Optimum Sigma is NOT 6

By Kermit Taylor

Designing to the Optimum Sigma can enable companies to profit from a lot of money that current operations waste. Optimum Sigma is NOT 6 is the first book that guides engineers and managers through the process of setting design specifications to meet assembly requirements and minimize overall cost. The methodology shows how to decrease defects without significant increases in product costs, thereby increasing profitability and production capacity. The defect-costs relationship was described in very generic terms in earlier statistical process control books. Those books focused on manufacturing process improvements while assuming that design specifications would be appropriate and correct. The book shows why legacy approaches have failed and the cause and effect relationships between factory rework, part variability, design specifications, and overall production costs. Instructions are provided in how to produce a design that will optimize costs and factory flow, assure customer satisfaction, improve profitability, enhance workforce morale, and be environmentally efficient through proper specifications. Downloadable files for customer application are available through the book’s website.
According to the most recent published data from the National Association of Manufacturers and Industry Week, manufactured goods contributed 2.18 trillion dollars to the economy of the United States in 2016. Applying Industry Week’s average defect rate of 2.7%, that figure includes at least $58 billion wasted to defective goods. Given that it typically costs ten times as much to fix a defective assembly as it does to produce a defect free unit, the real scrap and rework numbers grow to between fifteen and forty percent of most manufacturers operating costs. The methodology described in Optimum Sigma is NOT 6 targets eliminating at least eighty percent of that rework, the rate generally attributable to engineering errors.

• Language: English
• Publisher: Kermit Taylor
• Release date: Jun 10, 2021
• ISBN: 9781005461690

Kermit Taylor

Kermit Taylor has over thirty-four years’ experience adding value through quality mobile equipment designs in both the automotive and aerospace industries. Through twenty years of using his tolerance analysis method and as KC-46A program focal for tolerance analysis, he enabled engineering that product development groups otherwise would not have attempted, saving millions of dollars and improving factory flow. Through skillful analysis, he has provided design and process improvements that have stood the test of time and production, often unchanged for thousands of production assemblies. He has coached lean manufacturing workshops, led Six Sigma Black Belts, managed engineering and product test groups, and conducted operations research. He combined his bachelors’ degree in mechanical engineering with Theory of Constraints studies and an MBA to attain perspective and insight for optimizing the product and overall production system while maintaining the ability to focus on the details that can derail it. Semi-retired in 2017, he is now utilizing his time sharing these tolerance analysis techniques with industry via this book and consultation.

Book preview

Optimum Sigma is NOT 6

How to Design for Flow and Maximum Profits

by

Kermit Taylor

Smashwords Edition

Published on Smashwords by:

Kermit Taylor

Optimum Sigma is NOT 6

Copyright 2021 by Kermit Taylor

All rights reserved. Without limiting the rights under copyright reserved above, no part of this publication may be reproduced, stored in or introduced into a retrieval system, or transmitted, in any form, or by any means (electronic, mechanical, photocopying, recording, or otherwise) without the prior written permission of both the copyright owner and the above publisher of this book.

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CONTENTS

Chapter One: Why I Wrote This Book

Chapter Two: The Quest for Quality

Chapter Three: Operational Impacts

How the Costs Grow and Effects on Throughput and Flow

Management Focus on Production as the Means to Solution

Chapter Four: Initiatives That Do Not Address the Root Cause Cannot Reach the Solution

Innovation is Key, Right?

Why the Answer Is Not Six Sigma

Doesn’t 3D Modeling Solve the Problem?

What About Lean?

Chapter Five: Finding Your Optimum Sigma

Chapter Six: Fixing Current Production

Chapter Seven: Design Process—New Products

Chapter Eight: Structural Calculation Methods

Determinate Assembly—hole-to-hole

The Analysis Steps

Tolerance Loop Comparison: Baseline Dimensioning Vs. Composite Feature Control Frame

Wire, Tubing and Hose Length Methods

Chapter Nine: Caveats, Concerns, and Assumptions

Chapter Ten: Business Plan Impacts—What’s In It For Me?

Glossary of Terms and Acronyms

About the Author

References and Recommended Reading

To get the bad customs of a country changed and new ones, though better, introduced, it is necessary to first remove the prejudices of the people, enlighten their ignorance, and convince them that their interests will be promoted by the proposed changes, and this is not the work of a day.

