A ROUGH-CUT COST ESTIMATION IN A FINITE-CAPACITY STOCHASTIC ENVIRONMENT BASED ON FORCED IDLE TIME PREDICTION

摘要

In recent years several researchers suggested cost estimation models that consider the limited capacity of the shop. In these studies, the stochastic nature of the shop floor is modeled by a time-consuming simulation. This paper proposes five alternative rough-cut cost estimation methods that can replace the simulation. Three of five methods based on forced idle time prediction. The study compares the cost estimations derived from these methods. A cost estimation method, based on the forced idle time of the bottleneck workstation, was found to be outperform the others. As the best method, the bottleneck-based method was compared to the actual order's cost and was found as a replacement to simulation.