The Certified Quality Inspector Handbook

By H. Fred Walker and Ahmad K. Elshennawy

The quality inspector is the person perhaps most closely involved with day-to-day activities intended to ensure that products and services meet customer expectations. The quality inspector is required to understand and apply a variety of tools and techniques as codified in the American Society for Quality (ASQ) Certified Quality Inspector (CQI) Body of Knowledge (BoK). The tools and techniques identified in the ASQ CQI BoK include technical math, metrology, inspection and test techniques, and quality assurance. Quality inspectors frequently work with the quality function of organizations in the various measurement and inspection laboratories, as well as on the shop floor supporting and interacting with quality engineers and production/service delivery personnel.

This handbook supports individuals preparing to perform, or those already performing, this type of work. It is intended to serve as a ready reference for quality inspectors and quality inspectors in training, as well as a comprehensive reference for those individuals preparing to take the ASQ CQI examination. Examples and problems used throughout the handbook are thoroughly explained, are algebra-based, and are drawn from real-world situations encountered in the quality profession.

To assist readers in using this book as a ready reference or as a study aid, the book has been organized to conform explicitly to the ASQ CQI BoK. Each chapter title, all major topical divisions within the chapters, and every main point has been titled and then numbered exactly as they appear in the CQI BoK.

• Language: English
• Publisher: ASQ Quality Press
• Release date: Mar 9, 2019
• ISBN: 9781951058746

Book preview

The Certified Quality Inspector Handbook

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To request a complimentary catalog of ASQ Quality Press publications, call 800-248-1946, or visit our website at http://www.asq.org/quality-press.

The Certified Quality Inspector Handbook

Third Edition

H. Fred Walker, Ahmad Elshennawy, Bhisham C. Gupta, and Mary McShane Vaughn

ASQ Quality Press

Milwaukee, Wisconsin

American Society for Quality, Quality Press, Milwaukee 53203

© 2019 by ASQ

All rights reserved. Published 2019

Library of Congress Cataloging-in-Publication Data

Names: Walker, H. Fred, 1963– author. | Elshennawy, Ahmad K., author. |

Gupta, Bhisham C., 1942– author. | McShane-Vaughn, Mary, 1963– author.

Title: The certified quality inspector handbook / H. Fred Walker, Ahmad K.

Elshennawy, Bhisham C. Gupta, Mary McShane Vaughn.

Description: Third edition. | Milwaukee, Wisconsin : ASQ Quality Press,

[2019] | Includes bibliographical references and index.

Identifiers: LCCN 2018058749 | ISBN 9780873899819 (hard cover : alk. paper)

Subjects: LCSH: Quality control—Handbooks, manuals, etc. | Quality control

inspectors—Certification—United States.

Classification: LCC TS156 .W3139 2019 | DDC 658.5/62—dc23

LC record available at https://lccn.loc.gov/2018058749

ISBN: 978-0-87389-981-9

No part of this book may be reproduced in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher.

Publisher: Seiche Sanders

Sr. Creative Services Specialist: Randy L. Benson

ASQ Mission: The American Society for Quality advances individual, organizational, and community excellence worldwide through learning, quality improvement, and knowledge exchange.

Attention Bookstores, Wholesalers, Schools, and Corporations: ASQ Quality Press books, video, audio, and software are available at quantity discounts with bulk purchases for business, educational, or instructional use. For information, please contact ASQ Quality Press at 800-248-1946, or write to ASQ Quality Press, P.O. Box 3005, Milwaukee, WI 53201-3005.

To place orders or to request ASQ membership information, call 800-248-1946. Visit our website at http://www.asq.org/quality-press.

In loving memory of my father, Carl Ellsworth Walker.—Fred

In loving memory of my parents, Mohammed Elshennawy and Ikram Ismail.—Ahmad

In loving memory of my parents, Roshan Lal and Sodhan Devi.—Bhisham

In loving memory of my father, Charles H. McShane.—Mary

List of Figures and Tables

Section I

Table 1.1 Properties of real numbers.

Figure 1.1 Example prime factorization tree.

Table 1.2 Place values for ABCDEFG.HIJKLM.

Table 1.3 Decimal and fraction equivalents.

Table 2.1 Additional properties of real numbers.

Table 2.2 Inverse operations.

Table 3.1 Calculation of area for basic geometric shapes.

