Design for Six Sigma A Practical Approach through Innovation Continuous Improvement Series Series Editors: Elizabeth A Cudney and Tina Kanti Agustiady PUBLISHED TITLES Design for Six Sigma: A Practical Approach through Innovation Elizabeth A Cudney and Tina Kanti Agustiady Design for Six Sigma A Practical Approach through Innovation Elizabeth A Cudney Tina Kanti Agustiady CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2017 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S Government works Printed on acid-free paper Version Date: 20160421 International Standard Book Number-13: 978-1-4987-4255-9 (Hardback) This book contains information obtained from authentic and highly regarded sources Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint Except as permitted under U.S Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978750-8400 CCC is a not-for-profit organization that provides licenses and registration for a variety of users For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe Library of Congress Cataloging-in-Publication Data Names: Cudney, Elizabeth A., author | Agustiady, Tina, author Title: Design for Six Sigma : a practical approach through innovation / authors, Elizabeth A Cudney and Tina Agustiady Description: Boca Raton : Taylor & Francis, CRC Press, 2016 | Series: Continuous improvement series | Includes bibliographica references Identifiers: LCCN 2016005746 | ISBN 9781498742559 (hard copy) Subjects: LCSH: Six sigma (Quality control standard) | New products Quality control | Industrial design Classification: LCC TS156.17.S59 C83 2016 | DDC 658.5/75 dc23 LC record available at https://lccn.loc.gov/2016005746 Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com This book is dedicated to my husband, Brian, whose love and support keep me grounded and motivated To my handsome, thoughtful, and funny son, Joshua To my beautiful, talented, and driven daughter, Caroline I love you with all my heart! Beth Cudney To my first born child, Arie Agustiady Your love for books makes me want to continue writing every step of the way! To my princess, Meela Agustiady You encourage me to be a better woman, mother, and professional! To my dear husband Andry, your love and support keep me motivated and driven! Tina Agustiady Contents Preface Authors Acknowledgments Design for Six Sigma Overview Six Sigma Review DFSS Comparison of Six Sigma and DFSS Conclusion History of Six Sigma Variation Conclusion Design for Six Sigma Methodology Conclusion Design for Six Sigma Culture and Organizational Readiness Organizational Change Management Resistance to Change Using Known Leaders to Challenge the Status Quo Communicating Change Conclusion Technical Design Review: Define and Measure Phases Technical Design Review Gate Readiness: Define and Measure Phases Assessment of Risks Project Charter Introduction Project Charter Steps Risk Assessment Developing the Business Case Conclusion Balanced Scorecard Balanced Scorecard Key Performance Indicators Cost of Quality Financial Performance Process Performance Conclusion Benchmarking Best in Class Conclusion Project Management Why Projects Fail Management by Project Integrated Project Implementation Critical Factors for Project Success Project Organization Resource Allocation Project Scheduling Project Tracking and Reporting Project Control Project Termination Project Systems Implementation Outline Planning Organizing Scheduling (Resource Allocation) Control (Tracking, Reporting, and Correction) Termination (Close or Phase-Out) Documentation Project Plan Scope Management Conclusion Technical Design Review: Analyze Phase Technical Design Review Gate Readiness: Analyze Phase Assessment of Risks Gathering the Voice of the Customer VOC in Product Development Customers/Stakeholders Voice of the Customer Critical to Satisfaction Critical to Quality Conclusion 10 Quality Function Deployment Kano Model Quality Function Deployment Conclusion 11 TRIZ TRIZ Methodology Nine Windows TRIZ Methodology Contradictions Technical Contradictions Physical Contradictions Separation Principle Contradiction Matrix The 40 Principles of Invention TRIZ and DFSS Conclusion 12 Lean Design Single-Minute Exchange of Dies (SMED) What Is SMED? Conclusion 13 Design for X Methods Design for Manufacturability Design for Assembleability Design for Reliability Design for Serviceability Design for Environment Design for Testability Conclusion 14 Pugh Concept