Logistic Optimization of Chemical Production Processes
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.
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2S-MILP allocation applied approach assignment automata batch plants batch processes batch scheduling batch sizes branch and bound bullwhip effect calculated campaign capacity changeover Chem chemical combinatorial optimization complex computational constraints continuous-time copper corresponding costs CPLEX decisions defined demand density discrete due dates equipment ERP system evolution strategy evolutionary algorithm example feasible Figure finishing first-stage formulation Gantt chart industry integration intervals inventory logistics lot sizes makespan material flow MILP mixed-integer mixing vessels multipurpose batch nodes objective function ofthe operations orders parameters performance period pipeless plant planning horizon polymerization stage PP/DS production planning production process quantity quants random demand raw materials reachability recipes requirements resource SAP R/3 scenario scheduling problem second-stage Section sequence setup short-term scheduling simulation SNP optimizer SNP planning solution solved stations steps stochastic program storage Supply Chain Management tanks tasks two-stage stochastic units variables