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Acceptance Sampling Plans for Quality Control (Part-1)

Acceptance Sampling Plans for Quality Control (Part-1)

Dear friends, I am happy to share our first video on Quality Control Acceptance Sampling Plans! In this video, I have explained some basic concepts and terminology of sampling plans. I have also illustrated use of Microsoft Excel to construct Operating Characteristic Curve and AOQ Curve of a sampling plan It is not possible to inspect 100% parts received from suppliers. Obviously, processes need to be capable to produce consistently good quality parts that conform to the specifications. However, there are quite a few processes where the capabilities are either marginal or low. Also, controls at suppliers may not be adequate due to many reasons. Therefore there is still a need for statistical Acceptance Sampling Plans.

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SPC Q&A Part 3

SPC Q&A Part 3

Favorite Questions and Answers from my Course “Statistical Process Control (SPC) Using Microsoft Excel”, Pt 3

In this third and final installment in this series, I continue my review of questions I’ve received from students of my online course titled, “Statistical Process Control (SPC) Using Microsoft Excel.

The length of the course is just under 11 hours, and covers a wide range of topics under four major chapters: Pareto Analysis, Control Charting, Process Capability Analysis, and Linear Regression. In it, I draw numerous case studies and examples from my career in quality management and manufacturing engineering. These real-life examples, I believe, are what spark the most questions. As the statistical approaches are placed in the context of plausible scenarios – scenarios the students routinely see themselves – the content takes a better grip and leads the student toward a greater desire to learn.

So please enjoy this last set of questions. Maybe they will inspire you as well.

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Key Teaching Principle # 11: Prepare, Prepare, Prepare!

As covered in the first article in this series, Principles of Effective Teaching, reliability engineers, FMEA team leaders, and other quality and reliability professionals are often called upon to teach the principles of reliability or FMEA. Whether you are a student who wants to enhance your learning experience, an instructor who wants to improve teaching results, or an engineer who wishes to convey knowledge to another person, this series will offer practical knowledge and advice.

“Success depends upon previous preparation, and without such preparation there is sure to be failure.”   Confucius

Like any task in life, it is essential that instructors prepare well for each course being taught.

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Reliability Analysis of life data with Multiple Failure Modes

Reliability Analysis of life data with Multiple Failure Modes

Dear friends, I am happy to release this video on reliability analysis of life data with multiple failure modes. The analysis procedure is illustrated fully in Minitab software with a real-life case study with six failure modes. The concept is that when a system fails for one failure mode at time t, this data of time is right censored data for other failure modes! Analysis in Minitab can be performed in one single command!

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Fred’s Bicycles and Kaplan-Meier Error?

Fred’s Bicycles and Kaplan-Meier Error?

The Kaplan-Meier reliability estimator errs on Fred’s bicycle ships and failure data! The Kaplan-Meier estimate was computed from Fred’s bicycles’ grouped failure data in the body of a “Nevada” table. It disagrees with the reliability estimate from ships cohorts and monthly failures (without knowing which cohort the failures came from). It disagrees with least squares nonparametric reliability estimates. All but the Kaplan-Meier estimate agree! Which would you prefer?

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SPC Q&A part 2

SPC Q&A part 2

Favorite Questions and Answers from my Course “Statistical Process Control (SPC) Using Microsoft Excel”, Pt 2

In this second installment of my three-part article series, I am again showcasing some of my favorite student questions from the past seven years since first launching my online class titled “Statistical Process Control (SPC) Using Microsoft Excel.”

Each exchange represents not only the question in that student’s mind, but the type of question that lingers the minds of countless professionals trying to advance their skillsets. Each exchange – some of which I edited for clarity – become a permanent part of the class itself that future students can read and learn from. Perhaps you’ve had some of these questions as well.

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Competing Risks in Failure Time Data

Competing Risks in Failure Time Data
Part of the Statistical Methods for Failure-Time Data article series.

Introduction

In my previous article, I briefly discussed the survival function and the Kaplan Meier method of estimating this function from a given dataset. We applied this method to a vehicle shock absorber dataset to answer questions like “What is the probability that a vehicle shock absorber will last at least 19,000 km?”. The two different modes of failure of a shock absorber (Mode 1 and Mode 2) were ignored and were treated as the same type of failure. In the following post, we will consider the two modes of failures as two competing risks and answer questions like:

“What is the probability that a vehicle shock absorber will experience a Mode 1 failure by 19,000 km and that this failure occurs before it experiences a Mode 2 failure?” [Read more…]

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SPC Q&A Part 1

SPC Q&A Part 1

Favorite Questions and Answers from my Course “Statistical Process Control (SPC) Using Microsoft Excel”, Pt 1

Teaching manufacturing-related skills online offers a host of intangible benefits such as:

  • Interacting with professionals around the world,
  • Helping learners take the next step in their careers,
  • Witnessing the “a ha” moments of the learners taking my classes, and
  • Sharing the knowledge I’ve accumulated (and continue to accumulate) in my career.

And in one specific piece of the teaching process, I can experience all four benefits simultaneously, that is, answering student questions.

In this first article of a three-part series, I will share with you some of my favorite questions and answers from “Statistical Process Control (SPC) Using Microsoft Excel”, a course 7,800+ students from 126 countries have taken over the past since I launched it nearly 7 years ago.

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Key Teaching Principle # 10: Application

As covered in the first article in this series, Principles of Effective Teaching, reliability engineers, FMEA team leaders, and other quality and reliability professionals are often called upon to teach the principles of reliability or FMEA. Whether you are a student who wants to enhance your learning experience, an instructor who wants to improve teaching results, or an engineer who wishes to convey knowledge to another person, this series will offer practical knowledge and advice.

I have been impressed with the urgency of doing. Knowing is not enough; we must apply. Being willing is not enough; we must do.  Leonardo da Vinci

Key Teaching Principle # 10 compels the instructor to ensure that each and every student learns how to apply the material being taught, in a variety of realistic scenarios. [Read more…]

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Fractional Factorial Design in Minitab

Fractional Factorial Design in Minitab

Dear friends, this video illustrates how to create and analyze a fractional factorial design using Minitab software with an application example. You can watch our other video on basic concepts in Fractional Factorial Designs: DOE-5: Fractional Factorial Designs, Confounding and Resolution Codes. You can watch all our videos on DOE by clicking here to see the playlist:  DOE-2: Application of Design of Experiments. We hope you are finding our videos useful!

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Design of Experiments: Terms and Definitions

Design of Experiments: Terms and Definitions

Dear friends, many of you have requested for more videos about Design of Experiments. In this video, Hemant Urdhwareshe explains basic terms and definitions in DOE. These include OFAT vs DOE, Types of Factors, Levels, treatments, steps in DOE, nuisance or noise factors, blocking, randomization, covariates, etc. Hope you find this video useful to understand these basic concepts.

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Kaplan-Meier Ignores Cohort Variability!

Kaplan-Meier Ignores Cohort Variability!

The Kaplan-Meier reliability estimator is the nonparametric, maximum likelihood estimator from right-censored, grouped lifetime data. It has been used since publication, most statistics programs do it, and it has been taught since I was in school. I give away a spreadsheet version. 

Lifetime data requires tracking individual subjects or units from their start to failure, death, or censoring. Data may be collected periodically grouped by cohorts: monthly sales, ships, or other collections of individuals, subjects, or units and each cohort’s lifetimes. Data could be displayed in a “Nevada” table with random cohorts in one column, and each cohort’s lifetimes grouped in periodic age-at-failure intervals in columns to the right [Schenkelberg].

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