Selection Matrix Conclusion 15 Modeling of Technology Ideal Function P-Diagram Functional Analysis System Technique Conclusion 16 Taguchi Design Taguchi Loss Function Mahalanobis–Taguchi System Multidimensional Systems Mahalanobis–Taguchi Steps Step 1: Normal Group Calculations Step 2: Normal Space Calculations Step 3: Test (Abnormal) Group Calculations Step 4: Optimize the System MTS Steps Using the Graduate Admission System Example Step 1: Normal Group Calculations Step 2: Normal Space Calculations Step 3: Test Group Calculations Step 4: Optimize the System Conclusion 17 Design Failure Modes and Effects Analysis Failure Modes and Effects Analysis Poka Yokes Conclusion 18 Design of Experiments Design of Experiments (DOE) Conclusion 19 Reliability Testing Types of Systems Redundant Systems 20 Measurement Systems Analysis Gauge R&R Conclusions Technical Design Review: Design Phase Technical Design Review Gate Readiness: Design Phase Assessment of Risks 21 Capability Analysis Capability Analysis Control Charts X-Bar and Range Charts Calculation of Control Limits Plotting Control Charts for R- and X-Bar Charts Plotting Control Charts for MR and Individual Control Charts Defects per Million Opportunities (DPMO) Conclusion 22 Statistical Process Control Control Charts key performance indicator (KPI): a method for tracking or monitoring the progress of existing daily management systems lower control limit (LCL): the limit above which the process subgroup statistics must remain for the process to be in control Typically, the LCL is three standard deviations below the center line lower specification limit (LSL): the lowest value of a product specification for the product to be acceptable to the customer main effect: a measure of the effect of an individual factor removing the effect of all other factors Master Black Belt (MBB): an individual who trains and mentors others in Six Sigma tools and methodologies mean: the arithmetic average of a set of values It is calculated by adding the sample or population values together and dividing by the number of elements (n) denotes a sample mean; µ denotes a population mean mean time between failures (M TB F): the mean time between successive failures of a repairable product MTBF is a measure of product reliability measurement system: a system that is used to measure a CTQ All measurement systems should have an acceptable gauge R&R measurement system analysis (MSA): used to determine the reliability of a measurement instrument or gauge median: the middle value of a data set when the values are arranged in ascending or descending order metric: a performance measure that is linked to the goals and objectives of an organization multigenerational plan (MGP): a planned introduction phasing for product and process launch MGP allows the team to phase in more risky features and functionality noise: unexplained variability in a response non-value-added (NVA): those process steps that take time, resources, or space, but not transform or shape the product or service toward that which is sold to a customer These are activities that the customer would not be willing to pay for opportunity: any of the total number of chances for a defect to occur output: a product or service delivered by a process Pareto chart: a vertical bar graph for attribute or categorical data that shows the bars in descending order of significance, ordered from left to right Helps to focus on the vital few problems rather than the trivial many An extension of the Pareto principle suggests that the significant items in a given group normally constitute a relatively small portion of the items in the total group Conversely, a majority of the items will be of relatively minor significance (i.e., the 80/20 rule) PDCA cycle: plan-do-check-act cycle P DCA is a repeatable four-phase implementation strategy for process improvement Sometimes referred to as the Deming or Deming cycle poka yoke: a Japanese expression meaning “mistake proof.” A method of designing production or administrative processes that will, by their nature, prevent errors This may involve designing fixtures that will not accept an improperly loaded part process: an activity that blends inputs to produce a product, provide a service, or perform a task process capability: a comparison of the actual process performance with process specification limits Measures of process capability include, but are not limited