Theory of Constraints Handbook - James Cox Iii [185]
The idea is that both the amount of time an item spends in the red and the depth into the red are relevant signals to increase the buffer. The algorithm that emerges is that every time there is a penetration into the red, the depth of the penetration, expressed by the number of item units below the red level, is recorded. If within the time frame of the replenishment time the summation of all the recorded penetrations is equal to or greater than the size of the red level, then a recommendation to increase the buffer is given. In other words, if during the span of the replenishment period the penetration of red equals the entire size of the red buffer, it is time to increase the buffer size.
Once the target level has been increased, the specific item will definitely be in the red. The increase in the target causes a new replenishment production order to be released. It certainly will take time before the new buffer size will be stabilized. Before that, there is no sense in deciding to increase the buffer again. The point here is to refrain from hasty decisions until the impact of the previous increase has been noted.11 Thus, the algorithm calls for a “cooling period” where no re-evaluation of the penetration into the red would be done. The natural time for the cooling period is one replenishment time. Therefore, it takes one replenishment time to possibly discover the buffer should be increased and another period of replenishment time until such a check should start again.
Discussion: Issues with DBM and by How Much to Increase/Decrease the Targets
The first topic in this discussion has been by how much to increase/decrease the buffer. From this question, some additional questions might be raised, such as what are the immediate ramifications for such a change, and due to them when should such changes be avoided? Shouldn’t the increase of the buffer be subject to a forecast, which predicts how much the demand would grow?
In practice, the sales of one item at a specific location are too chaotic to truly support a good prediction of the quantity. However, the trend of the sales can be predicted, so we should know whether we need to increase or decrease the buffer, and decide rather arbitrarily about the size of the change.
We discuss here the behavior of sales from the manufacturer’s viewpoint. In other words, wild fluctuations are less common at the manufacturer’s level than at a specific store. The question is whether we’d have a better answer for the manufacturer than the arbitrary guideline that says whenever a clear signal is noted that the buffer is not adequate, change the buffer by 33 percent or any other fixed ratio that seems appropriate.
Note that the BM signal is impacted by the combination of demand and supply. When the demand goes up, the idle capacity decreases and the replenishment time gets longer. Do we know how that is going to affect the right size of the buffer?
This author’s inclination is to accept the premise of having an arbitrary number for buffer increase or decrease. However, for the shop floor a decision to increase the buffer by 33 percent looks to this author like it creates too many waves in the general flow. A buffer increase of 20 percent and a buffer decrease of 15 percent look more appropriate for the shop floor. The demand from a manufacturer usually has much less fluctuation than the sales of a store, and thus the changes in the buffers could be smaller and still be able to match the trends.
Another question is what are the appropriate conditions for increasing a buffer? When the buffer is increased, the whole amount of the increase is released to the shop floor as one production order. This relatively large production order comes on top of the regular replenishments that are following the actual demand. If the current load on the CCR is high, then the last action we should take is to release