Just-In-Time Calculator

Balance demand, lead time, and material flow today. Compute reorder points, kanban cards, and EOQ. Turn inputs into lean decisions your shop floor trusts.

Inputs

Use consistent units. Fields marked with an asterisk are key drivers.
Demand & lead time
Typical: 1.28 (90%), 1.65 (95%), 2.05 (98%).
Inventory policy
Adds protection for interruptions and variability.
Costs & flow

Result appears above this form, below the header.

Example data table

SKU Daily demand Lead time (days) Container size Buffer % Service Z On-hand
A-100120825151.65300
B-220601020202.05420
C-03135615101.28140
D-515200540121.65900

Formula used

These equations are widely used to support pull systems and stable replenishment.
Lead-time demand
LTD = d × LT
d = daily demand (units/day), LT = lead time (days).
Safety stock (variable demand + variable lead time)
SS = z × √( LT × σd² + d² × σLT² )
z = service factor, σd = demand std. dev., σLT = lead time std. dev.
Reorder point
ROP = LTD + SS
Trigger replenishment when on-hand ≤ ROP.
Kanban containers
K = ceil( d × LT × (1 + buffer) ÷ C )
C = container size. buffer is a percentage converted to a fraction.
Economic order quantity
EOQ = √( 2 × D × Co ÷ Ch )
D = annual demand, Co = ordering cost, Ch = holding cost/unit/year.
Takt time
Takt = available time ÷ customer demand
Compare to scrap-adjusted cycle time to spot constraints.

Demand signal quality

Track demand as units per day and measure variability using standard deviation. In many plants, a stable product family shows 5–15% daily variation, while volatile aftermarket items can exceed 30%. Use the calculator’s σd input to capture noise, then review the last 20–30 working days to confirm the mean is representative.

Lead-time behavior

Lead time is not only supplier transit; it includes picking, staging, receiving, and inspection. A mean lead time of 8 days with σLT of 1.5 days implies frequent late arrivals and inconsistent release timing. Reducing average lead time by one day cuts lead-time demand by d units, while reducing σLT directly lowers safety stock.

Practical targets are 95% on-time delivery and less than 10% lead-time variation. Map the end-to-end path, time each step, and remove queues. Even a two-day reduction in LT often allows a kanban reduction within one month without increasing safety stock at all.

Safety stock economics

Safety stock protects service, but it also ties up cash. With Z=1.65, d=120, LT=8, σd=20, and σLT=1.5, safety stock is about 351 units, worth 4,212 at a 12 unit cost. If turns are low, test a lower Z, improve σd through level loading, or shorten LT by supplier development.

Reorder point discipline

Reorder point equals lead-time demand plus safety stock. In the example above, lead-time demand is 960 units, giving an ROP near 1,311 units. If on-hand falls below that threshold, replenishment should trigger immediately, not at the next planning cycle. Use “days on hand” to validate feasibility: 300 units at 120/day is 2.5 days cover.

Kanban sizing for pull loops

Kanban containers translate policy into shop-floor actions. Using container size 25 and buffer 15%, K ≈ ceil(120×8×1.15/25)=45 containers. This number should match physical space, rack locations, and transport frequency. To reduce K safely, shrink LT, reduce buffer after downtime is controlled, and increase container size only if handling remains acceptable.

Takt versus cycle capability

Takt sets the required production pace. With 450 available minutes and 110 units demand, takt is 4.09 minutes/unit. If cycle is 3.9 with 2% scrap, effective cycle becomes 3.98, giving a pace ratio near 1.03. When the ratio drops below 1.00, cut setup time, balance work content, and protect uptime.

FAQs

Which output should I act on first?

Start with reorder point and kanban count because they drive daily replenishment behavior. Use takt and pace ratio to validate capacity, then use EOQ as a cost check against container multiples.

What service factor Z should I choose?

Use higher Z for high-penalty stockouts or critical parts. Common choices are 1.28 (90%), 1.65 (95%), and 2.05 (98%). Improve variability first before increasing Z.

Why does safety stock increase when lead-time variation rises?

Variable lead time increases uncertainty during replenishment. The safety stock formula adds a term with d²×σLT², so even small σLT values can raise buffers when daily demand is large.

Should I always order the EOQ quantity?

Not always. In pull systems, container multiples and delivery cadence matter. Use EOQ to understand cost tradeoffs, then align ordering to kanban containers, minimum order constraints, and transport frequency.

How do I use scrap rate in planning?

Scrap reduces yield, so effective cycle time increases. If the pace ratio trends below 1.00, improve quality, stabilize process settings, and protect critical-to-quality steps to recover capacity without adding overtime.

Can I use this for multiple SKUs?

Yes. Run it per SKU or per family with similar demand and lead time. For families, use aggregated demand and variability, then allocate kanban by mix and physical constraints on the line.

How to use this calculator

  1. Enter daily demand and lead time using real averages.
  2. Add variability: demand and lead time standard deviations.
  3. Select a service factor Z to match your target fill rate.
  4. Set container size and buffer to reflect your pull loop.
  5. Fill costs to estimate EOQ, then compare to container multiples.
  6. Enter available time, customer demand, and cycle time for takt checks.
  7. Press Submit. Review ROP, kanban count, and pace ratio.
  8. Export results as CSV or PDF for sharing.

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Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.