to, Cp , Cpk, dpm, and σlevel process control: a process is said to be in control if all special causes of variation have been removed and only common cause or natural variation remains process map: a visual representation of the sequential flow of a process Used as a tool in problem solving, this technique makes opportunities for improvement apparent pull: a system in which replenishment does not occur until a signal is received from a downstream customer push: conventional production in which product is pushed through operations based on sales projections or material availability quality characteristic: an aspect of a product that is vital to its ability to perform its intended function quality function deployment (QFD): a system for translating customer requirements into appropriate company requirements at each stage from research and product development, to engineering and manufacturing, to marketing/sales and distribution Makes use of the voice of the customer throughout the process range: a measure of variability in a data set The range is the difference between the largest and the smallest value in a data set reliability: the probability that a product will function properly for a specified period of time, typically under specified conditions return on investment (ROI): a profitability ratio that represents the benefit from an investment It is calculated by dividing the net profit by the total assets rework: an activity to correct defects produced by a process robust design: a term generically used to describe the ability to make a product or process design insensitive to sources of variation root cause: the ultimate reason for an event or condition run chart: a graphical tool that illustrates a process over time scatter diagram: a chart in which one variable is plotted against another to determine whether there is correlation between the two variables scatterplot: a two-dimensional plot that displays bivariate data See scatter diagram screening design: an experiment designed to separate the significant factors from the insignificant factors sigma (σ): sigma has two meanings in the context of Six Sigma Sigma is the measure of quality, as in Six Sigma Sigma is also the Greek symbol that is used to describe the standard deviation of a statistical population sigma capability: a measure of process capability that represents the number of standard deviations between the center of a process and the closest specification limit See sigma level sigma level: a measure of process capability that represents the number of standard deviations between the center of a process and the closest specification limit See sigma capability Six Sigma: a quality improvement and business strategy that emphasizes impacting the bottom line by reducing defects, reducing cycle time, and reducing costs Six Sigma began in the 1980s at Motorola An all-inclusive methodology (reactive and proactive) for selecting and executing projects focused on identifying and satisfying customer needs special causes of variation: nonrandom causes of variation Control charts can be used to detect special causes of variation specification limits: customer-driven boundaries of acceptable values for a product or process stability: a process is said to be stable if there are no recognizable pattern changes and no special causes of variation are present stakeholder: a person who will be impacted by the product or process when completed standard: a prescribed, documented method or process that is sustainable, repeatable, and predictable standard deviation: a measure of variability in a data set It is the square root of the variance standardization: the system of documenting and updating procedures to make sure that everyone knows clearly and simply what is expected of them Essential for the application of the PDCA cycle statistical control: a process is said to be in statistical control when it exhibits only random variation statistical process control (SPC): the application of statistical methods in the control of processes Generally, the emphasis with SP C is on tools, and specifically on SP C charts that plot performance over time, comparing the performance with control limits These graphical and statistical methods are used for measuring, analyzing, and controlling variation in a process for continuous improvement total revenue: the price of a product multiplied by the quantity sold in a given time period