Makespan estimation in batch process industries using aggregate resource and job set charateristics

To properly conduct aggregate control functions such as order acceptance and capacity loading, good estimates of the available production capacity need to be on hand. Capacity structures in batch process industries are generally so complex that it is not straightforward to estimate the capacity of a production department. In this paper, we assess the quality of estimation models that are based on regression. The paper builds on earlier results, which have demonstrated that a limited number of factors can explain a large share of the variance in makespan estimation based on regression models.