Job Ticket (Production Order)

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

Updated October 2025 • Production Execution & Traceability • eBMR • GS1/GTIN

A Job Ticket—also called a Production Order or Work Order—is the authoritative instruction set and container for evidence that governs the manufacture of a defined quantity of product on a particular line and time window. It binds master data (BOM, recipe, label master) to a unique identifier, constrains execution through barcode validation, and captures results, exceptions, and sign-offs into an eBMR or paper BMR. Practically, it is the thread that ties materials, people, machines, parameters, and labels together so QA can review by exception and customers receive conforming goods with defensible genealogy.

Unlike a schedule entry—which forecasts when a job could run—the job ticket is the control object that proves what did run, with what lots and limits, under which revision of instructions. It is created by planning/MES, becomes Released when all gates are green, is surfaced in the Job Queue for dispatch, and is closed only after reconciliation and QA approval. Whether you build tablets, beverages, or sterile kits, a weak ticket equals weak evidence; a strong ticket makes inspections boring and recalls surgical.

“The job ticket is the single source of truth for a batch: it tells operators what to do, systems what to check, and auditors what happened—step by step, lot by lot.”

1) What It Is

A job ticket is a controlled record that authorizes, guides, and documents the manufacture of a specific SKU/lot. It references the effective BOM, parameters, sampling plans, and label templates held under Document Control, and it binds those masters to a unique job ID with quantity, due date, and line. In modern plants the ticket lives inside an eBMR: each step is rendered to an HMI with device captures (scales, metal detectors, PLC tags), enforced fields, reason codes, and Dual Verification where risk warrants. On paper, the same logic applies—but risk of wrong revision and poor legibility skyrockets.

2) Core Contents & Identifiers

Every good ticket contains: (a) Identity—job ID, SKU, description, qty, planned dates, line/cell; (b) Revisions—effective BOM/recipe/version and label master ID; (c) Materials—required components with units, tolerances, and FEFO/FIFO rules; (d) Process—sequenced steps with parameters and control limits; (e) Quality—IPC plan, sampling frequency, acceptance criteria; (f) Labels—GTIN/lot/expiry formats per GS1/GTIN; (g) Risks—allergen class, potency bracket, PPE/JHA prompts; (h) Signatures—operator, verifier, supervisor/QA with Part 11 intent and meaning; (i) Traceability—links to Batch Genealogy and pallet/ship labels; (j) Exceptions—deviation/NC hooks and disposition logic.

3) Lifecycle: From Creation to Closeout

Create: MRP/MES issues the ticket with masters pinned to versions. Gate: materials Approved via Component Release, kits staged by Directed Picking under FEFO. Release: supervisory/QA e-signature changes state to Released; the job enters the Job Queue. Execute: scans and device data enforce limits; exceptions open Deviation/NC. Reconcile: yields/variance, label counts, and material consumption are balanced. QA Review: evidence is checked by exception. Close: results roll to inventory; records feed APR/PQR and CAPA where patterns exist.

4) Controls & Compliance Expectations

Tickets embody quality decisions and must meet GxP audit trail and ALCOA+ expectations: attributable user IDs, contemporaneous entries, original device data, and accurate, reviewable context. Electronic tickets should enforce unique logins, time sync, version-to-execution checks, and reason-coded edits; paper tickets must be controlled copies with legible, single-line corrections and signature/initial/date. Label issuance must reference the master art/template in force; serialization or lot/expiry coding must be previewed and verified before print/apply to prevent market withdrawals.

5) Material Management Tie-Ins

Job tickets are inseparable from warehouse control. Required components should stage via bin-directed moves and scans; substitutes follow controlled change with QA involvement. At dispense and pick, Barcode Validation confirms GTIN, lot, and expiry; FEFO pressure elevates near-dated lots; and status changes (Hold/Approved) propagate instantly so unreleased lots cannot be consumed. Backflush rules must align with reality—gravimetric steps use captured weights; discrete components subtract by scans—so reconciliation means something and genealogy is complete.

6) Execution Data Captured

Strong tickets capture: operator IDs and qualifications; start/stop times per step; actual machine settings and verified parameters; gravimetric weighing results with tolerance checks; IPC results and sampling timestamps; label print/reprint counts and template IDs; line clearance and counts reconciliation; deviations with photos and root-cause codes; holds and dispositions; and final yields (good/scrap/rework) with variance reasons. This data powers CPV, supplier performance feedback, and realistic standard-cost updates.

7) Common Failure Modes (and How to Avoid Them)

Old revision on the floor. Paper packets drift. Countermeasure: render controlled documents only in eBMR; block execution if revision mismatch is detected.

Wrong-part/label introduction. Manual lookups fail. Countermeasure: enforce GTIN+lot scans at dispense/pick and at print/apply; preview encoded data and reconcile label counts.

Ambiguous quantities and backflush. Generic backflush masks losses. Countermeasure: capture actuals from scales and scanners; use variance thresholds that trigger investigation.

Unqualified operators. Skill gaps block steps or drive errors. Countermeasure: role/skill checks at login; show upskilling prompts and alternates in the queue.

Incomplete deviations. “Fixed on the fly” with no evidence. Countermeasure: require reason codes, photos, containment and disposition before close; link systemic issues to CAPA.

Label reconciliation gaps. Overprints and waste untracked. Countermeasure: serialize label issuance, scan-back scrap/overage, and reconcile at line clearance.

8) What to Measure

Ticket quality is visible in: On-time starts vs. scheduled; Start-up block rate (materials/label/training holds); Right-first-time (no deviations raised); Scan adherence at dispense/pick/label; Yield & variance vs. standard; Label reconciliation accuracy; Review-by-exception rate (fraction of tickets QA can pass without manual digging); Trace time to render a complete record pack; and FEFO compliance for perishable inputs. Track these per SKU and line to see where masters, training, or equipment capability need work.

9) How This Fits with V5

V5 by SG Systems Global generates the Job Ticket as a controlled object. Masters come from Document Control; materials flow through Directed Picking with FEFO; consumption uses device data and scans; and the eBMR enforces parameters, prompts Dual Verification, and blocks wrong parts via Barcode Validation. Supervisors/QA authorize Job Release; the job appears in the Job Queue; results and deviations flow into analytics and Finished Goods Release. For audits, V5 renders the complete record set—including genealogy and label evidence—in minutes, not days.

10) FAQ

Q1. How is a Job Ticket different from a schedule line?
The schedule forecasts timing across resources; the Job Ticket is the controlled record that authorizes work and captures what actually happened—materials, parameters, labels, and signatures.

Q2. Paper or electronic—does it matter?
Paper can work but is fragile. Electronic tickets with enforced scans, device data, audit trails, and version checks are far more defensible and reduce rework during QA review.

Q3. What belongs on the ticket vs. in master data?
The ticket references masters (BOM, recipe, label templates) by effective revision. It should not duplicate them; it should carry job-specific quantities, exceptions, and results bound to those masters.

Q4. How do tickets prevent label errors?
By referencing the label master in force, previewing variable data (lot/expiry/GTIN), enforcing scans at print/apply, and reconciling issued vs. applied labels at line clearance.

Q5. What proves ticket effectiveness?
High scan adherence, low start-up blocks, low deviation rate, accurate label reconciliation, quick trace time, and strong review-by-exception—all tied back to audit-trailed actions on the ticket.

Related Reading
• Masters & Control: Document Control | BOM | GS1/GTIN
• Planning & Execution: Job Scheduling | Job Release | Job Queue
• Materials & Quality: Directed Picking | Barcode Validation | FEFO | Batch Genealogy | Finished Goods Release | Deviation/NC | CAPA