upper control limit (UCL): the upper limit below which a process must remain to be in control Typically, the UCL is three standard deviations above the center line upper specification limit (USL): the highest value at which a product is acceptable to the customer user: a person who will use or operate the product or process utility: the pleasure or satisfaction obtained from a good or service value: a capability provided to a customer for an appropriate price value added: any process or operation that shapes or transforms the product or service into a final form that the customer will purchase variability: a process is said to exhibit variation or variability if there are changes or differences in the process variance: a measure of variability in a data set or population Variance is equal to the squared value of the standard deviation variation: see variability voice of the customer (VOC): desires and requirements of the customer at all levels, translated into real terms for consideration in the development of new products, services, and daily business conduct waste: also known as muda Any process or operation that adds cost or time and does not add value Eight types of waste have been identified: Waste from overproduction Waste from waiting or idle time Waste from unnecessary transportation Waste from inefficient processes Waste from unnecessary stock on hand Waste of motion and efforts Waste from producing defective goods Waste from unused creativity Xs: the most critical elements to control to keep the Y under control Similar to root cause Ys: the main response being measured in a project Ys should be a CTQ ZLT (sigma long term): a measure of the process capability over a time period in which all sources of variation are included in the data ZLT is calculated by determining the number of standard deviations that fit between the mean and the specification limits of the long-term data ZS T (sigma short term): a measure of the process capability over a time period in which not all the sources of variation are included in the data ZST is calculated by determining the number of standard deviations that fit between the mean and the specification limits of the short-term data Index A AAA battery phone charger, 267 Abnormal group calculations, see Test group calculations Accuracy, gauge R&R, 204 Additive model, system, 254–255, 280, 296–297 Affinity diagram, 89, 243, 307 AIAG, see Automotive Industry Action Group (AIAG) Akao, Yoji, 94 Altshuller, Genrich S., 105, 106, 108 Appraisal costs, 50 Assessment, of risks, 40, 83, 211, 237 Assignable cause, see Special cause variation Attribute data, 215, 224, 228–230 Attribute gauge R&R, 203 Automotive Industry Action Group (AIAG), 174 Average, and range charts, 225 B Backup systems, see Redundant systems Badiru’s rule, 71 Balanced scorecard, KPIs, 47–56 cost of quality, 50–51 financial performance, 51–52 process performance, 52–56 Benchmarking, 59–65, 242, 247 Best-in-class (BIC), 59–64 Best Manufacturing Practices (BMP) Program, 61 Bias, gauge R&R, 204 Binary data, 205 BMP, see Best Manufacturing Practices (BMP) Program Brainstorming, 99, 131, 247, 324, 327 C C&E diagram, 35, 36, 37 Capability analysis, 213–219 control charts, 214–217 calculation of control limits, 216–217 plotting, 217 X-bar and range charts, 215–216 Defects per Million Opportunities (DPMO), 217–218 Capital investment, 45 cdf, see Cumulative distribution function (cdf) Central lines, X-bar and range charts, 215, 224 CFRs, see Critical functional responses (CFRs) Checklists, 210, 236 Combination system, 197 Common cause variation, 12, 222 Communication, 30–34 Computer tools, 72 Consumer Product Safety Commission, 318 Contact methods, 179–180 Continuous probability distributions, 223 Contradiction matrix, 109 Control charts, 214–217 calculation of control limits, 216–217 and individual, 217 plotting, for MR, 217 X-bar and range charts, 215–216 plotting, 217 Control factors, 142–143 Control limits calculation of, 216–217, 224–225 upper and lower, 215, 224, 226–227 Control systems, 179 Correlation matrix, 155 Cost performance index (CPI), 51 Critical functional responses (CFRs), 253, 255, 279, 295 Critical to quality (CTQ), 89–90, 97, 322 Critical to satisfaction (CTS), 88–89 Cross-functional leadership, 234 CTQ, see Critical to quality (CTQ) CTS, see Critical to satisfaction (CTS) Cumulative distribution function (cdf), 194 Customer, 86 feedback, 297 metrics, 