Developing cost-optimization production control model via simulation

This research is a further development of our recent papers [2, 3]. A production system produces a given target amount by a given due date and has several possible speeds which are subject to random disturbances. The system's output can be measured only at present inspection (control) points. The average manufacturing costs per time unit for each production speed and the average cost of performing a single inspection at the control point to observe the actual output at that point, are given. The least permissible probability of meeting the target on time, i.e. the system's chance constraint, is pre-given too. The problem is to determine both, control points and speeds to be introduced at those points, in order to minimize the system's expenses within the planning horizon. A stochastic optimization problem is formulated, followed by a heuristic solution via simulation. A numerical example is given. Extensive experimentation has been undertaken to illustrate the efficiency of the presented algorithm. The algorithm has been used in practice on a real man–machine plant.