JIT (Just-in-Time) Manufacturing

This topic is part of the SG Systems Global regulatory & operations guide library.

Updated January 2026 • JIT, pull replenishment, kanban signals, heijunka leveling, one-piece flow, WIP limits, lead time compression, shortage prevention, quality holds, traceability, exception handling, ERP/MRP boundary • Manufacturing & Operations

JIT (Just-in-Time) manufacturing is an operating model where material, components, and work are released only when needed, in the quantity needed, to support a controlled flow of production. The goal is not “run with no inventory.” The goal is to replace hidden buffers (excess WIP, overproduction, ad-hoc expediting) with visible, governed signals that keep flow stable while minimizing waste.

In practice, JIT is a promise: “We will not push work into the system just because we can.” That promise is valuable because push systems create WIP, long lead times, and low signal-to-noise when something goes wrong. But the trade-off is brutal: the less inventory you hold, the more your operation depends on execution truth—accurate inventory, reliable lead times, disciplined replenishment, and fast exception handling.

Good JIT is not a slogan. It is a controlled method that answers three questions continuously:

• What is the pull signal? (actual demand, takt, schedule, or consumption trigger)
• What is eligible to move or be consumed? (identity, lot/expiry, quarantine/release status, substitution rules)
• What happens when reality breaks the plan? (shortage, quality hold, downtime, supplier miss, rework)

If those questions are answered deterministically by a system, JIT reduces WIP and lead time while improving responsiveness. If they’re answered by spreadsheets and heroics, JIT becomes a shortage generator—because you removed buffers without building control.

“JIT doesn’t remove risk. It removes hiding places.”

1) What buyers mean by JIT

Organizations ask for JIT because they are trying to reduce one (or more) of these realities:

• Lead time inflation: too much WIP means work waits longer than it runs.
• Cash trapped in inventory: materials and WIP are sitting, aging, expiring, or becoming obsolete.
• Schedule instability: planners push orders; supervisors re-sequence; the floor chases “hot” work all day.
• Quality noise: defects are found late because WIP buffers hide problems until they explode.
• Expediting culture: daily firefighting replaces improvement, and “the squeaky wheel” becomes the schedule.

JIT is also a competitiveness strategy. If you can replenish quickly and reliably, you can offer shorter customer lead times without carrying massive buffers. But the requirement is not motivational posters—it is control. The system has to know what demand is real, what inventory is real, and what events actually happened.

Most buyers also implicitly want JIT to include:

• Pull replenishment: consumption triggers replenishment rather than forecast pushing material.
• Leveled production: variation is smoothed so suppliers, lines, and labor can keep up (heijunka).
• Flow thinking: reduce batch-and-queue behavior and improve end-to-end throughput (value stream mapping).
• Visual control: make shortages and stoppages obvious (dispatch boards, andon alerts, reason coding).

In other words, “JIT” is usually shorthand for pull + flow + visibility, not just “less inventory.”

2) JIT building blocks: pull, kanban, leveling, flow

JIT is not one workflow. It is a toolkit of mechanisms that create pull signals and protect flow. The mechanism you choose should match variability, lead time, and compliance constraints.

Notice the theme: every JIT mechanism depends on identity, timing, and discipline. That’s why JIT is often paired with lean fundamentals: standard work, visual management, quick changeover, and root-cause correction—not just scheduling changes.

Two glossary terms that prevent teams from inventing “personal definitions”:

• Lean manufacturing: the broader waste-elimination system that JIT sits inside.
• One-piece flow: the flow ideal that makes problems visible quickly and reduces waiting time.

If you have not defined the pull loop, the signal, the container size, and the exception rules, you don’t have JIT. You have hope.

3) When JIT works—and when it fails

JIT is not a universal best practice. It is a best practice under the right conditions and controls.

JIT works best when:

• Process capability is stable: predictable yields, controlled changeovers, and manageable downtime.
• Supply is reliable: lead times are real, suppliers are disciplined, and inbound variability is controlled.
• Inventory truth exists: you trust location, quantity, lot/expiry, and status (inventory accuracy is not optional).
• Exceptions are surfaced fast: stoppages and shortages create visible signals (andon, reason codes, dispatch boards).
• Quality gates are hard: held material cannot be consumed, and substitutions follow governance.

JIT fails (predictably) when:

• Variability is uncontrolled: frequent outages, high scrap, unstable changeovers, or supplier misses.
• Data is optimistic: lead times and inventory are “estimated,” so pull signals are wrong.
• Work release is undisciplined: planners push orders “just in case,” violating WIP limits.
• Quality is disconnected: material is on hold in one system but still consumable in another.
• Expediting is the operating system: people bypass signals because “we don’t have time.”

