An integrated system solution for supply chain optimisation in the chemical process industry

We consider a complex scheduling problem in the chemical process industry involving batch pro-duction. 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 al-gorithm 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 speci¯c parameters such as batch sizes, and setup and cleanup times. The collabora-tive planning concept allows all the plants to work simultaneously as partners in a supply chain resulting in higher transparency, greater °exibility, 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