### Kanban Logistics

Demand lead times are getting shorter in most business while supply lead times are not able to keep pace. This often leaves just one alternative: "make to plan", also called "Push" logistics. The result is that in spite of our excess inventories we are unable to satisfy the demand: we have plenty of what nobody wants and no enough of what they want.

"Make to order" or "Pull" logistics produces only what has been ordered by the customer so we avoid dedicating resources to produce unwanted items. The problem usually is lead time: can the customer wait until our supply chain is able to deliver?

### Kanban

One way to implement "Pull" logistics is to use Kanban.

A Kanban (Japanese for a card) is a token generated by the consumption of an item (or fixed lot of items) which authorizes the production of a similar one to replace it.

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In the model above the blue workstation can produce one item A or one B every 4 minutes. There is no setup time when changing product. "a" is a kanban which enables the production of "A" and "b" a kanban to produce "B".

When an item "A" is consumed its corresponding kanban "a" is released and it joins the queue at the production station. Kanbans "a" and "b" will be produced in the order of arrival to the queue.

Market demand is defined by the Takt times of A and B: one item A is required every 10 minutes and one B also every 10 minutes.

The number of kanbans in circulation determines the maximum inventory we could accumulate.

In this case Takt of both A and B is 20 minutes which is equivalent to 3 items per hour. Since we need 3 A's and 3 B's every hour this gives a total of 6 items per hour to be produced. Production process time is 5 minutes therefore production capacity is 12 items/ hour. Kanbans are limiting production to the consumption rate of 6/ hour therefore we are producing at 50% capacity.

In this case we have decided to put into circulation 10 "a" kanbans and 10 "b" therefore we have accumulated an inventory of 10 A's and 10 B's.

In this case supply capacity 12/h is the sum of demand thruputs (6 + 6)/h therefore supply capacity utilization is 100% and demand fulfillment of both A and B is also 100%.

In this case Supply is the bottleneck: we are unable to supply the market demand which is 12 A's plus 12 B's' per hour. Since total capacity is 12/h fulfillment of both demand A and demand B is 50%.

We see no inventory of A's or B's because as soon as they are produced they are consumed.

In this case of limited supply we might decide to give priority to one item (or customer) Vs the other. We can do this with the number of kanbans in circulation. In this case by releasing 10 a's and 5 b's we are able to increase fulfillment of A to 70% at the expense of fulfillment of B which will drop to 30%.

With this Just-In-Time approach a drop in the demand of one item (customer) could be balanced by an increase in another one.

In this example B in no longer required so the full capacity is available to produce A.

In this case of short supply the demand of A and B is different. We may decide to manage this situation by balancing the fulfillment of A and B. Since demand of A is double of B we release double number of "a" kanbans Vs "b".

In this way we achieve 80% fulfillment both for A and B.

On the other hand we may have variation both in process time and in the demands of both A and B. To compensate for this variation we will need to increase the number of kanbans and therefore the level of inventory.

As shown in: Value Stream Constraints

Variation in process capacity §2 causes an accumulation of WIP both before and after it. This increases the lead time for the whole value stream.

If we eliminate this excess WIP by applying kanban:

We have, indeed, eliminated the excess WIP but at the expense of reducing the effective capacity of the total value stream (Average thruput) and exposing the customer to the variation of step §2: drastic drop in on-time-delivery.

So this is a case where kanban is NOT recommended.

A Kanban (Japanese for a card) is a token generated by the consumption of an item (or fixed lot of items) which authorizes the production of a similar one to replace it.

Download this Excel file

**JITeng3.xlsm**from OneDrive folder: PolyhedrikaIn the model above the blue workstation can produce one item A or one B every 4 minutes. There is no setup time when changing product. "a" is a kanban which enables the production of "A" and "b" a kanban to produce "B".

When an item "A" is consumed its corresponding kanban "a" is released and it joins the queue at the production station. Kanbans "a" and "b" will be produced in the order of arrival to the queue.

Market demand is defined by the Takt times of A and B: one item A is required every 10 minutes and one B also every 10 minutes.

The number of kanbans in circulation determines the maximum inventory we could accumulate.

### Supply Capacity Greater than Demand

In this case Takt of both A and B is 20 minutes which is equivalent to 3 items per hour. Since we need 3 A's and 3 B's every hour this gives a total of 6 items per hour to be produced. Production process time is 5 minutes therefore production capacity is 12 items/ hour. Kanbans are limiting production to the consumption rate of 6/ hour therefore we are producing at 50% capacity.

In this case we have decided to put into circulation 10 "a" kanbans and 10 "b" therefore we have accumulated an inventory of 10 A's and 10 B's.

### Balanced Supply and Demand

In this case supply capacity 12/h is the sum of demand thruputs (6 + 6)/h therefore supply capacity utilization is 100% and demand fulfillment of both A and B is also 100%.

### Short Supply

In this case Supply is the bottleneck: we are unable to supply the market demand which is 12 A's plus 12 B's' per hour. Since total capacity is 12/h fulfillment of both demand A and demand B is 50%.

We see no inventory of A's or B's because as soon as they are produced they are consumed.

### Priority Allocation

In this case of limited supply we might decide to give priority to one item (or customer) Vs the other. We can do this with the number of kanbans in circulation. In this case by releasing 10 a's and 5 b's we are able to increase fulfillment of A to 70% at the expense of fulfillment of B which will drop to 30%.

### Item B Discontinued

With this Just-In-Time approach a drop in the demand of one item (customer) could be balanced by an increase in another one.

In this example B in no longer required so the full capacity is available to produce A.

### Balanced Fulfillment

In this case of short supply the demand of A and B is different. We may decide to manage this situation by balancing the fulfillment of A and B. Since demand of A is double of B we release double number of "a" kanbans Vs "b".

In this way we achieve 80% fulfillment both for A and B.

### Number of Kanbans

The more kanbans we release the more inventory we could accumulate so we want to keep the number of kanbans as low as possible.On the other hand we may have variation both in process time and in the demands of both A and B. To compensate for this variation we will need to increase the number of kanbans and therefore the level of inventory.

### Kanban and Variation

Variation causes an accumulation of WIP in the Value Stream:As shown in: Value Stream Constraints

Variation in process capacity §2 causes an accumulation of WIP both before and after it. This increases the lead time for the whole value stream.

If we eliminate this excess WIP by applying kanban:

We have, indeed, eliminated the excess WIP but at the expense of reducing the effective capacity of the total value stream (Average thruput) and exposing the customer to the variation of step §2: drastic drop in on-time-delivery.

So this is a case where kanban is NOT recommended.

### Conclusion

- Kanban is a practical way to implement pull logistics in our supply chain
- Managing the number of kanbans we put a limit in the inventory level in the value stream of each item
- High variation in the supply or the demand side will require a higher number of kanbans and might make pull logistics impossible

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