48 reviews, 255–256 survey, 303, 305 D Datum, 131, 136 Decision trees, 34 Defects per million opportunities (DPMO), 52, 53, 217–218 Defects per unit (DPU), 52 Defect wastes, 124 Define, measure, analyze, design, and verify (DMADV), 3, 5, 13, 110, 321 Define, measure, analyze, design, optimize, verify (DMADOV), 16, 19 Define, measure, analyze, improve, and control (DMAIC), 2–3, 10, 13, 19–20, 110 Delighters, 94 Deming, W Edwards, 12 Design failure mode and effects analysis (DFMEA), 173–184, 274, 276–278, 293–295, 315–316, 336–337 failure modes and effects analysis (FMEA), 173–179 poka yokes, 179–183 Design for assembleability (DFA), 127–128 Design for environment (DFE), 129 Design for manufacturability (DFM), 127 Design for reliability, 128 Design for serviceability (DFS), 128–129 Design for Six Sigma (DFSS), 1, 12–13, 39, 115; see also Technical design review (TDR) case study hospital bed, 321–339 paper shredder, 281–299 portable energy solutions, 259–280 Sure Mix Gas Can, 239–258 universal iPhone dock, 301–319 culture and organizational readiness, 23–37 change management, 23–29 communicating change, 30–34 resistance to change, 29–30 future and challenges of, 233–235 engagement and success factors, 234–235 methodology, 15–21 DMAIC and, 19–20 modeling of technology, 139–145 functional analysis system technique, 143 ideal function, 139–141 P-diagram, 141–143 overview, 3–6 Six Sigma vs., 6–7 and TRIZ, 109–113 Design for testability, 129 Design for X (DFX) methods, 127–130, 245–247, 267, 286, 328–335 design for assembleability, 127–128 design for environment, 129 design for manufacturability, 127 design for reliability, 128 design for serviceability, 128–129 design for testability, 129 Design of experiments (DOE), 185–192 environmental variables affect, 190–191 fractional factorial DOE, 187, 188 full factorial DOE, 187 phases of, 190 Design reuse, 124 Design trade-offs, 131–132, 135 DFA, see Design for assembleability (DFA) DFE, see Design for environment (DFE) DFM, see Design for manufacturability (DFM) DFMEA, see Design failure mode and effects analysis (DFMEA) DFS, see Design for serviceability (DFS) DFSS, see Design for Six Sigma (DFSS) DFX, see Design for X (DFX) methods Direct labor costs, 125 Direct material costs, 125 Discrete gauge R&R, 202 Discrete probability distributions, 223 Discrimination, gauge R&R, 204 DMADOV, see Define, measure, analyze, design, optimize, verify (DMADOV) DMADV, see Define, measure, analyze, design, and verify (DMADV) DMAIC, see Define, measure, analyze, improve, and control (DMAIC) Docking station, 301, 315, 318 DOE, see Design of Experiments (DOE) DPMO, see Defects per Million Opportunities (DPMO) DPU, see Defects per unit (DPU) E E-mail surveys, 87 Engagement, and success factors, 234–235 Enterprise-wide project management, see Management by project (MBP) Euclidean distance (ED), 149–150 Exciting quality, 311 Expected quality, 310–311 External benchmarking, 61 External failure costs, 51 External setup, 119 F Failure mode and effects analysis (FMEA), 144, 173–179, 315–316 Failure modes, effects, and criticality analysis (FMECA), see Design failure mode and effects analysis (DFMEA) FAST, see Functional analysis system technique (FAST) Father of Quality Management, see Deming, W Edwards Fault tree, 143, 144, 274, 276 FDA, see Food and Drug Administration (FDA) Financial performance, 47–48, 51–52 Fishbone diagram, see C&E diagram 5s principles, 122–123 Fixed-value methods, 180 FMEA, see Failure mode and effects analysis (FMEA) FMECA, see Design failure mode and effects analysis (DFMEA) Focus groups, 87–88 Foldable solar panel, 269 Food and Drug Administration (FDA), 323 40 principles of invention, 109 Fractional factorial DOE, 187, 188 Full factorial DOE, 187 Functional analysis system technique (FAST), 143, 274, 276 Functional benchmarking, 61 G Galvin, Bob, Gantt chart, 80, 240, 303, 304, 210, 236 Gate, technical design review, 39–40, 83–84, 210, 211, 236, 237 Gauge repeatability and reproducibility (R&R), 203–208 General Electric, 281 Generic benchmarking, 61 Genichi Taguchi, 147, 149 Graduate admission system, 157–172 H Harry, Mikel, Harvard Business School, 47 Hazard function, 194 Heijunka, 118 Helical compression spring, 140 Hooke’s law, 140 HOQ, see House of quality (HOQ) Hospital bed case study, 321–339 Design for Six Sigma overview, 321–324 project boundaries, 322–323 project description, 321–322 project goals, 322 project