Buch, Englisch, 462 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 727 g
Reihe: International Series in Operations Research & Management Science
A Statistical Approach
Buch, Englisch, 462 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 727 g
Reihe: International Series in Operations Research & Management Science
ISBN: 978-1-4419-4396-5
Verlag: Springer US
This book is an ideal textbook for a second course in experimental optimization techniques for industrial production processes. In addition, it is a superb reference volume for use by professors and graduate students in Industrial Engineering and Statistics departments. It will also be of huge interest to applied statisticians, process engineers, and quality engineers working in the electronics and biotech manufacturing industries. In all, it provides an in-depth presentation of the statistical issues that arise in optimization problems, including, amongst other things, confidence regions on the optimal settings of a process and stopping rules in experimental optimization. It presents a detailed treatment of Bayesian Optimization approaches. It contains a mix of technical and practical sections, appropriate for a first year graduate text in the subject or useful for self-study or reference.
Zielgruppe
Graduate
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
- Geisteswissenschaften Design Produktdesign, Industriedesign
- Mathematik | Informatik Mathematik Operations Research Spieltheorie
- Technische Wissenschaften Technik Allgemein Technische Zuverlässigkeit, Sicherheitstechnik
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Industrielle Qualitätskontrolle
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
- Technische Wissenschaften Technik Allgemein Konstruktionslehre und -technik
Weitere Infos & Material
Preliminaries.- 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.