The useful question isn’t “Do we want JIT?” It’s: where should the buffer live? In push systems, the buffer is usually WIP and finished goods. In JIT, the buffer is usually controlled supermarkets, schedule discipline, and fast response. When those buffers are weak, the operation will recreate buffers informally—usually in the worst possible places (untracked WIP, “emergency” pallets, undocumented substitutions).

4) Process model: signal → replenish → consume → confirm

A controlled JIT process is built around consumption-driven replenishment and scan-confirmed execution. A practical model looks like this:

The weak pattern is “use kanban cards” while system inventory is inaccurate and consumption is posted later. That creates false signals and silent shortages. The strong pattern is event-driven truth—the system updates as work happens (see real-time shop-floor execution and event-driven manufacturing execution).

Once you model the signal, you can govern it. Without a defined signal, “JIT” becomes improvisation.

5) Execution controls: WIP limits, supermarkets, shortage logic

JIT lives or dies on three execution controls.

A) WIP limits and release gates

• Explicit WIP caps: define how much work can be in each stage, not just “overall.”
• Release discipline: new work is released only when capacity and material eligibility are true.
• No silent bypass: overrides must be captured with reasons and reviewed.

B) Supermarkets and point-of-use control

• Named locations: line-side and supermarket locations are explicit, scannable, and reconciled.
• Min/max logic: replenishment quantities are rule-based, not guessed at 2am.
• Container integrity: if a “container” can be anything, your signal will drift; define pack sizes and enforce them.
• FEFO/lot rules where needed: when expiry matters, point-of-use must respect lot rules (FEFO).

C) Shortage logic and fast recovery

• Shortage visibility: when material is missing, the system should surface “why” (not received, on hold, mislocated, consumed elsewhere).
• Controlled substitutions: alternates are used only under approved rules, not “whatever fits.”
• Escalation paths: shortage events trigger andon and clear escalation, not quiet workarounds.

A key operational detail: JIT does not eliminate the need for planning. It changes what planning focuses on—from micromanaging every release to designing stable loops and enforcing truth. That’s why mature JIT environments still use ERP/MRP—they just stop treating MRP suggestions as automatic shop-floor orders.

6) Quality and compliance: holds, traceability, and “no leak” rules

JIT increases sensitivity to quality state because it reduces buffers. In regulated or safety-sensitive environments, JIT must be tightly coupled to quality disposition. The core requirement is simple: quality state must be a hard gate on movement and consumption.

Practically, that means:

• Holds block consumption: if a lot is on hold, it must be ineligible for issue/consume (quarantine/hold status).
• Disposition is explicit: release, reject, rework, return, scrap are controlled outcomes tied to evidence (release status).
• Traceability survives speed: consumption and replenishment must preserve lot/serial genealogy. JIT without traceability becomes undefendable.
• Change control protects loops: engineering changes, recipe changes, and approved alternates must be governed (change control).

This is where many “lean” programs collide with reality: the warehouse thinks material is available, while quality thinks it is not. If systems disagree, JIT will force operators into workarounds. The right architecture is alignment: warehouse and shop-floor execution must consume only what is released, and quality state changes must apply quickly and consistently.

Data integrity matters here because JIT is evidence-driven. If consumption postings are delayed, edited without audit trails, or reconstructed later, you cannot trust your pull signals or your compliance story (see data integrity and audit trails).

A practical rule in regulated environments: if material isn’t released, it shouldn’t physically be in the same flow as released material. That’s why JIT implementations often define separate supermarkets or controlled staging for released stock, and route held stock to quarantine zones by default.

7) Data prerequisites: inventory truth, UOM, BOMs, and lead times

JIT is a data-quality accelerator. It magnifies both good data and bad data.

Minimum data prerequisites:

• Inventory accuracy: quantities, locations, and status must reflect reality (inventory accuracy).
• Unit-of-measure consistency: conversions must be correct or replenishment will fail (UOM conversion).
• BOM truth and approved alternates: the system must know what can be used (BOM + approved alternates).
• Lead time realism: measured lead times and constraints, not wishful targets (lead time).
• Supplier performance insight: variability must be known and improved (supplier risk management + supply chain risk).

Inventory accuracy is the most common silent killer. If you implement pull loops on top of inaccurate inventory, you will get “phantom stock,” false signals, and emergency moves. The fix is not “train people to be careful.” The fix is to design capture points and verification loops: receiving, put-away, line-side replenishment, consumption, and cycle counting.

One more harsh truth: JIT cannot compensate for uncontrolled engineering change. If BOMs drift, recipes change informally, or alternates are used without governance, pull loops will constantly misfire. That’s why serious JIT programs invest in master data control and change control before they “turn down inventory.”

8) Integrations: ERP/MRP boundary + real-time execution events

JIT is inherently cross-system. It touches planning (ERP/MRP), execution (MES/WMS), quality (QMS), and supplier communication (ASN/EDI). The risk is not lack of integration—it’s uncontrolled integration where systems disagree about what is true.