management, 323–324, 325, 326 requirements and expectations, 322 designing, for improving stakeholders’ level of care, 321 develop phase Design for X methods and concept generation, 328–335 invent/innovate phase, 324, 326–327 KJ analysis and Kano model, 324, 326–327 voice of the customer, 324 Pugh concept selection matrix, 335–338 final design prototype, 338–339 optimize, 336–338 tips to improve design, 338 verify, 336 quality function deployment, 327–328 House of quality (HOQ), 95–104, 243–245, 260, 264, 265, 284–286, 287, 303, 327, 329 I I2DOV, see Invention and innovation, development, optimization, and verification (I2DOV) plan Ideal function, 139–141 Identify, design, optimize, validate (IDOV), 110 IEC, see International Electrotechnical Commission (IEC) IEEE, see Institute of Electrical and Electronics Engineers (IEEE) IFR, Items for resolution (IFR) chart Inspection costs, 50 Institute of Electrical and Electronics Engineers (IEEE), 318 Instrument accuracy, gauge R&R, 204 Instrument bias, gauge R&R, 204 Integrated project implementation, 72–73 Internal benchmarking, 61 Internal business process, 48 Internal failure costs, 51 Internal setup, 119 International Electrotechnical Commission (IEC), 323 Invention and innovation, development, optimization, and verification (I2DOV) plan, 240, 241, 261, 278 Inverse matrix, 155 Items for resolution (IFR) chart, 80 K Kaizen, 122 Kanbans, 117 Kano Model, 93–94, 245, 265–266, 308–310, 324, 326–327 Kano Model of Customer/Consumer Satisfaction (KMCCS), 310 Kaplan, Robert, 47 Kawakita Jiro (KJ) analysis, 324, 326–327 Key performance indicators (KPIs), 49–56 KJ, see Kawakita Jiro (KJ) analysis KMCCS, see Kano Model of Customer/Consumer Satisfaction (KMCCS) KPIs, see Key performance indicators (KPIs) L Lagging indicators, 49 Leadership, 234–235 Leading indicators, 49 Lean, 20, 115–126 Learning, and growth metrics, 48–49 Limit switches, 179–180 Lithium ion phone charger, 269 M MacGyver, 271 Mahalanobis, Prasanta Chandra, 149 Mahalanobis distance (MD), 149, 150–151, 155 Mahalanobis space (MS), 153 Mahalanobis–Taguchi System (MTS), 149–152 abnormal group calculations, 155–156 graduate admission system, 157–172 normal group calculations, 153–155 normal space calculations, 155 optimization, 156–157 test group calculations, 155–156 Management by project (MBP), 70–71 Margin, 51–52 Market share, 51 MD, see Mahalanobis distance (MD) Mean time between failures (MTBF), 196 Measure, of central tendency, 12 Measurement capability index, see Precision-to-tolerance (P/T) ratio Measurement systems analysis (MSA), 201–209; see also Technical design review (TDR) Measures, of spread of data, 12 Mistake proofing, 124, 179–183 Motion-step method, 180 Motorola, 9, 281 MR, plotting control charts for, 217 MS, see Mahalanobis space (MS) MTBF, see Mean time between failures (MTBF) MTS, see Mahalanobis–Taguchi System (MTS) Muda, see Waste Multidimensional systems, 152–153 Murphy’s law, 71 N National sustainability improvement, 45 Net present value, 52 New, unique, and difficult (NUD) requirements, 243, 245–246, 263 Nine Windows, 106–107 Noise factors, 143, 295, 296 Nonrecurring design costs, 125 Noriaki Kano, 93, 308 Normal group calculations, 153–155, 158–162 Normal space calculations, 155, 162–163 Norton, David, 47 NUD, see New, unique, and difficult (NUD) requirements O OA, see Orthogonal array (OA) One-dimensional quality, 310–311 One-on-one interviews, 88 Operational overheads, 125 Operator bias, gauge R&R, 204 Organization, project, 74 Orthogonal array (OA), 156, 166 OtterBox Defender Series cases, 301–302, 303 P Paper shredder case study develop, 286–295 concept generation, 286, 287–290 design failure modes and effects analysis (DFMEA), 293–295 Design for X methods, 286 final design, 292–293 Pugh concept selection matrix, 290–291 invent/innovate, 282–285 Quality Function Deployment (QFD), 284–286, 287 voice of the customer, 282–284 optimization, 295–297 robustness and tenability, 295–296 system additive model, 296–297 project description, 281–282 goals and requirements, 282 management, 282 verify, 297–299 customer feedback, 297 robustness evaluation, 297–299 Parallel system, 196, 197 Parameter Diagram (P-diagram), 141–143, 253, 254, 272–273, 295, 336 Parking lot, see Items for resolution (IFR) chart Parkinson’s law, 71 Patent studies, 247 PCSM, see Pugh’s concept selection matrix (PCSM) Pdf, see Probability density function (pdf) P-diagram, see