Institute of Quality & Reliability

Dear friends, we are happy to upload this video on how to estimate B10 life when failure data follows Weibull or Lognormal Distribution. Your feedback on the video is welcome!

This video from the Institute of Quality and Reliability explains how to determine BX life for products that follow Weibull and log-normal distributions. BX life is defined as the time by which X percent of items are expected to fail. For example, B10 life means that 10% of items are expected to fail, which implies a 90% reliability.

We recommend watching following videos before watching this video for better learning experience:

Weibull Distribution Part-1

B10 Life for Exponential Distribution

Normal Distribution and Z-Score

Lognormal Distribution

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This video from the Institute of Quality and Reliability explains how to calculate the B10 life (the time by which 10% of items are expected to fail) for an exponential distribution.

We suggest to view our video on Exponential Distribution for better learning experience. Here is the link to the video:  Remember this Memoryless Exponential Distribution . Your feedback is welcome!

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Dear All, in this video Hemant Urdhwareshe explains the Miner’s Rule for cumulative damage under cyclic loading along with an application example. Your feedback is welcome! Hemant is a Fellow of ASQ, and certified by ASQ as Six Sigma Master Black Belt, CRE, CQE and CMQ/OE.

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Dear Friends, We are happy to share this second video on Response Surface Design. In this video, Hemant Urdhwareshe, Fellow of ASQ and Six Sigma Master Black Belt explains the structure of Response Surface Design with focus on Central Composite Design (CCD). Hemant has taken lot of efforts to illustrate this little complex concept with lot of graphics and animations so that viewers can understand it clearly and quickly. Hemant has also illustrated how to create, analyse and interpret results of Central Composite Design on Minitab with a virtual catapult.

We recommend that viewers should watch our previous videos:

(1) RSM Part-1

(2) Fractional Factorial Designs and Resolution Code

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Dear friends, I am posting a video after some gap! This is our first video in our series on Response Surface Designs. Response Surface Designs become necessary when we want to model a second order response in an experiment. In this first video, Hemant Urdhwareshe explains addition of centerpoint to a factorial design to assess presence of non-linearity in the response. The concept is explained with a virtual catapult with a two-factor two-level design.

Links to the related videos:

(1) DOE-1: Introduction to Design of Experiments

(2) DOE-8: Linearity and Orthogonality in Experimental Design

(3) DOE-6: Case Study in Creating Full Factorial Design in Minitab

(4) DOE-7: Analyse Factorial Design with Minitab

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Dear friends, we are happy to release this second video on statistical process control charts. In this video, Hemant Urdhwareshe illustrates how to use attributes charts, specifically p-charts for proportion defective and np charts for number defective! Watch our video SPC-1 for Introduction and Selection of Control Charts, and X-bar and R charts.

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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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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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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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