Table 3.2 Calculation of perimeter and circumference of basic geometric shapes.

Table 3.3 Calculation of volume of basic geometric shapes.

Table 3.4 Calculation of surface area for basic geometric shapes.

Figure 4.1 The right triangle.

Table 4.1 Calculation of trigonometric functions.

Table 4.2 Values of trigonometric functions for common angles.

Figure 4.2 Finding angles in a right triangle.

Table 4.3 Oblique triangles.

Figure 4.3 Oblique triangle.

Figure 4.4 Three sides known.

Figure 4.5 Two sides and angle between known.

Figure 4.6 Two sides and opposite angle known.

Figure 4.7 One side and two angles known.

Table 5.1 Converting measures of length.

Table 5.2 Converting measures of area.

Table 5.3 Converting measures of volume.

Table 5.4 Converting measures of weight.

Table 5.5 Converting measures of liquid.

Table 5.6 Converting measures of pressure.

Table 5.7 Converting measures of length—metric units.

Table 5.8 Converting measures of area—metric units.

Table 5.9 Converting measures of volume—metric units.

Table 5.10 Converting measures of mass—metric units.

Table 5.11 Converting liquid measures—metric units.

Table 5.12 Converting measures of length—English and metric units.

Table 5.13 Converting measures of area—English and metric units.

Table 5.14 Converting measures of volume—English and metric units.

Table 5.15 Converting measures of weight and mass.

Table 5.16 Converting measures of liquid—English and metric units.

Table 5.17 Converting temperatures—Celsius to Fahrenheit.

Table 5.18 Converting temperatures—Fahrenheit to Celsius.

Table 5.19 Converting temperatures—English and metric units.

Table 6.1 Powers of 10.

Table 6.2 Common fractions and their decimal equivalents.

Figure 7.1 Fine-adjustment style vernier caliper.

Figure 7.2 LCD digital-reading caliper with 0–152 mm (0–6 in.) range.

Figure 7.3 Digital-reading, single-axis height gauge for two-dimensional measurements.

Figure 7.4 A 0–25 mm micrometer caliper.

Figure 7.5 Micrometer reading of 10.66 mm

Figure 7.6 Scales of a vernier micrometer showing a reading of 10.666 mm.

Figure 7.7 A digital micrometer.

Figure 7.8 An indicating micrometer.

Figure 7.9 A schematic showing the process of wringing gauge blocks.

Figure 7.10 CMM classifications.

Figure 7.11 Examples of typical gauges.

Figure 8.1 Elements of electronic gauges.

Figure 8.2 (a) Light-wave interference with an optical flat, (b) application of an optical flat, (c) diagram of an interferometer.

Figure 8.3 Diagram of air gauge principles.

Table 8.1 Summary of commonly used gauges and their applications.

Figure 10.1 Granite surface plate for checking the flatness of a part, with dial indicator and leveling screws.

Figure 10.2 Simple dial indicator mechanism.

Figure 10.3 An application of dial indicators for inspecting flatness by placing the workpiece on gauge blocks and checking full indicator movement (FIM).

Figure 10.4 Application of a sine bar.

Figure 10.5 Addition and subtraction of angle blocks.

Figure 11.1 (a) Typical surface highly magnified, (b) profile of surface roughness, (c) surface quality specifications.

Figure 11.2 (a) Skid-type or average surface finish measuring gauge, (b) skidless or profiling gauge.

Figure 11.3 Optical tooling.

Figure 11.4 Optical comparator system.

Figure 11.5 Horizontal optical comparator with a 356 mm (14 in.) viewing screen, digital readout, and edge-sensing device.

Figure 12.1 The calibration system.

Figure 12.2 Calibration standards hierarchy.

Figure 13.1 Components of total variation.

Figure 13.2 (a) Accurate and precise, (b) accurate but not precise, (c) not accurate but precise, (d) neither accurate nor precise.

Figure 13.3 Diagram showing the linear relationship between the actual and the observed values.

Table 13.1 Data on an experiment involving three operators, 10 bolts, and three measurements (in mm) on each bolt by each operator.

Figure 13.4 Two-way ANOVA table with interaction (Minitab printout).

Figure 13.5 Two-way ANOVA table without interaction (Minitab printout).

Figure 13.6 Gauge R&R (Minitab printout).

Figure 13.7 An example: percent tolerance contribution by the various components of the measurement system.