—Benjamin Franklin (1781)

Chapter One:

Why I Wrote This Book

What prompts an introverted retired engineer to take on the extra-curricular activity of writing a book? The answer isn’t just passing along lessons learned from thirty plus years of designing assemblies for mobile equipment. The compulsion started roughly twenty years ago with an assignment to fix a truck door assembly relative to its surrounding frame. After six months of production, the company was experiencing major rework expenses on the doors. Management wanted a solution—probably expecting me to whip the vendor into better compliance. Supported by eight Six Sigma Black Belts and my personal spreadsheet, we examined the assemblies through three factories and all phases of production. Finding that the door assembly could not be predictably built to specifications by any known process was bad, but the accuracy with which rework rates were predictable by the spreadsheet was personally astounding.

Although it had been a couple of years since I had received the spreadsheet, it included factors that I had never seen in a variability analysis (a variable multiplier, a requirements comparison, and a mean shift percentage), and I wasn’t confident in it. My status was that of having basic knowledge how to calculate assembly variability and statistically assess the risk probability of having to perform rework, but I had not verified the spreadsheet predictive accuracy nor dealt with the magnitude of variability costs. That project was the transformational change that affected my viewpoint on engineering quality. My definition of quality grew from manufacturing parts per specifications to parts and assemblies meeting all customer requirements (including design influences). Those requirements may be from the end user, a regulatory agency, or a mechanic trying to put the assembly together and are usually unique to that assembly or individual relationships within the assembly. If any of those criteria is not met, the product becomes defective, causing rework, customization, trims or shims, or scrap. Large volumes of statistical theory describe formulas on variability, but they are nearly worthless to engineers who seldom have time to access or apply them without a pre-prepared software application, virtually all of which also require extensive training and set up. Most engineers aren’t so interested in learning theory as they are in having an effective way to get things done. I saw a need for a different approach to determining design specifications and the cost of quality—a methodology that engineers can use to get a nearly instantaneous projection of the design to manufacturing costs. Consequently, this book avoids in-depth statistical theories and is all about application of statistical attributes to get quality results.

This book is primarily for managers and engineers although many quality assurance workers will appreciate its contents. If you are a manager, you probably have a product or factory that requires too much rework. If rework levels seem to be under control, your concerns have turned toward product costs and schedule. Engineers, you are responsible for designing products and want to do it well without making production too expensive. For both of you, this book holds your keys to success. It really doesn’t matter what you produce or design, rigid structures like skyscrapers, flexible cables or hose assemblies, product packaging for sales display or shipment, tiny parts for computers or big pieces for ships or airplanes—all assemblies have parts, and every part has variability. The key is to make each part’s variability meet the assembly’s requirements as viewed by the customers.

The principles illustrated herein generally have not been found in academia and seldom practiced to this extent in business. In the rare circumstance where anything similar to this book is taught, the class is usually in a Math and Statistics Department with no requirement or emphasis in the engineering colleges. In my own bachelor’s program, I recall about one hour of class learning the Square Root Sum of Squares formula, with no discussion of cost, factory impacts, or application value. Your application of these principles can distinguish your efforts and mark you as a highly valued member of your company. Strengths and shortcomings of common business practices such as Six Sigma, Lean Manufacturing, and Theory of Constraints (TOC) are woven into the text to show how successful application of those programs often depends on the materials and practices espoused herein.

First, although I am critical of Six Sigma and many common quality improvement programs, let me assure you that I am not an opponent of quality and delivering customer satisfaction! You won’t have a business without them. However, it is also true that you won’t have a business without profit, and that is my principal concern. The efforts in Detroit adequately demonstrated that, alone, Six Sigma was not the panacea to solve all company ills and return the Big 3 automotive companies to a dominant competitive position in the marketplace. Instead, they all were virtually or actually bankrupt in 2009. What I demonstrate in this book will convince you that blindly mandating adherence to that standard actually contributed to their collapse. Without the methods in this book, those programs do not have the capability to solve the root cause of most quality problems.

Second, I do not advocate elimination of any quality programs, just that those programs need to be adjusted and managed differently. Because the metrics of most first pass quality programs do not address the root causes of defects, factory results do not correlate with measurements from those programs. This too will be explained with lessons on how to evaluate conditions, decision steps to follow, and results forecast analyses. Albert Einstein is credited with saying Insanity: doing the same thing over and over again and expecting different results and "The significant problems we face cannot be solved at the same level of thinking