Differentiated Service Level · Inventory Buffer

Semiconductor Buffer Optimizer

Separates the fixed supply bin-split from demand segments, each with its own service-level target — by customer, product, or family. One bin can serve several segments at different targets; downgrade substitution pools the risk, and each cut is sized to the toughest target it protects. Then it quantifies what differentiating saves versus a uniform policy pinned to your hardest customer.

Set it up in 5 steps
  1. Supply — bin split. Enter your grades top-down (best quality first) with the % of output that falls into each. This is process physics: you don't choose it, you measure it. Splits auto-normalize to 100%.
  2. Demand — segments. One row per demand segment, named however you segment (customer tier, ABC class, end-market). Each maps to the minimum grade it accepts, fans out into its number of FG SKUs, and carries its weekly demand, CV and its own service-level target. Tick NPI for launches without history.
  3. Structure. Pick where the buffer lives (wafer / die bank / finished goods) and where the grade becomes authoritative (wafer sort = end of front-end, final test = end of back-end). Together they decide whether your inventory is pooled or committed.
  4. Variability. Lead times with their σ per stage, yields and yield CV, supply-adherence CV (receipts vs the unpadded committed plan), correlation ρ between FG variants, and the NPI premium/maturity if you flagged any segment.
  5. Unit costs. Value per unit at each stage — this is what converts buffer units into the capital figures shown everywhere.
How to read the results

KPIs. Buffer Value is the capital of your differentiated policy at the selected position. Response Time is how long a customer waits when demand hits the buffer. Structural Excess is overproduction forced purely by the mismatch between bin split and demand mix — it exists before any safety stock.

Segment Coverage. Buffer attributed per segment, with a share bar. The amber “drives cut” tag marks the segment whose target sizes the binding cut — your most expensive customer to protect.

Position Trade-off. For each position, the blue bar is your differentiated policy and the pink bar a uniform policy pinned to your toughest target. Where the bars are nearly equal, differentiation gains you nothing there.

Decoupling Frontier. Each point is a position: buffer capital vs customer response. Down-left dominates; the dashed line is the frontier your lead-time, yield and mix structure allows.

Cost of a Uniform Policy. The blue curve prices a single flat target at every service level; the green dashed line is your differentiated policy. If green sits on the red dot, your pooled buffer is hostage to your toughest customer.

Four experiments that teach the model
1 · Pooling vs differentiation
On Die Bank, switch Grade Fixed At from Final Test to Wafer Sort. The buffer flips from pooled to committed — and differentiation suddenly starts saving money.
2 · The value of component-level calc
Raise variant correlation ρ from 20% to 100% and watch the Finished Goods point climb no further — when variants move together, computing at component level stops paying.
3 · NPI graduation
Flag a segment as NPI, then slide Ramp maturity from 0% to 100%. The buffer premium decays live until the NPI carries the same buffer as its analog.
4 · Who holds your buffer hostage
Move the highest SL to a lower grade (e.g. set the Value segment to 99.5%). Pre-bin savings appear out of nowhere: pooling only chains you to your toughest customer when they sit in your top bin.

Model Inputs

Supply — Fixed Bin Split

Top = highest quality (substitutes down). Splits auto-normalize to 100%.

Demand — Segments
Segment Requires SKUs Dem/wk CV% SL% NPI

Each segment reads as a component (die) family: SKUs = how many finished-good variants that common component fans out into. Demand and CV are the segment aggregate.

BOM Commonality

0% = variants move independently (full pooling upside at the component: √N). 100% = variants rise and fall together (pooling is worthless). Applies where inventory is committed per SKU — finished goods.

NPI Settings

For segments flagged NPI, the CV you enter reads as the analog product's CV (matched by lifecycle phase). It is inflated by the premium — analog history understates launch risk — and the inflation decays as maturity grows: effective CV = analog CV × (1 + premium × (1 − maturity)). At 100% maturity the NPI has graduated.

Buffer Position
Grade Fixed At

Where the grade becomes authoritative. Fix it at final test and the die bank is still pooled (undifferentiated die). Fix it at wafer sort and the die bank is already committed per bin — pooling is lost one stage earlier.

Lead Time — weeks (mean ± σ)
±
±
±
±
Yield %
Supply Adherence

Variability of receipts vs the committed plan (factory schedule adherence, supplier fill). Enters the buffer in quadrature with demand and lead-time variability. Measure it against the unpadded plan — adherence to an already-buffered schedule double-counts.

Unit Cost by Stage ($)
Buffer Value
–
differentiated policy
Response Time
–
–
Structural Excess
–
forced by fixed bin split

Decoupling Point

Segment Coverage

Segment Grade SL Demand / LT Buffer

Position Trade-off

Differentiated ($) Uniform @ toughest ($) Response (wks)

Decoupling Frontier

Cost of a Uniform Policy

Uniform policy @ SL Your differentiated policy

Model: first-order screening approximation. Differentiated targets couple via cumulative cuts sized to the toughest service level each protects (conservative); yield uncertainty via delta method; demand, lead-time and supply-adherence variability combine in quadrature (King extended); BOM commonality via per-segment SKU fan-out with correlation ρ — finished-goods safety fragments by √(N/(1+(N−1)ρ)); NPI segments use analog CV inflated by a maturity-decaying premium. For policy-setting and what-if analysis — not a replacement for full stochastic simulation. © 2026 Mr. Supply Chain® Labs.