Figure 13.8 Percent contribution of variance components for the data in Example 13.1.

Figure 13.9 X and R chart for the data in Example 13.1.

Figure 13.10 Interaction between operators and parts for the data in Example 13.1.

Figure 13.11 Scatter plot for measurements versus operators.

Figure 13.12 Scatter plot for measurements versus parts (bolts).

Figure 14.1 Blueprint for a house floor plan.

Figure 14.2 Placement of the title block and notes on engineering drawings.

Figure 14.3 Example of title and notes blocks on an engineering drawing.

Figure 14.4 Example of a revision block.

Figure 14.5 Example of a technical engineering drawing with an indication of geometric tolerances.

Figure 14.6 Visual representation of the control frame of a hole.

Figure 14.7 Features that can be specified by geometric tolerancing.

Figure 14.8 Simple 2-D example of position tolerance.

Figure 14.9 Top, front, and right side views of an item.

Figure 14.10 Engineering drawing line types and styles.

Table 14.1 Other feature control symbols.

Figure 14.11 Example of symbols on an engineering drawing.

Figure 14.12 Form tolerance example.

Figure 15.1 An OC curve.

Figure 15.2 AOQ curve for N = ∞, n = 50, c = 3.

Figure 15.3 Switching rules for normal, tightened, and reduced inspection.

Figure 15.4 Structure and organization of ANSI/ASQ Z1.9-2008.

Figure 15.5 Decision areas for a sequential sampling plan.

Figure 16.1 Inspection decisions.

Figure 16.2 An example of a flowchart of a repair job.

Figure 16.3 Factors affecting the measuring process.

Table 16.1 Standards pertaining to MRB operations.

Figure 17.1 Visual inspection ensures consistency.

Figure 17.2 Inspection using X-ray.

Figure 17.3 Example of an inspection using X-ray.

Figure 17.4 Eddy current method.

Figure 17.5 The general inspection principle for ultrasonic testing.

Figure 17.6 Magnetic particle inspection.

Figure 17.7 Liquid penetrant testing steps.

Figure 17.8 Tensile test for a furnace.

Figure 17.9 Free-bend test.

Figure 17.10 Crash testing.

Figure 17.11 Tension test machine.

Figure 17.12 Torque can be calculated by multiplying the force applied to a lever by its distance from the lever’s fulcrum.

Figure 17.13 Compression test.

Figure 17.14 Brinell hardness test method.

Figure 17.15 Rockwell hardness test method.

Figure 17.16 The Vickers hardness test.

Table 19.1 Classification of annual revenues of 110 small to midsize companies located in the Midwestern region of the United States.

Table 19.2 Complete frequency distribution table for the 110 small to midsize companies.

Table 19.3 Complete frequency distribution table for the data in Example 19.2.

Table 19.4 Frequency table for the data on rod lengths.

Figure 19.1 Dot plot for the data on defective motors received in 20 different shipments.

Table 19.5 Understanding defect rates as a function of various process steps.

Figure 19.2 Pie chart for defects associated with manufacturing process steps.

Figure 19.3 Bar chart for annual revenues of a company over a five-year period.

Table 19.6 Frequency distribution table for the data in Example 19.7.

Figure 19.4 Bar graph for the data in Example 19.7.

Figure 19.5 Pareto chart for the data in Example 19.7.

Table 19.7 Frequencies and weighted frequencies when different types of defects are not equally important.

Figure 19.6 Pareto chart when weighted frequencies are used.

Table 19.8 Cholesterol levels and systolic blood pressures of 30 randomly selected US males.

Figure 19.7 Scatter plot of the data in Table 19.8.

Table 19.9 Frequency distribution table for the survival time of parts.

Figure 19.8 Frequency histogram for survival time of parts under extreme operating conditions.

Figure 19.9 Relative frequency histogram for survival time of parts under extreme operating conditions.

Figure 19.10 Frequency polygon for the data in Example 19.9.

Figure 19.11 Relative frequency polygon for the data in Example 19.9.

Figure 19.12 A typical frequency distribution curve.

Figure 19.13 Three types of frequency distribution curves.

Figure 19.14 Ordinary and ordered stem-and-leaf diagram for the data on survival time for parts under certain conditions.

Figure 19.15 Frequency distributions showing the shape and location of measures of central tendency.

