04939oam 2200685Mu 450 991025495810332120191114074228.03-319-42258-810.1007/978-3-319-42258-9(CKB)3710000000909090(DE-He213)978-3-319-42258-9(MiAaPQ)EBC5577363(OCoLC)966104210(OCoLC-P)966104210(FlBoTFG)9780429116902(PPN)228320135(EXLCZ)99371000000090909020161208d2016 uy 0engur|n|||||||||txtrdacontentcrdamediacrrdacarrierIntroduction to Process Control /Victor A. Skormin1st ed. 2016.[Place of publication not identified]Springer International Publishing Switzerland20161 online resource (XVII, 254 p. 106 illus., 50 illus. in color.)Springer Texts in Business and Economics,2192-4333Title from content provider.3-319-42257-X Includes bibliographical references and index.Statistical Methods and their Applications -- Mathematical Description of Manufacturing Processes -- Computer Control of Manufacturing Processes -- Methods and Models of Optimazation. .This textbook is intended for an introductory graduate level on process control, taught in most engineering curricula. It focuses on the statistical techniques and methods of control and system optimization needed for the mathematical modeling, analysis, simulation, control and optimization of multivariable manufacturing processes. In four sections, it covers: Relevant mathematical methods, including random events, variables and processes, and their characteristics; estimation and confidence intervals; Bayes applications; correlation and regression analysis; statistical cluster analysis; and singular value decomposition for classification applications. Mathematical description of manufacturing processes, including static and dynamic models; model validation; confidence intervals for model parameters; principal component analysis; conventional and recursive least squares procedures; nonlinear least squares; and continuous-time, discrete-time, s-domain and Z-domain models. Control of manufacturing processes, including transfer function/transfer matrix models; state-variable models; methods of discrete-time classical control; state variable discrete-time control; state observers/estimators in control systems; methods of decoupling control; and methods of adaptive control. Methods and applications of system optimization, including unconstrained and constrained optimization; analytical and numerical optimization procedures; use of penalty functions; methods of linear programming; gradient methods; direct search methods; genetic optimization; methods and applications of dynamic programming; and applications to estimation, design, control, and planning. Each section of the book will include end-of-chapter exercises, and the book will be suitable for any systems, electrical, chemical, or industrial engineering program, as it focuses on the processes themselves, and not on the product being manufactured. Students will be able to obtain a mathematical model of any manufacturing process, to design a computer-based control system for a particular continuous manufacturing process, and be able to formulate an engineering problem in terms of optimization, as well as the ability to choose and apply the appropriate optimization technique.Springer Texts in Business and Economics,2192-4333Operations researchDecision makingManagement information systemsIndustrial managementIndustrial engineeringProduction engineeringOperations Research/Decision Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/521000Business Process Managementhttps://scigraph.springernature.com/ontologies/product-market-codes/522020Industrial and Production Engineeringhttps://scigraph.springernature.com/ontologies/product-market-codes/T22008Operations research.Decision making.Management information systems.Industrial management.Industrial engineering.Production engineering.Operations Research/Decision Theory.Business Process Management.Industrial and Production Engineering.658.40301Skormin Victor A980124OCoLC-POCoLC-PBOOK9910254958103321Introduction to Process Control2235686UNINA