Currently, I am researching an approach to integrate scheduling and optimal process operation of batch plants under uncertainty. Common scheduling methods are limited, in a way such that they imply the successful completion of a specific processing recipe, this is not always true. Process uncertainty, is a critical factor that in conjuction with disturbances and fluctuating demand, will impact and effectively null the validity of a schedule. As such, it is important to develop a computationally efficient method, able to integrate the aforementioned factors to generate an optimal schedule, maximizing process revenue, while meeting manufacturing and dynamic constraints under the influence of uncertainty.
Preliminary results show that a multi scenario approach is able to efficiently link process dynamics and scheduling while not being a computationally demanding method.