Parameter Diagram (P-diagram) Performance attributes, see Expected quality PERT, see Program Evaluation and Review Technique (PERT) Peter’s principle, 71 PFMEAs, see Process FMEAs (PFMEAs) Plan, project, 80 PMBOK, see Project Management Body of Knowledge (PMBOK) PMI, see Project Management Institute (PMI) Poka yoke, see Mistake proofing Portable energy solutions case study, 259–280 develop, 267–271 concept generation, 267–271 Design for X methods, 267 invent/innovate, 261–263 Kano analysis, 265–266 modeling of technology, 272–274 Pugh’s concept selection, 274, 275 super concept, 273 optimize modeling of robustness, 274 project description, 259–260 project goals, 260–261 boundaries, 260–261 management, 261 requirements and expectations, 260 quality function deployment (QFD), 263–265 system variance model, 278–280 develop and confirm robustness additive models, 278–280 verify design failure mode and effects analysis, 274, 276–278 Potential failure modes and effects analysis, see Design failure mode and effects analysis (DFMEA) Precision, gauge R&R, 204 Precision-to-tolerance (P/T) ratio, 204 Prevention costs, 50 Probability density function (pdf), 194 Probability distributions, 223 Process capability indices, 53–56 Process delays, 124 Process efficiency waste, 124 Process FMEAs (PFMEAs), 173 Process performance, 52–56 Product-specific capital investments, 125 Profitability, 45 Program Evaluation and Review Technique (PERT), 36, 37, 210, 236, 240, 241, 256 Project charter, 41–45 developing business case, 44–45 risk assessment, 42–44 steps, 41–42 Project control, 75–76 Project failure, 69–70 Project management, 67–82; see also Technical design review (TDR) control, 75–76 critical factors for success, 73–74 documentation, 79–80 enterprise-wide (see Management by project (MBP)) failure, 69–70 implementation outline, 76–79 control, 78–79 organizing, 77–78 planning, 76–77 scheduling, 78 termination, 79 integrated project implementation, 72–73 organization, 74 plan, 80 resource allocation, 74 scheduling, 75 scope management, 80–81 termination, 76 tracking and reporting, 75 Project Management Body of Knowledge (PMBOK), 76 Project Management Institute (PMI), 76 P/T ratio, see Precision-to-tolerance (P/T) ratio Pugh’s concept selection matrix (PCSM), 131–137, 174, 248, 274, 275, 290–291, 311, 313, 335–338 Pull-flow diagram, 120 Pull technique, 116, 117 Q QFD, see Quality Function Deployment (QFD) Quadratic loss function (QLF), 147–149 Qualitative tools, 72 Quality costs, 50–51 Quality Function Deployment (QFD), 93–104, 263–265, 284–286, 287, 307–308, 327–328 and house of quality (HOQ), 95–104 Kano Model, 93–94 Quality loss function, see Quadratic loss function (QLF) Quantitative tools, 72, 73 R Range chart (R-chart), 215–216, 217, 224 and average charts, 225 moving, and individual control charts, 225–226 X-bar and, 224 R-chart, see Range chart (R-chart) Redundant systems, 198 Reliability testing redundant systems, 198 types of system, 196–197 combination system, 197 parallel system, 196, 197 series system, 196 Repeatability, gauge R&R, 204 Reproducibility, gauge R&R, 204 Resolution, see Discrimination, gauge R&R Resource allocation, 74 Revenue growth, 51 Risk assessment, 40, 42–44, 83, 211, 237 Risk exposure, 45 Risk impact assessment, 35, 40 Risk priority number (RPN), 177, 179, 276, 278 Rolled throughput yield (RTY), 52, 53 Root cause analysis, 35, 36 RPN, see Risk priority number (RPN) S Satisfaction, and complaint cards, 88 Scale factors, 143 Schedule performance index (SPI), 51 Scheduling, project, 75 Schroeder, Richard, Scorecards, 210, 236 Self-leaders, 30 Separation principle, 108–109 Series system, 196 Shewhart constants, 226, 228 Shingo, Shigeo, 124 Sigma level, 53 Signal factor, 142 Signal-to-noise (S/N) ratio, 156, 157, 169, 297 Single-minute exchange of dies (SMED), 118–125 SIPOC, see Suppliers, inputs, processes, outputs, customers (SIPOC) model 6Ms, 36 Six Sigma, 217, 218 DFSS vs., 6–7 history, 9–14 overview, 2–3 SMART, see Specific, measurable, achievable, relevant, time bounded (SMART) metrics Smartphone, survey responses, 261–263 SMED, see Single-minute exchange of dies (SMED) Smith, Bill, S/N ratio, see Signal-to-noise (S/N) ratio Software tools, 72 Solar, and lithium ion phone charger, 268–269 Solar heating dish, 271 Solar-kinetic charger, 269–271 SPC, see Statistical process control (SPC) Special cause variation, 12, 222 