In most operations, the clean boundary looks like this:

JIT performs best when execution is event-driven: consumption creates signals, completion updates state, holds instantly block use, and downtime events are reason-coded. That requires a reliable event and API boundary. In the V5 product stack, that boundary is V5 Connect API: keep integrations consistent, observable, and governed so pull decisions are based on real state, not stale assumptions.

If your integrations routinely lag, JIT will recreate buffers as “emergency” material and “just in case” work release—which is exactly what you were trying to eliminate.

9) What this means for V5: product alignment and link strategy

In V5 terms, JIT should be positioned as a platform-level flow capability that is executed in MES and WMS, governed by quality state, and strengthened by integration reliability. It’s not a single feature toggle. It’s an operating model that needs orchestration.

Here is the clean product alignment:

What to emphasize in V5 messaging:

• “Pull with proof”: replenishment and consumption are scan-confirmed and status-aware, not assumed.
• “WIP is governed”: release gates and WIP caps stop flooding and make lead time predictable.
• “Exceptions become improvement”: reason-coded shortages and downtime drive root cause correction.
• “Quality state is real-time”: holds and releases instantly affect eligibility to move/consume.
• “Integration is part of the feature”: JIT is only as good as the state truth feeding it.

10) Industry considerations: how JIT changes by sector

JIT is common in discrete manufacturing, but it is increasingly relevant in regulated and process manufacturing networks—especially where demand volatility and working capital pressure collide with strict quality controls. The constraints change by industry.

If you want the “one line” summary by sector: high-velocity industries use JIT to protect freshness and service; high-control industries use JIT only when quality state and identity are airtight.

Browse all industry pages: Industries

11) KPIs that prove JIT is working

JIT should show up in measurable flow outcomes. If you can’t measure it, you can’t govern it—and it will drift into “push with extra paperwork.”

One KPI that reveals whether JIT is real: exception aging. If shortage alerts and andon events remain open for hours or days without controlled resolution, you don’t have pull—you have slow chaos.

12) Selection pitfalls: how “JIT” gets faked

JIT is easy to claim and easy to fake. These are the red flags that the capability isn’t real (or isn’t controlled):

• “JIT” means zero inventory. Cutting buffers without improving stability just increases shortages and expediting.
• Signals exist, but overrides are routine. If people ignore kanban and push work anyway, WIP limits are meaningless.
• Consumption is posted late. Backflushing can work in some contexts, but if it hides shortages, pull becomes fiction (see backflush accounting).
• Supermarkets are unstructured. No named locations, no cycle counting, no reconciliation—just “bins.”
• Quality holds are advisory. Held material can still be issued or “borrowed” by production.
• Master data drifts. UOM conversions, container sizes, and lead times aren’t governed, so loops misfire.
• Success depends on heroics. If JIT only works when a few experts are present, it won’t scale.

13) Copy/paste demo script and scorecard

Use this script to force an execution-real demo. You want to see JIT under failure conditions, not a perfect-day scenario.

14) Extended FAQ

Q1. What is JIT (Just-in-Time) manufacturing?
JIT is a pull-based operating model where materials and work are released only when needed, reducing WIP and lead time while increasing responsiveness—provided inventory truth, replenishment discipline, and exception handling are strong.

Q2. Is JIT the same as “zero inventory”?
No. JIT replaces uncontrolled buffers with controlled ones (supermarkets, leveled schedules, WIP caps). Cutting inventory without building control increases shortages and expediting.

Q3. What’s the relationship between kanban and JIT?
Kanban is a common mechanism for JIT pull replenishment. It defines the signal that triggers replenishment when consumption occurs, keeping flow stable without pushing excess work.

Q4. Can JIT work in regulated industries?
Yes, but only with hard quality gates, quarantine/release discipline, and audit-ready traceability. Held material must be ineligible for movement and consumption, and the system must prove compliance.

Q5. How does JIT relate to V5 products?
JIT execution relies on V5 MES for real shop-floor events and WIP governance, V5 WMS for replenishment and inventory truth, V5 QMS for holds/releases and audit-ready evidence, and V5 Connect API to keep planning and execution state aligned across ERP, suppliers, automation, and external systems.

Related Reading
• Glossary Core: JIT (Just-in-Time) | Lean Manufacturing | Kanban | Heijunka | One-Piece Flow | Value Stream Mapping
• Planning & Control: Production Scheduling | Lead Time | MRP | ERP | Capacity Planning
• Execution & Visibility: Inventory Accuracy | Cycle Counting | Real-time Shop Floor Execution | Event-driven Execution | Dispatch Board | Dispatch Rules Engine | Andon Alerts
• Quality & Governance: Quarantine/Hold | Release Status | Change Control | Data Integrity | Audit Trail
• V5 Products: V5 MES | V5 WMS | V5 QMS | V5 Connect API | V5 Solution Overview