Figure 19.16 Two frequency distribution curves with equal mean, median, and mode values.

Figure 19.17 Application of the empirical rule.

Figure 19.18 Amount of soft drink contained in a bottle.

Figure 19.19 Dollar value of units of bad production.

Figure 19.20 Percentile of salary data.

Figure 19.21 Quartiles and percentiles.

Figure 19.22 Box-and-whisker plot.

Figure 19.23 Box plot for the data in Example 19.25.

Figure 19.24 Box plot for the data shown in Example 19.26.

Figure 19.25 The normal probability function curve with mean µ and standard deviation σ .

Figure 19.26 Curves representing the normal density function with different means, but with the same standard deviation.

Figure 19.27 Curves representing the normal density function with different standard deviations, but with the same mean.

Figure 19.28 The standard normal density function curve.

Figure 19.29 Probability (a ≤ Z ≤ b) under the standard normal curve.

Table 19.10 A portion of the standard normal distribution table from Appendix D.

Figure 19.30 Shaded area equal to P(1.0 ≤ Z ≤ 2.0).

Figure 19.31 Two shaded areas in Figure 19.31 showing P(–1.5 ≤ Z ≤ 0) = P(0 ≤ Z ≤ 1.5).

Figure 19.32 Two shaded areas showing P(–2.2 ≤ Z ≤ –1.0) = P(1.0 ≤ Z ≤ 2.2).

Figure 19.33 Shaded area showing P(–1.5 ≤ Z ≤ 0.8) = P(–1.5 ≤ Z ≤ 0) + P(0 ≤ Z ≤ 0.8).

Figure 19.34 Shaded area showing P(Z ≤ 0.7).

Figure 19.35 Shaded area showing P(Z ≥ –1.0).

Figure 19.36 Shaded area showing P(Z ≥ 2.15).

Figure 19.37 Shaded area showing P(Z ≤ –2.15).

Figure 19.38 Converting normal N(6,4) to standard normal N(0,1).

Figure 19.39 Shaded area showing P(0.5 ≤ Z ≤ 2.0).

Figure 19.40 Shaded area showing P(–1.0 ≤ Z ≤ 1.0).

Figure 19.41 Shaded area showing P(–1.5 ≤ Z ≤ –0.5).

Figure 20.1 Flowchart of a process.

Table 20.1 Check sheet summarizing the data of a study over a period of four weeks.

Figure 20.2 Initial form of a cause-and-effect diagram.

Figure 20.3 A completed cause-and-effect diagram.

Figure 20.4 A damaged item shaped as a rectangular prism.

Table 20.2 Percentage of nonconforming units in 30 different shifts.

Figure 20.5 Run chart.

Figure 20.6 A pictorial representation of the components of a control chart.

Figure 20.7 OC curves for the X chart with 3-sigma limits, for different sample sizes n.

Table 20.3 Diameter measurements (mm) of ball bearings used in the wheels of heavy construction equipment.

Figure 20.8 X and R control chart for the ball bearing data in Table 20.3.

Figure 20.9 X and S control chart for the ball bearing data in Table 20.3.

Table 20.4 Control charts for attributes.

Table 20.5 Number of nonconforming computer chips out of 1000 inspected each day during the study period of 30 days.

Figure 20.10 p chart for nonconforming computer chips, using trial control limits for the data in Table 20.5.

Table 20.6 Number of nonconforming computer chips with different size samples inspected each day during the study period of 30 days.

Figure 20.11 p chart for nonconforming chips with variable sample sizes, using trial control limits for the data in Table 20.6.

Figure 20.12 np chart for nonconforming computer chips, using trial control limits for the data in Table 20.5.

Table 20.7 Total number of nonconformities in samples of five rolls of paper.

Figure 20.13 c control chart of nonconformities for the data in Table 20.7.

Table 20.8 Number of nonconformities on printed boards for laptops per sample; each sample consists of five inspection units.

Figure 20.14 u chart of nonconformities for the data in Table 20.8, constructed using Minitab.

Table 20.9 Number of nonconformities on printed boards for laptops per sample, with varying sample size.

Figure 20.15 u chart of nonconformities for the data in Table 20.9, constructed using Minitab.

Table 20.10 Data showing the lengths of tie rods for cars.

Table 20.11 Different processes with the same value of Cpk.

