We can put p 1 and p 2 in cells, and have all the calculations refer to those cells. Then as we vary the values of those cells, we can dynamically see the effect in operational readiness rate. If the previous day was low, the next day tends to be low, as well. If the previous day was high, the next day tends to be high. This type of pictorial representation of a stochastic discrete system is very useful to demonstrate the properties of a maintenance system to a commander.
Pictures tell stories that mere numbers often fail to convey.
The picture of the Markov chain model shows only the long-term trend of the average number of tanks. These pictures from the simulation show both the long-term average and the variability. The randomness remains. We may never know them exactly. The best we can hope to do is to estimate them from historical data.