failure forecasts? Compare naïve forecasts: guess, AFR, MTBF, or times series extrapolations such as ARIMA, GMDH, and AI, vs. forecasts based on reliability estimators. With grouped lifetime data, the Kaplan-Meier estimator is statistically efficient, under a condition often ignored! With lifetime data you could use maximum likelihood estimators like Weibull or Kaplan-Meier from (a sample of?) grouped lifetimes. Without lifetime data you could estimate reliability from population ships and returns counts from data required by GAAP! This article compares efficiency and cost of forecasts based on alternative data and estimators.

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by Hemant Urdhwareshe 1 Comment

Reliability Estimation with Kaplan-Meier Nonparametric Method

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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Covid-19 RT-PCR Test, Confusion Matrix and International Travel

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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by Carl S. Carlson Leave a Comment

FMEA Quality Objective 2: SCOPE

“If you don’t know where you are going, you’ll end up someplace else.” – Yogi Berra

As summarized in the first article in this series, “New Series – The Quality of FMEAs,” each month, I will write an article focusing on one of the 14 FMEA Quality Objectives. The intent is to provide insights and application tips for evaluating how well an FMEA meets the quality objectives. By learning to apply FMEA quality objectives, you can help to ensure that product designs and manufacturing processes are safe and reliable. If you didn’t read the introductory article, now is a good time to read it, since it explains FMEA Quality Objectives, and how they are used to create high-quality FMEAs.

In this article, I will outline how to evaluate an individual FMEA against the FMEA Quality Objective for Scope. [Read more…]

by Larry George Leave a Comment

What MTBF Do You Want?

Originally published in the ASQC Reliability Review, Vol. 15, No. 3, Sept. 1995

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.

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by Hemant Urdhwareshe Leave a Comment

Sample Size and Power In Hypothesis Testing

Concepts and Application with Minitab Software

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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by Ray Harkins Leave a Comment

The Answer That’s Clear, Simple, and Wrong

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.

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by Hemant Urdhwareshe Leave a Comment

Confidence Intervals (Part 3) for Proportion and Standard Deviation

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 Distribution

Chi-square Test of One Variance

by Hemant Urdhwareshe Leave a Comment

Confidence Intervals for Mean ( part-2:) : Using t-distribution

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.

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by Hemant Urdhwareshe Leave a Comment

Confidence Interval of Population Mean (Part-1)

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.

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by Hemant Urdhwareshe Leave a Comment

Exponential Probability Plotting on Excel

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.

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by Carl S. Carlson Leave a Comment