Logistic Optimization of Chemical Production ProcessesSebastian Engell John Wiley & Sons, 4 Agu 2008 - 298 halaman In this first book dedicated to the logistics of chemical plants and production processes, authors from academia and industry -- such as Bayer, Degussa, Merck -- provide an overview of the field, incorporating the knowledge and experience gathered over the last 10 years. In so doing, they describe the latest ideas on efficient design, illustrating when to produce which part of the equipment and with which resources, so as to optimize chemical plants for high capacity and flexibility. This book gives an overview of the state-of-the-art of the whole logistic chain of chemical production processes. Alongside the fundamentals, tools and algorithms, and integration issues, the book features five significant industrial case studies. |
Isi
Supply Chain and Supply Chain Management | 3 |
Logistics Simulation in the Chemical Industry | 21 |
Logistic Optimization of Chemical Production Processes Edited by Sebastian Engell | 37 |
Planning Large Supply Chain Scenarios with Quantbased | 59 |
WILEYVCH Verlag GmbH Co KGaA Weinheim | 93 |
Stochastic Tools in Supply Chain Management | 111 |
Engineered MixedInteger Programming in Chemical | 137 |
MILP Optimization Models for Shortterm Scheduling | 163 |
Uncertainty Conscious Scheduling by TwoStage Stochastic | 185 |
Scheduling Based on Reachability Analysis of Timed Automata | 215 |
Integrated Short and Midterm Scheduling of Chemical Production | 239 |
Integration of Scheduling with ERP Systems | 263 |
| 279 | |
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additional algorithms allocation amount applied approach assignment assumed basic batch calculated campaign capacity chemical cleaning combination combinatorial optimization complex computational concept considered constraints continuous copper corresponding costs dates decisions defined demand density dependent described detailed discrete distribution equipment example existing feasible Figure finishing flow formulation function given horizon increase industry integrated intervals inventory leads limited linear logistics material maximum means methods MILP mixing necessary needed nodes objective operations optimization orders parameters performance period plant polymerization possible production plan production process programming quant quantity quants random raw materials recipes represented requirements scenario scheduling problem sequence setup shows simulation sizes solution solved specific stage standard starts stations steps stochastic stochastic program storage structure supply chain Table task transportation types units variables vessels