Table 20.12 Parts per million of nonconforming units for different values of Cpk.

Figure 24.1 The plan–do–check–act cycle.

Figure 24.2 Blank design FMEA form.

Figure 24.3 Blank process FMEA form.

Table 24.1 Design FMEA severity criteria.

Table 24.2 Process FMEA severity criteria.

Table 24.3 Design FMEA occurrence criteria.

Table 24.4 Process FMEA occurrence criteria.

Table 24.5 Design FMEA detection criteria.

Table 24.6 Process FMEA detection criteria.

Figure 24.4 Design FMEA example.

Figure 24.5 Process FMEA example.

Figure 24.6 List of the eight disciplines (8D).

Figure 24.7 Fault tree depicting the root causes of hazard to patients during surgery.

Figure 25.1a First article inspection process—First Article Inspection Report Approval Form.

Figure 25.1b First article inspection process—First Article Inspection Report Content/Check Sheet.

Figure 25.1c First article inspection process—Form 1: Part Number Accountability.

Figure 25.1d First article inspection process—Form 2: Product Accountability—Raw Material, Specifications and Special Process(es), Functional Testing.

Figure 25.1e First article inspection process—Form 3: Characteristic Accountability, Verification and Compatibility Evaluation.

Figure 25.1f First article inspection process—Form 3: Characteristic Accountability, Verification and Compatibility Evaluation.

Figure B.1 The screen that appears first in the Minitab environment.

Figure B.2 Minitab window showing the menu command options.

Figure B.3 Minitab window showing input and output for Column Statistics.

Figure B.4 Minitab window showing various options available under the Stat menu.

Figure B.5 Minitab display of the histogram for the data given in Example B.3.

Figure B.6 Minitab window showing Edit Bars dialog box.

Figure B.7 Minitab display of a histogram with five classes for the data in Example B.3.

Figure B.8 Minitab dot plot output for the data in Example B.4.

Figure B.9 Minitab scatter plot output for the data given in Example B.5.

Figure B.10 Minitab display of box plot for the data in Example B.6.

Figure B.11 Minitab display of graphical summary for the data in Example B.7.

Figure B.12 Minitab display of the bar chart for the data in Example B.8.

Figure B.13 Minitab display of the pie chart for the data in Example B.9.

Figure B.14 Minitab window showing the X̅-R Chart dialog box.

Figure B.15 Minitab window showing the X̅-R Chart—Options dialog box.

Figure B.16 Minitab window showing the X̅-S Chart dialog box.

Table B.1 Data for 25 samples each of size five from a given process.

Figure B.17 Minitab window showing the Capability Analysis (Normal Distribution) dialog box.

Figure B.18 Minitab windows showing the Minitab process capability analysis.

Figure B.19 Minitab window showing the P Chart dialog box.

Figure B.20 Minitab window showing the C Chart dialog box.

Figure B.21 Minitab window showing the U Chart dialog box.

Figure H.1 ANSI/ASQ Z1.4-2008 Table VIII: Limit numbers for reduced inspection.

Figure H.2 ANSI/ASQ Z1.4-2008 Table I: Sample size code letters.

Figure H.3 ANSI/ASQ Z1.4-2008 Table II-A: Single sampling plans for normal inspection.

Figure H.4 ANSI/ASQ Z1.4-2008 Table III-A: Double sampling plans for normal inspection.

Figure H.5 ANSI/ASQ Z1.4-2008 Table IV-A: Multiple sampling plans for normal inspection.

Figure H.6 ANSI/ASQ Z1.9-2008 Table A-2: Sample size code letters.

Figure H.7 ANSI/ASQ Z1.9-2008 Table C-1: Master table for normal and tightened inspection for plans based on variability unknown (single specification limit—Form 1).

Figure H.8 ANSI/ASQ Z1.9-2008 Table B-5: Table for estimating the lot percent nonconforming using standard deviation method. Values tabulated are read as percentages.

Figure H.9 ANSI/ASQ Z1.9-2008 Table B-3: Master table for normal and tightened inspection for plans based on variability unknown (double specification limit and Form 2—single specification limit).

