This paper considers a complex scheduling problem in the chemical process industry involving batch production. The application described comprises a network of production plants with interdependent production schedules, multi-stage production at multi-purpose facilities, and chain production. The paper addresses three distinct aspects: (i) a scheduling solution obtained from a genetic algorithm based optimizer, (ii) a mechanism for collaborative planning among the involved plants, and (iii) a tool for manual updates and schedule changes. The tailor made optimization algorithm simultaneously considers alternative production paths and facility selection as well as product and resource specific parameters such as batch sizes, and setup and cleanup times. The collaborative planning concept allows all the plants to work simultaneously as partners in a supply chain resulting in higher transparency, greater flexibility, and reduced response time as a whole. The user interface supports monitoring production schedules graphically and provides custom-built utilities for manual changes to the production schedule, investigation of various what-if scenarios, and marketing queries.
Berning G, Brandenburg M, Gürsoy K, Mehta V, Tölle F-J. An integrated system solution for supply chain optimization in the chemical process industry. 2002;24(4):371-401, . doi:10.1007/s00291-002-0104-4.
(2002). An integrated system solution for supply chain optimization in the chemical process industry, 24(4), 371-401, . http://doi.org/10.1007/s00291-002-0104-4 (Original work published 2002 November 01 ).
Berning, Guido, Marcus Brandenburg, Korhan Gürsoy, Vipul Mehta, und Franz-Josef Tölle. (01 ) 2002. „An Integrated System Solution For Supply Chain Optimization In The Chemical Process Industry“ 24 (4): 371-401, . doi:10.1007/s00291-002-0104-4.
Berning, Guido u. a. „An Integrated System Solution For Supply Chain Optimization In The Chemical Process Industry“. 24.4 (2002): 371-401, .
An Integrated System Solution For Supply Chain Optimization In The Chemical Process Industry. 01 2002, S. 371-401, ..
Number of Pages371-401,