About: Process optimization is a research topic. Over the lifetime, 2266 publications have been published within this topic receiving 30258 citations.
Papers published on a yearly basis
01 Jan 2002
TL;DR: In this article, the authors present essential flow diagrams for understanding processes, including the structure of Chemical Process Flow Diagrams, and tools for evaluating system performance and performance curves for individual unit operations.
Abstract: 1 Essential Flow Diagrams for Understanding Processes I ENGINEERING ECONOMIC ANALYSIS OF CHEMICAL PROCESSES 2 Estimation of Capital Costs 3 Estimation of Manufacturing Costs 4 Engineering Economic Analysis 5 Profitability Analysis II TECHNICAL ANALYSIS OF A CHEMICAL PROCESS 6 Structure of Chemical Process Flow Diagrams 7 Tracing Chemicals Through the Process Flow Diagram 8 Understanding Process Conditions 9 Utilizing Experience-Based Principles to Confirm the Suitability of a Process Design III ANALYSIS OF SYSTEM PERFORMANCE 10 Process Input/Output Models 11 Tools for Evaluating System Performance 12 Performance Curves for Individual Unit Operations 13 Performance of Multiple Unit Operations 14 Reactor Performance 15 Regulating Process Conditions 16 Process Troubleshooting and Debottlenecking IV SYNTHESIS AND OPTIMIZATION OF A PROCESS FLOW DIAGRAM 17 Synthesis of the PFD from the Generic BFD 18 Synthesis of a Process Using a Simulator and Simulator Troubleshooting 19 Process Optimization V THE PROFESSIONAL ENGINEER, THE ENVIRONMENT, AND COMMUNICATIONS 20 Ethics and Professionalism 21 Health, Safety, and the Environment 22 Written and Oral Communications 23 A Report Writing Case Study APPENDICES Appendix A Cost Equations and Curves for the CAPCOSTA(c) Program Appendix B Information for the Preliminary Design of Four Chemical Processes Appendix C Design Projects Index
14 Oct 2010
TL;DR: The author provides a firm grounding in fundamental NLP properties and algorithms, and relates them to real-world problem classes in process optimization, thus making the material understandable and useful to chemical engineers and experts in mathematical optimization.
Abstract: This book addresses modern nonlinear programming (NLP) concepts and algorithms, especially as they apply to challenging applications in chemical process engineering. The author provides a firm grounding in fundamental NLP properties and algorithms, and relates them to real-world problem classes in process optimization, thus making the material understandable and useful to chemical engineers and experts in mathematical optimization. Nonlinear Programming: Concepts, Algorithms, and Applications to Chemical Processes shows readers which NLP methods are best suited for specific applications, how large-scale problems should be formulated and what features of these problems should be emphasized, and how existing NLP methods can be extended to exploit specific structures of large-scale optimization models. Audience: The book is intended for chemical engineers interested in using NLP algorithms for specific applications, experts in mathematical optimization who want to understand process engineering problems and develop better approaches to solving them, and researchers from both fields interested in developing better methods and problem formulations for challenging engineering problems. Contents: Preface; Chapter 1: Introduction to Process Optimization; Chapter 2: Concepts of Unconstrained Optimization; Chapter 3: Newton-Type Methods for Unconstrained Optimization; Chapter 4: Concepts of Constrained Optimization; Chapter 5: Newton Methods for Equality Constrained Optimization; Chapter 6: Numerical Algorithms for Constrained Optimization; Chapter 7: Steady State Process Optimization; Chapter 8: Introduction to Dynamic Process Optimization; Chapter 9: Dynamic Optimization Methods with Embedded DAE Solvers; Chapter 10: Simultaneous Methods for Dynamic Optimization; Chapter 11: Process Optimization with Complementarity Constraints; Bibliography; Index
TL;DR: An improved algorithm for simultaneous strategies for dynamic optimization based on interior point methods is developed and a reliable and efficient algorithm to adjust elements to track optimal control profile breakpoints and to ensure accurate state and control profiles is developed.
TL;DR: A procedure is proposed for simultaneously handling the problem of optimal heat integration while performing the optimization of process flow sheets so as to insure that the minimum utility target for heat recovery networks is featured.
Abstract: A procedure is proposed for simultaneously handling the problem of optimal heat integration while performing the optimization of process flow sheets. The method is based on including a set of constraints into the nonlinear process optimization problem so as to insure that the minimum utility target for heat recovery networks is featured. These heat integration constraints, which do not require temperature intervals for their definition, are based on a proposed representation for locating pinch points that can vary according to every set of process stream conditions (flow rates and temperatures) selected in the optimization path. The underlying mathematical formulations correspond to nondifferentiable optimization problems, and an efficient smooth approximation method is proposed for their solution. An example problem on a chemical process is presented to illustrate the economic savings that can be obtained with the proposed simultaneous approach. The method reduces to simple models for the case of fixed flow rates and temperatures.
TL;DR: In this paper, a study has been made to optimize the process parameters of powder mixed electrical discharge machining (PMEDM), and the results identify the most important parameters to maximize material removal rate and minimize surface roughness.
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