000 04966nam a22005175i 4500
001 978-0-387-71435-6
003 DE-He213
005 20250710084012.0
007 cr nn 008mamaa
008 100301s2007 xxu| s |||| 0|eng d
020 _a9780387714356
_a99780387714356
024 7 _a10.1007/978-0-387-71435-6
_2doi
082 0 4 _a519.5
_223
100 1 _aCastillo, Enrique Del.
_eauthor.
245 1 0 _aProcess Optimization
_h[recurso electrónico] :
_bA Statistical Approach /
_cby Enrique Del Castillo.
264 1 _aBoston, MA :
_bSpringer US,
_c2007.
300 _bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v105
505 0 _aPreliminaries -- An Overview of Empirical Process Optimization -- Elements of Response Surface Methods -- Optimization Of First Order Models -- Experimental Designs For First Order Models -- Analysis and Optimization of Second Order Models -- Experimental Designs for Second Order Models -- Statistical Inference in Process Optimization -- Statistical Inference in First Order RSM Optimization -- Statistical Inference in Second Order RSM Optimization -- Bias Vs. Variance -- Robust Parameter Design and Robust Optimization -- Robust Parameter Design -- Robust Optimization -- Bayesian Approaches in Process Optimization -- to Bayesian Inference -- Bayesian Methods for Process Optimization -- to Optimization of Simulation and Computer Models -- Simulation Optimization -- Kriging and Computer Experiments -- Appendices -- Basics of Linear Regression -- Analysis of Variance -- Matrix Algebra and Optimization Results -- Some Probability Results Used in Bayesian Inference.
520 _aPROCESS OPTIMIZATION: A Statistical Approach is a textbook for a course in experimental optimization techniques for industrial production processes and other "noisy" systems where the main emphasis is process optimization. The book can also be used as a reference text by Industrial, Quality and Process Engineers and Applied Statisticians working in industry, in particular, in semiconductor/electronics manufacturing and in biotech manufacturing industries. The major features of PROCESS OPTIMIZATION: A Statistical Approach are: It provides a complete exposition of mainstream experimental design techniques, including designs for first and second order models, response surface and optimal designs; Discusses mainstream response surface method in detail, including unconstrained and constrained (i.e., ridge analysis and dual and multiple response) approaches; Includes an extensive discussion of Robust Parameter Design (RPD) problems, including experimental design issues such as Split Plot designs and recent optimization approaches used for RPD; Presents a detailed treatment of Bayesian Optimization approaches based on experimental data (including an introduction to Bayesian inference), including single and multiple response optimization and model robust optimization; Provides an in-depth presentation of the statistical issues that arise in optimization problems, including confidence regions on the optimal settings of a process, stopping rules in experimental optimization and more; Contains a discussion on robust optimization methods as used in mathematical programming and their application in response surface optimization; Offers software programs written in MATLAB and MAPLE to implement Bayesian and frequentist process optimization methods; Provides an introduction to the optimization of computer and simulation experiments including and introduction to stochastic approximation and stochastic perturbation stochastic approximation (SPSA) methods; Includes an introduction to Kriging methods and experimental design for computer experiments; Provides extensive appendices on Linear Regression, ANOVA, and Optimization Results.
650 0 _aENGINEERING.
650 0 _aMATHEMATICAL OPTIMIZATION.
650 0 _aSTATISTICS.
650 0 _aMATHEMATICAL STATISTICS.
650 0 _aENGINEERING DESIGN.
650 0 _aSYSTEM SAFETY.
650 1 4 _aENGINEERING.
650 2 4 _aSTATISTICAL THEORY AND METHODS.
650 2 4 _aQUALITY CONTROL, RELIABILITY, SAFETY AND RISK.
650 2 4 _aSTATISTICS, GENERAL.
650 2 4 _aMATHEMATICAL MODELING AND INDUSTRIAL MATHEMATICS.
650 2 4 _aENGINEERING DESIGN.
650 2 4 _aOPTIMIZATION.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387714349
830 0 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v105
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-387-71435-6
_zVer el texto completo en las instalaciones del CICY
912 _aZDB-2-SBE
942 _2ddc
_cER
999 _c58247
_d58247