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Probabilistic design for optimization and robustness for engineers /

Probabilistic Design for Optimization and Robustness: Presents the theory of modeling with variation using physical models and methods for practical applications on designs more insensitive to variation. Provides a comprehensive guide to optimization and robustness for probabilistic design. Features...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Dodson, Bryan, 1962-
Otros Autores: Hammett, Patrick C., Klerx, Rene
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Chichester, West Sussex, United Kingdom : John Wiley & Sons, [2014]
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Dodson, Bryan,  |d 1962- 
245 1 0 |a Probabilistic design for optimization and robustness for engineers /  |c Bryan Dodson, Patrick C. Hammett, Rene Klerx. 
264 1 |a Chichester, West Sussex, United Kingdom :  |b John Wiley & Sons,  |c [2014] 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
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338 |a online resource  |b nc  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record and CIP data provided by publisher. 
505 0 |a Probabilistic Design for Optimization and Robustness for Engineers; Contents; Preface; Acknowledgments; 1 New product development process; 1.1 Introduction; 1.2 Phases of new product development; 1.2.1 Phase I-concept planning; 1.2.2 Phase II-product planning; 1.2.3 Phase III-product engineering design and verification; 1.2.4 Phase IV-process engineering; 1.2.5 Phase V-manufacturing validation and ramp-up; 1.3 Patterns of new product development; 1.4 New product development and Design for Six Sigma; 1.4.1 DfSS core objectives; 1.4.2 DfSS methodology; 1.4.3 Embedded DfSS; 1.5 Summary. 
505 8 |a Exercises2 Statistical background for engineering design; 2.1 Expectation; 2.2 Statistical distributions; 2.2.1 Normal distribution; 2.2.2 Lognormal distribution; 2.2.3 Weibull distribution; 2.2.4 Exponential distribution; 2.3 Probability plotting; 2.3.1 Probability plotting-lognormal distribution; 2.3.2 Probability plotting-normal distribution; 2.3.3 Probability plotting-Weibull distribution; 2.3.4 Probability plotting-exponential distribution; 2.3.5 Probability plotting with confidence limits; 2.4 Summary; Exercises; 3 Introduction to variation in engineering design. 
505 8 |a 3.1 Variation in engineering design3.2 Propagation of error; 3.3 Protecting designs against variation; 3.4 Estimates of means and variances of functions of several variables; 3.5 Statistical bias; 3.6 Robustness; 3.7 Summary; Exercises; 4 Monte Carlo simulation; 4.1 Determining variation of the inputs; 4.2 Random number generators; 4.3 Validation; 4.4 Stratified sampling; 4.5 Summary; Exercises; 5 Modeling variation of complex systems; 5.1 Approximating the mean, bias, and variance; 5.2 Estimating the parameters of non-normal distributions. 
505 8 |a 5.3 Limitations of first-order Taylor series approximation for variance5.4 Effect of non-normal input distributions; 5.5 Nonconstant input standard deviation; 5.6 Summary; Exercises; 6 Desirability; 6.1 Introduction; 6.2 Requirements and scorecards; 6.2.1 Types of requirements; 6.2.2 Design scorecard; 6.3 Desirability-single requirement; 6.3.1 Desirability-one-sided limit; 6.3.2 Desirability-two-sided limit; 6.3.3 Desirability-nonlinear function; 6.4 Desirability-multiple requirements; 6.4.1 Maxi-min total desirability index; 6.5 Desirability-accounting for variation. 
505 8 |a 6.5.1 Determining desirability-using expected yields6.5.2 Determining desirability-using non-mean responses; 6.6 Summary; Exercises; 7 Optimization and sensitivity; 7.1 Optimization procedure; 7.2 Statistical outliers; 7.3 Process capability; 7.4 Sensitivity and cost reduction; 7.4.1 Reservoir flow example; 7.4.2 Reservoir flow initial solution; 7.4.3 Reservoir flow initial solution verification; 7.4.4 Reservoir flow optimized with normal horsepower distribution; 7.4.5 Reservoir flow optimized with normal horsepower distribution verification. 
520 |a Probabilistic Design for Optimization and Robustness: Presents the theory of modeling with variation using physical models and methods for practical applications on designs more insensitive to variation. Provides a comprehensive guide to optimization and robustness for probabilistic design. Features examples, case studies and exercises throughout. The methods presented can be applied to a wide range of disciplines such as mechanics, electrics, chemistry, aerospace, industry and engineering. This text is supported by an accompanying website featu. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Industrial design  |x Statistical methods. 
650 0 |a Reliability (Engineering) 
650 0 |a Robust statistics. 
650 6 |a Design  |x Méthodes statistiques. 
650 6 |a Fiabilité. 
650 6 |a Statistiques robustes. 
650 7 |a TECHNOLOGY & ENGINEERING  |x Engineering (General)  |2 bisacsh 
650 7 |a TECHNOLOGY & ENGINEERING  |x Reference.  |2 bisacsh 
650 7 |a Reliability (Engineering)  |2 fast  |0 (OCoLC)fst01093646 
650 7 |a Robust statistics.  |2 fast  |0 (OCoLC)fst01099111 
650 7 |a Mechanical Engineering.  |2 hilcc 
650 7 |a Engineering & Applied Sciences.  |2 hilcc 
650 7 |a Industrial & Management Engineering.  |2 hilcc 
700 1 |a Hammett, Patrick C. 
700 1 |a Klerx, Rene. 
776 0 8 |i Print version:  |a Dodson, Bryan, 1962-  |t Probabilistic design for optimization and robustness for engineers.  |d Chichester, West Sussex, United Kingdom : John Wiley & Sons, [2014]  |z 9781118796191  |w (DLC) 2014013950 
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