In several posts related to supply chain performance, I have mentioned the need for driving the size of transfer batches down. Transfer batches, here, are to be distinguished from purchasing or pricing batches. As you already know, if you are a regular reader, I am a big advocate of entirely disconnecting pricing and pricing policy from the size of the transfer batches (in this case, shipments between trading partners in the supply chain).
Direct Effects
Some might question just how big an effect changes in the size of transfer batches might make. So, I have set up the simulation below to show the direct effects. After we have discussed the direct effects, we will also talk about some other aspects related to the size of transfer batches.
In the chart above, we start with a single item being manufactured through Work Centers (WCs) 1 through 5. You will note that as the batch size increases (reading down the columns), the processing time (Process Time) remains the same at each Work Center. As do the other times Wait Time and Move Time associated with each Work Center’s processing of the item.
Wait Time is defined as the time a resource spends waiting for a unit of material on which to act. In our example, we are assuming that execution is always “Johnny-on-the-spot.” No matter how large or small the batch size, no resource ever waits more than five minutes for materials regardless of the batch size.
Move Time is defined as the time a unit of material spends being transported from one resource to another. Here again, we assume that nothing ever spends more than five minutes being transported from one resource to another in our fictitious plant.
Queue Time requires a little more definition.
Queue Time is the time a unit of material waits for a resource to act on it. The Queue Time is calculated as
Processing Time * Transfer Batch Qty / 2
This can be explained by seeing it in this way: the first unit in the batch is acted upon right away. It’s Queue Time is zero. The last unit in the transfer batch is completed at time equal to the size of the batch (quantity) times the processing time per unit. The average Queue Time, therefore, is the time it takes to process the entire batch divided by two.
It is Queue Time (QT) that varies with the size of the batch in otherwise idealized scenario above.
Very Small Transfer Batches
Let us start our review of the table above with the first row—the ideal transfer batch size of one.
If we assume that our work centers can be arranged so that, when Work Center 1 completes its processing of a unit, it can just hand it off to Work Center 2; and when Work Center 2 completes its processing, it can hand it off directly to Work Center 3, then we have eliminated both Queue Times and Move Times for all the work centers that are so arranged and coordinated. Even so, we have allowed a full five minutes of Wait Time at each Work Center, just in case Murphy has caused a delay or they’re just not paying attention.
When we read through to the end of the chart where the “Transfer Batch Size” is equal to 1, we find that the Total Lead Time is equal to 1.5 hours, and we are going to say that, whatever the level of WIP inventory in the system actually is (probably between 1 and 2 units), we are going to call that a “relative inventory” of 1.00 (to make our math simple).
By the way, you will notice that, with a Transfer Batch Size of 1, 72.8 percent of the time the unit spend in production was spent in value-added steps. The remaining 27.2 percent of the time was (theoretically) spent waiting between value-added steps.
Larger Transfer Batch Sizes
When we jump up to a transfer batch size (TBS) of 10 units, our Lead Time leaps from 1.5 hours to (essentially) a full day—at 7.50 hours. Our WIP inventory will be (according to Little’s Law, which says that the amount of inventory in the system will be directly proportional to the system’s lead time) about five times what it was with a 1-unit TBS.
If we move to a 50-unit TBS, lead time approaches one week (4 working-days) and inventory to support the lead-time increases to 19-fold what it was with a TBS of 1 unit.
By the way, at a 50-unit TBS (in our scenario), the ratio of Processing Time to total Lead Time is about what it is in most manufacturing operations. Less than four (4) percent of the time a unit spends in the manufacturing is spent in value-added activity.
If management decides we must have transfer batches of 250 units, lead-times approach a full month (18 of 20 or 21 working-days) and we have about 92 times more inventory in WIP than was necessary with an ideal 1-unit TBS.
If our TBS reaches 2,500 units, lead times will skyrocket to about eight-and-a-half months and we will be forced to carry about 900 times more inventory than if we could execute on a TBS of 1 unit!
But wait! There’s more!
Just like those info-mercials on TV: hang on to your seat belt! There’s more to come!
Large transfer batches offer MORE and MORE bad news!
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It is MORE likely that you will be out-of-stock on some other items while you are waiting for a large batch of item ‘Z’ to complete
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If you have quality problems, chances are it will take longer before the problem is noticed and corrective action taken
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Late identification of quality problems means MORE bad product to recall, replace and rework
There are more problems with large transfer batch sizes. And many of these same principles apply with large “transfer batches” created by longer order cycles in your supply chain. The more days between replenishment orders (and related transfer batches) simply means longer lead times and these large orders merely encourage the manufacturers to augment the supply chain problems by working with larger transfer batches in their own production facilities.
Somebody needs to step up and break the cycle.
Do everything you can in your supply chain to drive Transfer Batch Sizes as low as possible and you will begin to see immediate improvement—all else being equal.
Let us hear what you have to say on this topic. Leave your comments here, or feel free to contact us directly.
