Process Validation in Additive Manufacturing: Why Manual Workflows Fail Every Audit
- Authentise Team
- Feb 8
- 4 min read
Introduction — Additive Manufacturing Needs Proof, Not Promises
In regulated industries such as aerospace, medical, and defence, success in additive manufacturing doesn’t come from printing a part once - it comes from proving you can print it the same way every single time.
This is the purpose of process validation.
But here’s the truth most AM teams quietly admit: Manual workflows make real validation almost impossible.
If:
design files live outside the system,
materials are tracked in spreadsheets,
machine logs aren't linked to the part,
operators record notes in notebooks,
testing data arrives as PDFs via email…
Then you don’t have a validated process - you have a best guess.
This article explores why process validation breaks down so often in AM and what a robust, repeatable, audit-ready system really looks like.
For background, see: Additive MES Explained
What Process Validation Actually Means in Additive Manufacturing
Process validation ensures that every part produced:
follows the same workflow
uses the same validated parameters
meets the same mechanical and dimensional requirements
delivers consistent performance
But AM complicates this because:
every design is unique
parameters vary widely
post-processing affects final properties
machines drift over time
tests depend on external labs
material quality varies with reuse
Validation requires complete control of every variable — and for AM, there are many.
Why Manual AM Workflows Fail Validation
Manual workflows create uncertainty. And uncertainty is the enemy of validation.
1. Uncontrolled Design Files
If design, supports, and slicing files aren’t version-controlled, the process isn’t stable.
2. Material Tracking Gaps
Powder genealogy and metal re-use cycles must be documented end-to-end.
Manual logs introduce:
missing entries
incorrect re-use counts
lost batch data
3. Missing or Unlinked Machine Data
AM machines produce rich data - but if it sits in folders disconnected from the workflow, it cannot support validation.
Auditors expect:
build parameters
exposure settings
thermal histories
chamber conditions
recoater metrics
When these are missing, validation collapses.
4. No Traceability of Operator Input
Operators influence:
machine setup
powder preparation
visual inspections
parameter adjustments
Without digital capture, you cannot validate human decisions — and they matter.
5. External Test Results Arrive (and Stay) in Silos
Tensile tests, CT scans, and NDT results are essential, but labs often return them as PDFs without structured data or linkage.
This breaks the digital thread, a problem explored in: Smart, Traceable, Efficient
What an Audit-Ready AM Validation Workflow Looks Like
A validated AM process needs far more than documentation - it needs data integrity.
Here’s what strong validation looks like:
1. Locked, Controlled Design Revisions
Only validated versions can be printed. Build prep files (supports, slices, parameters) are included as part of the design package.
2. Complete Material Genealogy
Aerospace- and medical-grade validation requires:
batch certificates
re-use tracking
blending documentation
sieving events
powder condition at every stage
This is essential for programmes like: MABOND Case Study
3. Linked Machine Data
Machine logs must be automatically captured and stored within the part’s lifecycle record.
This allows:
deviation detection
process signature comparison
root cause analysis
4. Structured Human Input
Operator actions must be logged:
sign-offs
checks
manual adjustments
photos
notes
This removes ambiguity during audits.
5. Structured, Linked Test Data
External tests must flow into the system and link to the build automatically.
This is becoming mandatory as seen in: DECSAM Programme
How to Prove a Process Is Validated
Auditors need evidence - not explanation.
An ideal system can instantly show:
the design revision used
the exact parameters printed
the material batch genealogy
the machine state during the run
the operator actions recorded
the post-processing steps completed
the full test history
the comparison to previously validated runs
Manual workflows force teams to reconstruct this after the fact, often taking days or weeks - and still leaving gaps.
The Benefits of Digital, Connected Process Validation
When validation is built into the workflow (not bolted on after), organisations achieve:
1. Predictable Quality
Every part follows the same controlled process.
2. Faster Qualifications
Evidence packages generate automatically.
3. Rapid Root Cause Analysis
Every variable is documented and connected.
4. Lower Scrap & Rework
Issues are caught before they progress.
5. Stronger Compliance Confidence
Audits can be passed in minutes, not weeks.
How to Build a Validated Workflow in Practice
There are four steps:
Step 1 — Establish a Digital Thread
All data sources must connect into one lifecycle record.
Step 2 — Automate Data Collection
Manual input introduces risk.
Step 3 — Control Workflow Execution
Validation steps must be enforced, not optional.
Step 4 — Capture Testing & Documentation Digitally
External data must integrate cleanly.
Conclusion — Process Validation Requires Connected Systems, Not More Paperwork
Additive manufacturing cannot rely on manual evidence gathering. The complexity is too high, the data too rich, and the consequences too serious.
A validated process must be:
controlled
traceable
repeatable
automated
connected
This is the only way to achieve the consistency required for industrial-scale AM.
Recommended Authentise Tools
Authentise Flows — enforce workflows & capture machine data
Authentise Materials Management — full genealogy & material control
Authentise Threads — structured test data & documentation
Digital Design Warehouse — design control & revision history
Ready for Industrial-Grade Process Validation?
See how leading AM organisations build validated, audit-ready workflows with Authentise. Book a demo
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