A Primer on the Taguchi MethodSociety of Manufacturing Engineers, 1990 - 247 sayfa A clear, simple and essentially non-mathematical presentation, this practical guide introduces you to the basic concepts, techniques and applications of the renowned Taguchi approach. A Primer on the Taguchi Method introduces the fundamental concepts of Taguchi experimental design and shows engineers how to design, analyze, and interpret experiments using the Taguchi approach for a wide range of common products and processes. Written for manufacturing and production engineers, as well as design engineers and managers, this book explains the most practical ways to apply the Taguchi approach. The Taguchi approach to quality: the power of the Taguchi approach shows how it can be applied to an array of products from automobiles to computers. Learn the extraordinary benefits of building quality into the design, the heart of the Taguchi technique. Numerous real-world examples will help you see how the Taguchi Method works in a variety of manufacturing applications.For those who need a more rigorous statistical treatment, the book's working appendices provide full mathematical details on orthogonal arrays, triangular tables and linear graphs, plus fully worked solutions to problems presented in the example case studies. |
İçindekiler
512 REPETITIONS UNDER CONTROLLED NOISE CONDITIONS | 94 |
513 DESIGN AND ANALYSIS SUMMARY | 96 |
EXERCISES | 98 |
Analysis of Variance ANOVA | 100 |
63 ONE WAY ANOVA | 106 |
64 ONE FACTOR TWO LEVEL EXPERIMENTS ONE WAY ANOVA | 112 |
641 Confidence Intervals | 116 |
65 TWO WAY ANOVA | 117 |
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47 SPECIFYING TOLERANCE LEVELS | 37 |
EXERCISES | 39 |
Working Mechanics of the Taguchi Design of Experiments | 40 |
53 DESIGNING THE EXPERIMENT | 44 |
531 Order of Running the Experiments | 46 |
532 Analysis of the Results | 47 |
533 Quality Characteristics | 49 |
534 ANOVA Terms and Notations | 50 |
536 Degrees of Freedom DOF | 52 |
537 Projection of the Optimum Performance | 55 |
54 DESIGNING WITH MORE THAN THREE VARIABLES | 56 |
542 Designs with 3 Level Variables | 58 |
551 Steps in the Design and Analysis Degrees of Freedom DOF | 62 |
552 Interaction Effects | 68 |
553 Key Observations | 71 |
554 More Designs with Interactions | 72 |
56 DESIGNS WITH MIXED FACTOR LEVELS | 75 |
561 Preparation of a 4 Level Column | 77 |
562 Preparation of an 8 Level Column | 79 |
57 DUMMY TREATMENT COLUMN DEGRADING | 82 |
58 COMBINATION DESIGN | 87 |
59 DESIGNING EXPERIMENTS TO INVESTIGATE NOISE FACTORS | 90 |
510 BENEFITING FROM REPETITIONS | 91 |
511 DEFINITION OF SN RATIO | 92 |
66 EXPERIMENTS WITH REPLICATIONS | 121 |
661 Procedures for Pooling | 124 |
67 STANDARD ANALYSIS WITH SINGLE AND MULTIPLE RUNS | 126 |
672 Pooling | 134 |
673 Confidence Interval of Factor Effect | 138 |
674 Estimated Result at Optimum Condition | 139 |
675 Confidence Interval of the Result at the Optimum Condition | 140 |
676 Analysis with Multiple Runs | 142 |
68 APPLICATION OF THE SN RATIO | 145 |
682 Advantage of SIN Ratio over Average | 146 |
683 Computation of the SN Ratio | 148 |
684 Effect of the SN Ratio on the Analysis | 150 |
685 When to Use the SN Ratio for Analysis | 154 |
EXERCISES | 155 |
Loss Function | 156 |
72 AVERAGE LOSS FUNCTION FOR PRODUCT POPULATION | 160 |
EXERCISES | 171 |
BrainstormingAn Integral Part of the Taguchi Philosophy | 172 |
83 TOPICS OF THE DISCUSSIONS | 174 |
84 TYPICAL DISCUSSIONS IN THE SESSION | 175 |
EXERCISES | 178 |
Examples of Taguchi Case Studies | 180 |
92 APPLICATION EXAMPLES INCLUDING DESIGN AND ANALYSIS | 181 |
Study of Crankshaft Surface Finishing Process | 185 |
Automobile Generator Noise Study | 189 |
Engine Idle Stability Study | 192 |
Instrument Panel Structure Design Optimization | 194 |
Study Leading to the Selection of the Worst Case Barrier Test Vehicle | 197 |
Airbag Design Study | 202 |
Transmission Control Cable Adjustment Parameters | 203 |
References | 209 |
Orthogonal arrays triangular tables and linear graphs | 210 |
FTables | 217 |
Glossary | |
Index | |
Diğer baskılar - Tümünü görüntüle
Sık kullanılan terimler ve kelime öbekleri
