Premium
Simulation and Data Analytics in the Conceptual Design of Industrial Networks in Stochastic Environments
Author(s) -
Wagner Henning,
Ruoshan Wei Sophie
Publication year - 2018
Publication title -
chemie ingenieur technik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 36
eISSN - 1522-2640
pISSN - 0009-286X
DOI - 10.1002/cite.201800033
Subject(s) - interdependence , analytics , computer science , process (computing) , conceptual design , industrial engineering , stochastic modelling , systems engineering , engineering , data science , statistics , mathematics , human–computer interaction , political science , law , operating system
The cross‐linking of industrial processes and plants is gaining great importance. The project Carbon2Chem® deals with industrial networks in a stochastic environment with volatilely available resources. Thus, processes in the networks must be designed for discontinuous operation, and design challenges arise due to complex dynamic interdependencies within the system. Here, a V‐model based framework for the conceptual design of industrial networks is presented, which integrates simulation and data analytics methods for a hierarchical derivation of stochastic boundary conditions on different levels of process integration. This framework is applied to study the utilization of steel mill gases for methanol synthesis in a stochastic dynamic environment.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom