Triangle Kanban Sizing

Triangle kanban, while one of three types of signal kanban, are unique in that there is only a single kanban per part number or stock keeping unit. Accordingly, kanban sizing math has nothing to do with determining the number of kanban - that’s obviously fixed.

triangle kanban 4Instead, the math is around determining the total manufacturing lot size, which is the total kanban size, and the appropriate replenishment trigger point or re-order point. Re-order point is addressed in a separate entry by the same title.

 There are two basic methods of sizing triangle kanbans. We will call these: 1) product specific lot size, and 2) universal lot size. The first applies a universal every part every interval (EPEI) for all parts made by the supplying operation. This yields lot sizes that are unique to each part because they are based upon their own unique demand. The second method applies EOQ-type thinking and/or a more simplistic one size fits all approach to determine a universal lot size for all parts. For example, management may determine that the supplying operation will produce every part number in 500 piece lots, no matter what each part number’s specific average demand level may be.

triangle kanban 3The product specific lot size method better matches production with demand and thus minimizes inventory levels, although it is a bit harder to manage. The universal lot size method, while easier to manage (same lot size for every part), will generally require more inventory.

triangle kanban 1triangle kanban 2

There are 3 Comments

Alejandro Terrado's picture

Mark, I have a doubt. As far as I can see, for Product Specific Lot Size, it doesnt matter the demand period. You are multiplying the number of days for Dp and then dividing the number of days for Tr. So Sp doesnt depend on the period. Am I right?
On the other hand, I couldnt find a post about trigger point? What would be the correct math to get the trigger flag from the kanban?
Thanks a lot for the Available time for Change over recent post!!

MarkRHamel's picture

Hi Alejandro,

Thanks for the comment! Mathematically speaking, you are correct. However, remember that the factor of safety is based upon weekly demand variation, as is the demand (I just showed the dailyX5 for reference purposes). I therefore like to keep all of the variables in weekly buckets to keep it pure. If I had calculated daily demand variation, there's a very good chance that the factor of safety would be different...and then the kanban size then would be different.

I'll post the trigger point calculation in the future. In the meantime, check here ( for some great material from Art Smalley and LEI.

Best regards,

Shankh Kumar Acharya's picture

Very well explained Mark, but regarding the trigger point calculation, could you please clarify a bit on the lead time calculation? Smalley says take lead time as sum of 1) runtime of the part with the longest runtime, assuming it is at the front of the queue, 2) Setup time & 3) time taken to produce 1st container.
Now here, why are we assuming only one part is ahead at queue? It may so happen that reorder points for multiple items may reach at the same time, and more than one part nos. are ahead at queue. Secondly, if the withdrawal from my FG inventory is in bulk, as in I ship to my customer once a day, or even the case where the withdrawal rate is more than the throughput of the machine, then is considering just one container production in lead time correct? 1 container may reach but the customer may want to collect his entire order .
Thanks and great blog by the way.