The slab yard upstream of a heating furnace in a steel factory has several LIFO buffers and a crane. In managing the yard, slabs are moved from a buffer to another and to the furnace by the crane. Which specific operation should be done and when are determined by the crane operator according to the situation being dynamically changed with arrivals of new slabs to the yard and removals of heated slabs from the furnace. This study models a mathematical aspect of the dynamic decision process for managing the yard, and analyzes the effects of some factors on its performance using a reinforcement learning agent. As a result, it reveals an interaction effect between the arrival rate of slabs and how many steps in the future the agent considers when making decision. The findings obtained by this and similar following studies will be valuable for supporting the actual decision process and for training skills for the process.