Preface

The quality inspector is the person perhaps most closely involved with day-to-day activities intended to ensure that products and services meet customer expectations. The quality inspector is required to understand and apply a variety of tools and techniques as codified in the American Society for Quality (ASQ) Certified Quality Inspector (CQI) Body of Knowledge (BoK). The tools and techniques identified in the ASQ CQI BoK include technical math, metrology, inspection and test techniques, and quality assurance. Quality inspectors frequently work with the quality function of organizations in the various measurement and inspection laboratories, as well as on the shop floor supporting and interacting with quality engineers and production/service delivery personnel. This book, The Certified Quality Inspector Handbook (CQIH), was commissioned by ASQ Quality Press to support individuals preparing to perform, or those already performing, this type of work.

The CQIH is intended to serve as a ready reference for quality inspectors and quality inspectors in training, as well as a comprehensive reference for those individuals preparing to take the ASQ CQI examination. Examples and problems used throughout the handbook are thoroughly explained, are algebra-based, and are drawn from real-world situations encountered in the quality profession.

Acknowledgments

The authors would like to thank their families.

Fred would like to acknowledge the patience and support of his wife, Julie, and sons, Carl and George, as he worked on this book.

Ahmad would like to acknowledge the patience and support provided by his wife, Hanan, sons, Mohammed and Omar, and daughter, Leemar. Without their love, devotion, and encouragement, work on this book would not have been possible or meaningful.

Bhisham is indebted to his wife, Swarn, daughters, Anita and Anjali, son, Shiva, sons-in-law, Prajay and Mark, daughter-in-law, Aditi, and granddaughters, Priya and Kaviya, for their deep love and devotion. Without the encouragement of both our families, this project would not have been possible or meaningful.

Mary thanks her husband, Jim, and their six children for their support and understanding while she was working on this project.

We are grateful to the several anonymous reviewers whose constructive suggestions greatly improved this book. We also want to thank Matt Meinholz and Paul O’Mara of ASQ Quality Press for their patience and cooperation throughout this project.

H. Fred Walker

Ahmad K. Elshennawy

Bhisham C. Gupta

Mary McShane Vaughn

How to Use This Book

To assist readers in using this book as a ready reference or as a study aid, the book has been organized so as to conform explicitly to the ASQ CQI BoK. Each chapter title, all major topical divisions within the chapters, and every main point has been titled and then numbered exactly as they appear in the CQI  BoK.

To gain the most benefit from reading this book, it is intended that readers initially read the material in the order in which it is presented. Having read the material sequentially from beginning to end, readers are encouraged to then reread material unfamiliar or unclear to them to gain additional insights and mastery.

It should be noted that many references were used to support development of the ASQ CQI BoK, and by the authors to write this book. Individuals ­learning about quality inspection should expect to begin building a library of their own support materials—materials that have been identified in this book as well as identified and recommended on ASQ’s website.

Section I: Technical Mathematics

Chapter 1 A. Basic Shop Math

Chapter 2 B. Basic Algebra

Chapter 3 C. Basic Geometry

Chapter 4 D. Basic Trigonometry

Chapter 5 E. Measurement Systems

Chapter 6 F. Numeric Conversions

Chapter 1: A. Basic Shop Math

Properties of Real Numbers

When performing arithmetic operations on numbers, keep in mind the fundamental properties as shown in Table 1.1.

Let a, b, and c represent real numbers.

Positive and Negative Numbers

A positive number is one that is greater than zero; a negative number is less than zero. For example, the number 6 is a positive number, while –2 is a negative number.

Adding and Subtracting with Positive and Negative Numbers

We can add and subtract positive and negative numbers, as the examples show:

Multiplying and Dividing with Positive and Negative Numbers

We can also multiply and divide positive and negative numbers, as the examples show:

Fractions

A fraction relates a number of parts to the whole, and is usually written in the form

The number a is the numerator and the number b is the denominator. For example, the fraction

refers to 3 parts from a total of 8 parts. Here, 3 is the numerator and 8 is the denominator.

Equivalent Fractions

Equivalent fractions are those that express the same proportion of parts to the whole. For example, the fractions

are equivalent.

Simplified Fractions

A simplified fraction refers to a fraction in which the numerator and the denominator do not share any factors in common. A simplified fraction is found by dividing both numerator and denominator by the greatest common factor (GCF). We can find the GCF by factoring both numerator and denominator and choosing the largest factor in common.