Specific, measurable, achievable, realistic, time-bounded (SMART), 50, 73–74 Specification limits, 228 SPI, see Schedule performance index (SPI) Stakeholders, 86 Standard deviation, 154 Statistical process control (SPC), charts, 221–231 attribute data formulas, 228–230 calculation of control limits, 224–225 for moving range and individual control charts, 225–226 for range and average charts, 225 X-bar and range charts, 224, 226–228 Status quo, 23, 24, 30, 32–33 The Steve Roesler Group, 31 Strategic planning, 61 Strengths, weaknesses, opportunities and threats (SWOT) analysis, 34, 35 Super concept, 273 Suppliers, inputs, processes, outputs, customers (SIPOC) model, 63 Sure Mix Gas Can case study, 239–258 additive model, system, 254–255 concept generation, 247–252 customer reviews, 255–256 Design for X methods, 245–247 field testing (prototype acceptance), 257 future project targets, 256–257 invent/innovate, 242–244 affinity diagram, 243 benchmarking, 242 house of quality (HOQ), 243–245 voice of the customer, 242–243 Kano analysis, 245 lessons learned, 256 project description, 239–242 boundaries/scope, 240 expectations, 240 goals, 239 management, 240–242 robustness/tenability, 253–254 technology modeling, 253 variational sensitivities and system variance model, 255 Survival/reliability function, 194 SWOT, see Strengths, weaknesses, opportunities and threats (SWOT) analysis T Taguchi loss function, see Quadratic loss function (QLF) Takt time, 124–125 Technical design review (TDR), 1–2, 16, 18, 39–40, 256 analyze phase, 82–83 assessment of risks, 83 gate readiness, 83 define and measure phases, 38–40 assessment of risks, 40 gate readiness, 39–40 design phase, 209–211 assessment of risks, 211 gate readiness, 211 verify phase, 235–237 assessment of risks, 237 gate readiness, 237 Termination, project, 76 Test group calculations, 155–156, 163–166 Theoria Resheneyva Isobretatelskehuh Zadach (TRIZ), 105–114 contradiction matrix, 109 and DFSS, 109–113 40 principles of invention, 109 key steps, 107–108 methodology, 105–106 Nine Windows, 106–107 physical contradiction, 108 separation principle, 108–109 technical contradiction, 108 3.4 DPMO, 217 Threshold qualities, see One-dimensional quality TIPS, see Theoria Resheneyva Isobretatelskehuh Zadach (TRIZ) Tollgates, see Technical design review (TDR) Total-cost approach, vs price-of-product approach, 60 Tracking and reporting, project, 75 Triad approach TRIZ, see Theoria Resheneyva Isobretatelskehuh Zadach (TRIZ) True value, gauge R&R, 204 2-cycle engine, 242, 243 Type I, and II errors, 222 U Unit space, see Mahalanobis space (MS) Universal iPhone dock case study, 301–319 concept generation, 311–313 Pugh concept selection matrix, 311, 313 design failure modes and effects analysis (DFMEA), 315–316 final design, 313–315 Kano analysis, 308–310 one-dimensional quality, 310–311 exciting quality, 311 expected quality, 310–311 project description, 301–319 boundaries, 303 goals, 302 requirements and expectations, 302 project management, 303–308 affinity diagram, 307 customer survey, 303, 305 quality function deployment (QFD), 307–308 survey results, 305–306 voice of the customer, 303 prototype, final design, 316–318 testing, 318 verification, 318 Upper, and lower control limits, 215, 224, 226–227 V Value-added activities, 116 Value stream mapping, 116, 117 Variable data, 215, 223 Variance model, system, 278–280 Voice of the customer (VOC), 13, 99, 242–243, 259, 260, 261, 263, 265, 282–284, 303, 324, 328 critical to quality, 89–90 critical to satisfaction, 88–89 customers, 86 gathering, 87–88 in product development, 85–86 stakeholders, 86 W Warning systems, 179 Waste, 125 Weighted PCSM, 131, 134 Welch, Jack, 281 “What’s in it for me?” (WIIFM), 25 Work in process (WIP), 124 X X-bar chart, 215–216, 217, 224 Z Zero defects, 124 Zero quality control (ZQC), 124, 179, 180 ... Sigma: A Practical Approach through Innovation Elizabeth A Cudney and Tina Kanti Agustiady Design for Six Sigma A Practical Approach through Innovation Elizabeth A Cudney Tina Kanti Agustiady CRC... Cataloging-in-Publication Data Names: Cudney, Elizabeth A. , author | Agustiady, Tina, author Title: Design for Six Sigma : a practical approach through innovation / authors, Elizabeth A Cudney and Tina Agustiady.. .Design for Six Sigma A Practical Approach through Innovation Continuous Improvement Series Series Editors: Elizabeth A Cudney and Tina Kanti Agustiady PUBLISHED TITLES Design for Six Sigma: A