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      Full Scale Plant Optimization in Chemical Engineering

      A Practical Guide

      AvZivorad R. Lazic

      Inbunden, Engelska, 2022

      1 549 kr

      Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

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      E-bok

      1 690 kr

      E-bok

      1 673 kr

      Beskrivning

      Full Scale Plant Optimization in Chemical Engineering Highlights the basic principles and applications of the primary three methods in plant and process optimization for responsible operators and engineers. Chemical engineers are a vital part of the creation of any process development—lab-scale and pilot-scale—for any plant. In fact, they are the lynchpin of later efforts to scale-up and full-scale plant process improvement. As these engineers approach a new project, there are three generally recognized methodologies that are applicable in industry generally: Design of Experiments (DOE), Evolutionary Operations (EVOP), and Data Mining Using Neural Networks (DM). In Full Scale Plant Optimization in Chemical Engineering, experienced chemical engineer Živorad R. Laziċ offers an in-depth analysis and comparison of these three methods in full-scale plant optimization applications. The book is designed to provide the basic principles and necessary information for complete understanding of these three methods (DOE, EVOP, and DM). The application of each method is fully described. Full Scale Plant Optimization in Chemical Engineering readers will also find: A thorough discussion of the advantages, disadvantages and applications for the five different EVOP methods (BEVOP, ROVOP, REVOP, QSEVOP & SEVOP) with examples and simulations An overview of EVOP tools that responsible operators and engineers utilize in deciding which EVOP method is the most appropriate for the certain type of the process Particular attention is given to the simple but powerful technique Evolutionary Operation or EVOP, which provides the experimental tools for the full scale plant optimizationFull Scale Plant Optimization in Chemical Engineering is a useful reference for all chemists in industry, chemical engineers, pharmaceutical chemists, and process engineers.

      Produktinformation

      • Utgivningsdatum:2022-07-06
      • Mått:170 x 244 x 19 mm
      • Vikt:680 g
      • Format:Inbunden
      • Språk:Engelska
      • Antal sidor:272
      • Förlag:Wiley-VCH Verlag GmbH
      • ISBN:9783527350384

      Utforska kategorier

      • Kemi inom Naturvetenskap och teknik
      • Tillverkningsteknik inom Naturvetenskap och teknik
      • Byggnadsteknik inom Naturvetenskap och teknik

      Mer om författaren

      Živorad R. Laziċ is the author of “Design of Experiments in Chemical Engineering: A Practical Guide”, published by J. Wiley in January 2004. He has produced a unique, “how to do it”, a practical guide for the statistical design of experiments. It is the ideal book for the industrial scientist or engineer who wants to take an advantage of DOE techniques without becoming a statistician. Basic statistical ideas are presented clearly and simply with numerous examples. This is one of the few books that are practically suited for self-study by a busy technologist, engineers and scientists. He is a Certified Six-Sigma Black Belt professional with interests in advanced statistical tools, Design of Experiments(DOE), Statistical Process Control(SPC), Evolutionary Operation(EVOP) and process modeling via application of neural networks.

      Innehållsförteckning

      • Preface ixBiography xii1 The Basic Ideas 11.1 Introduction 12 Design of Experiments – DOE 32.1 The 2 2 Factorial Designs 42.2 Effects for 2 2 Factorial Designs 62.3 Interactions Between Factors 62.4 Standard Error for the Effects 72.5 2 3 Factorial Design 72.6 Effects for the 2 3 Factorial Designs 92.7 Standard Errors of Effects for Two- and Three-Level Factorial Designs 103 Neural Network Modeling – Data Mining 173.1 Data Preprocessing 183.2 Building, Training, and Verifying Model 193.3 Model Analyzing 213.4 What-Ifs Optimization 253.5 DOE Experiment Using Neural Networks Model 264 Evolutionary Operation – EVOP 294.1 Small-Scale and Plant-Scale Investigation 294.2 Scale-up 294.3 Static and Evolutionary Operation 304.4 Analysis of Information Board 344.5 Three-Factor Scheme 354.6 Current Best-Known Conditions 364.7 Change in Mean for a 2 2 Factorial Design with Center Point 384.8 Standard Errors for the Effects 384.9 The Effects and Their Standard Errors for a 2 2 Design with Center Point 404.10 Analysis of Information Board for Three Responses Using Factorial Effects 404.11 2 3 Factorial Design Effects, Interpretation, and Information Board 414.11.1 An Estimate of Standard Deviation 434.12 Dividing the 2 3 Factorial Design Into Two Blocks 454.13 2 3 Design with Two Center Points Run in Two Blocks 454.13.1 Two Standard Error Limits for the Overall Change in Mean 465 Different Techniques of EVOP 495.1 Box EVOP – BEVOP 495.2 Calculation Procedure for Two-Factor EVOP 505.3 Calculation Procedure for Three-Factor EVOP 545.4 BEVOP in Plant-Scale Experiments 935.5 BEVOP Applications 965.6 BEVOP Advantages and Disadvantages 995.7 BEVOP Simulation 1005.7.1 2 2 BEVOP Simulation 1005.7.1.1 Simulation No. 1 1005.7.1.2 Simulation No. 2: 2 2 BEVOP 1175.7.1.3 Simulation No. 3: 2 2 BEVOP 1275.7.2 2 3 BEVOP Simulation 1345.7.2.1 Simulation No. 4 1345.8 Rotating Square Evolutionary Operation – ROVOP 1555.8.1 2 2 Rovop 1555.8.2 Method of Analysis 1575.8.3 2 2 ROVOP Simulation 1585.8.3.1 Simulation No. 5 1585.8.4 2 3 ROVOP Simulation 1855.8.4.1 Simulation No. 6: 2 3 ROVOP 1865.9 Random Evolutionary Operation – REVOP 1985.9.1 REVOP Simulation 2005.9.1.1 Simulation No. 7 2005.10 Quick-Start EVOP – QSEVOP 2045.10.1 The way QSEVOP works 2045.10.2 How to Recover From “Hang-ups” 2075.11 QSEVOP Simulation 2085.11.1 Simulation No. 8 2085.12 Simplex Evolutionary Operation – SEVOP 2145.12.1 The Basic Simplex Method 2145.12.2 Simplex Evolutionary Operation – SEVOP 2235.12.3 SEVOP Simulation 2285.12.3.1 Simulation S-9 2285.12.3.2 Simulation S-10 2315.13 Some Practical Advice About Using EVOP 2336 EVOP Software 235Appendix A The Approximate Method of Estimating the Standard Deviation in EVOP 237Appendix B 2 2 -and2 3 -Factor Box EVOP Calculations with Center Point 239Appendix C Short Table of Random Normal Deviates 243Appendix d How Many Cycles Are Necessary to Detect Effects of Reasonable Size 245Appendix E Multiple Responses: The Desirability Approach 247References 253Index 257
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