analysis ANOVA ANOVA Table application approach assigned average B₁ better brainstorming C₁ cake calculated COLUMN FACTORS combination computed concept confidence interval confidence level contribution cost Current degrees of freedom described DESCRIPTION desired determine deviation engineering error estimate Example expected experiment experimental expressed Figure four identified improve included indicates influence interaction involved LEVEL 1 LEVEL level column level factors limits loss function main effects manufacturer mean measured noise factors Note objective Observation obtained optimum condition Orthogonal Arrays parameters PERCENT performance pooled possible presented procedure quality characteristic reduce repetitions represents response S/N ratio sample selected shown in Table significant smaller standard steps structure sum of squares Supplier Taguchi target value term tolerance trial conditions TRIAL NUMBER trial runs unit variables variance variation
Popüler pasajlar
Sayfa 7 - ... money was expended in engineering experimentation and testing. Little emphasis was given to the process of creative brainstorming to minimize the expenditure of resources. Dr. Taguchi started to develop new methods to optimize the process of engineering experimentation. He developed techniques that are now known as the Taguchi Methods. His greatest contribution lies not in the mathematical formulation of the design of experiments, but rather in the accompanying philosophy. His approach is more...
Sayfa 8 - Reproduced by permission. approach is more than a method to lay out experiments. His is a concept that has produced a unique and powerful quality improvement discipline that differs from traditional practices. These concepts are: 1 . Quality should be designed into the product and not inspected into it. 2. Quality is best achieved by minimizing the deviation from a target. The product should be so designed that it is immune to uncontrollable environmental factors. 3 . The cost of quality should be...
Sayfa 42 - ... theater use music to support the action on stage and to help create mood. Music also helps to create atmosphere in films and many television programs. Music has its own written language, or score, made up of symbols and notes. Different musical notes are used to indicate the length of a sound. Notes are represented by the letters A, B, C, D, E, F, and G. These letters or notes are marked on a stave, which is a set of five parallel lines. The position of a note on the stave indicates whether the...
Sayfa 145 - The change in the quality characteristics of a product under investigation, in response to a factor introduced in the experimental design is the "signal" of the desired effect. However, when an experiment is conducted, there are numerous external factors not designed into the experiment which influence the outcome. These external factors are called the noise factors and their effect on the outcome of the quality characteristic under test is termed "the noise.
Sayfa 1 - The technique of defining and investigating all possible conditions in an experiment involving multiple factors is known as the design of experiments.
Sayfa 101 - Sum of squares. The sum of squares is a measure of the deviation of the experimental data from the mean value of the data. Summing each squared deviation emphasizes the total deviation. Tbus where: Khar is the average of Y s. = S
Sayfa 10 - Taguchi divides quality control efforts into two categories: on-line quality control and off-line quality control. On-line quality control involves diagnosis and adjustment of the process, forecasting and correction of problems, inspection and disposition of product, and follow-up...
Sayfa 10 - While system design helps to identify the working levels of the design factors, parameter design seeks to determine the factor levels that produce the best performance of the product/process under study. The optimum condition is selected so that the influence of the uncontrolled factors (noise factors) causes minimum variation of system performance.
Sayfa 145 - The signal to noise ratio (S/N ratio) measures the sensitivity of the quality characteristic being investigated in a controlled manner, to those external influencing factors (noise factors) not under control. The concept of S/N originated in the electrical engineering field.