For example, given the fraction

we can factor the numerator and the denominator

and determine that the GCF is 9. Dividing the numerator and the denominator each by 9 yields the simplified fraction

Proper and Improper Fractions

A proper fraction is one in which the numerator is less than the denominator. The fractions

are all examples of proper fractions. An improper fraction is one in which the numerator is larger than the denominator. Improper fractions can be converted into a mixed number, or a whole number and a proper fraction, by dividing the denominator into the numerator. For example:

Adding and Subtracting Fractions with Like Denominators

To add or subtract fractions with equal denominators:

1. Add or subtract the numerators and leave the denominator the same

2. Simplify the resulting fraction if necessary

Adding and Subtracting Fractions with Unequal Denominators

Many times, the denominators of the fractions we wish to add or subtract are not equal. In this case:

1. Find the least common denominator (LCD) using prime factorization

2. Find the equivalent fractions using the LCD

3. Perform the addition or subtraction

4. Simplify the resulting fraction if necessary

Prime Factorization. A prime number is an integer greater than one that is a multiple of only itself and the number 1. For example, the number 7 is a prime number since it can only be divided evenly by the numbers 1 and 7, which are called the factors of 7. Conversely, 8 is not a prime number since its factors are 1, 2, 4, and 8. A list of the first few prime numbers follows: 1, 2, 3, 5, 7, 11, 13, 17, 19, 23, 29.

A prime factorization expresses a number in terms of prime number factors. For example, the prime factorization of the number 12 is (2 × 2 × 3). To find the prime factorization of a given number, we can draw a number tree in which we successively break down the factors until we find the prime components. For example, the prime factorization of the number 100 is (2 × 2 × 5 × 5) and can be found using the tree in Figure 1.1.

Least Common Denominator. To find the LCD, express each denominator in terms of its prime factors. For example, if asked to solve

we begin with expressing the denominators in terms of their prime factors:

Record the maximum number of times each factor is used in any one expression. This will indicate how many times each factor must be multiplied to find the LCD. The factor 2 appears at most two times in the expressions, and the factor 3 appears at most two times. Therefore the LCD is calculated as:

Next, find the equivalent fractions using the LCD. The numerators can be found by cross multiplying:

Now add the equivalent fractions, and simplify the result if needed:

Adding or Subtracting Mixed Numbers

To add or subtract mixed numbers, we can convert the mixed numbers back into improper fractions and then proceed, or we can first add and subtract the whole number parts and then add and subtract the fractions. For example:

Multiplying and Dividing Fractions

To multiply fractions:

1. Multiply the numerators to obtain the numerator of the result

2. Multiply the denominators to obtain the resulting denominator

3. Simplify the resulting fraction if necessary

For example:

To divide fractions, we convert the problem into a multiplication problem:

1. Switch the numerator and the denominator of the second fraction

2. Multiply the numerators to obtain the numerator of the result

3. Multiply the denominators to obtain the resulting denominator

4. Simplify the resulting fraction if necessary

For example:

Decimals

Given a number of the form:

ABCDEFG.HIJKLM

we can define the place values for each letter-position as shown in Table 1.2.

Decimal and Fraction Equivalents

Decimal and fraction equivalents are shown in Table 1.3.

Converting Fractions to Decimals

Fractions can be converted to decimals by dividing the denominator into the numerator. For example:

We read this decimal as 375 thousandths.

Rational and Irrational Numbers

A rational number can be represented in fractional form. It has either a finite number of decimal places or an infinite (never-ending) number of repeating decimal places. For example, the numbers 0.37, 0.6894, 1.33562, 4.3–, 8.519–—– are all examples of rational numbers.

An irrational number is a number that has an infinite number of decimal places that do not repeat. An example of an irrational number is π = 3.14159 . . . , since its digits are nonrepeating and infinite.

Converting Decimals to Percentages

To convert a decimal into a percentage, multiply by 100, as shown:

Adding and Subtracting Decimals

To add or subtract decimals, line up the numbers at their decimal places. For example, the numbers 3.475, 11.55, and 2.2 can be added as shown:

Multiplying and Dividing Decimals

To multiply or divide decimals, count the total number of decimal places in the problem. The final answer will have that number of decimal places.

2 decimal places

1 decimal place

3 decimal places

Squares and Square Roots

The square of a number is simply that number multiplied by itself. The square of a number can also be written as that number to the second power. For example, the square of 7 is calculated as

A square root is denoted as follows:

Every positive number has a square root. For example, using a calculator, we can determine that

Imaginary Numbers

The square root of a negative number does not exist on the real number line. Rather, the imaginary number i is defined as the square root of negative one. The result is written in terms of i. For example,

Exponents

A whole number exponent indicates how many times a number is multiplied by itself. For example:

Order of Operations

The order of operations can be remembered by using the mnemonic device of PEMDAS, or Please Excuse My Dear Aunt Sally, which stands for parentheses, exponents, multiplication, division, addition, and subtraction. As an illustration, the expression

is correctly evaluated as follows:

Factorials

A factorial is a mathematical operation denoted by an exclamation point (!), and is evaluated in the following manner:

By definition, 0! = 1.

Factorials are used when calculating probabilities from the binomial, hypergeometric, and Poisson distributions, among others.

Truncating, Rounding, and Significant Digits

To display a result with a certain number of decimal places, we can choose to truncate the number. For example, we can truncate the number 3.527 to two decimal places by writing 3.52.

We can round a result to a certain number of digits by looking at the value of the digit to the right of the decimal place of interest. For example, if we want to round the number 3.527 to the hundredths place, we will look at the third decimal place (in this case 7) as our decision point. The rule for rounding is this: If the decision number is less than 5, do not round up. If it is 5 or greater, round up. Therefore, 3.527 would be rounded up to 3.53. However, if we rounded to the tenths place, 3.527 would be displayed as 3.5, since 2 would be our decision number.

When dealing with the precision of a measurement, we must consider significant digits. For example, instrument measurements have a certain inherent precision, which can be expressed in terms of a certain number of significant digits. We must take care to express instrument measurements using the proper number of significant digits.

Adding and Subtracting Measurements

When adding or subtracting measurements, the final answer will only be as precise as the least precise reading. Therefore, the number of decimal places of the answer should match that of the least precise reading. In the following example, the reading of 5.2 is the least precise, and the final answer is rounded to the tenths place:

Multiplying and Dividing Using Significant Digits

When multiplying measurements, display the final result with the same number of significant digits as the least accurate reading. For example, the following result will be rounded to three significant digits since the value 3.21 has three significant digits and 20.45 has four:

Bibliography

Achatz, T. 2006. Technical Shop Mathematics. 3rd ed. New York: Industrial Press.

Griffith, G. 1986. Quality Technician’s Handbook. Englewood Cliffs, NJ: Prentice Hall.

Horton, H. L. 1999. Mathematics at Work. 4th ed. New York: Industrial Press.

Chapter 2: B. Basic Algebra

Solving Algebraic Equations

When we solve an algebraic equation, we are finding the value of the unknown variable, which is denoted by a letter. To illustrate, the following equations are all examples of algebraic expressions:

In each, the goal is to solve for the value or values of the variable that make the expression true. We accomplish this by collecting terms and then isolating the unknown variable on one side of the equation by performing inverse operations.

Properties of Real Numbers

In addition to the commutative, associative, and distributive properties of real numbers (see Table 1.1), fundamental properties for real numbers also exist, as shown in Table 2.1. Let a, b, and c be real numbers.

Inverse Operations

To isolate the variable on one side of the equation, we perform a series of inverse operations on both sides of the equation. A list of inverse operations is shown in Table 2.2.

Solving Equations Using One Inverse Operation

In order to isolate x, we perform the appropriate inverse operation on both sides of the equation. In the following example, note that the inverse of adding 3 is subtracting 3:

Always perform a check of your work by putting the value of the variable into the original equation.

Solving Equations Using Two or More Inverse Operations

To solve a problem such as ax + b = c, we must do a series of inverse operations on both sides of the equation in order to isolate the variable a. In the following ­example, addition and division inverse operations are employed in succession to find the solution:

Next, check the solution:

Solving Equations by Collecting Terms

To solve a problem where the variable and/or constants appear in more than two terms, we must first collect terms and then perform the inverse operations. For example, to solve the equation 8z + 5 + 4z + –1 = 16, we must collect the variable and the constant terms before proceeding with the solution:

Check the solution:

To solve a problem such as 4s + 4 = 6s – 9, we must collect terms that appear on both sides of the equation:

Check the solution:

Solving Equations with Parentheses

To solve equations with parentheses, follow the order of operations rule PEMDAS, in which parentheses, exponents, multiplication, division, addition, and subtraction operations are performed