Who
A US-based manufacturer focused on high-performance polymer extrusion and custom tubing solutions.
Case Study
Executive Summary
Problem
Their existing analog contact angle tool was not delivering the precision and repeatability needed for modern QC.
Solution
Adoption of Droplet Lab's smartphone-based goniometer system, supported by a validated measurement approach benchmarked against KRÜSS DSA100E reference measurements.
Time to Value
4 months
Results
Variance moved from broad manual estimation toward instrument-grade repeatability, with stronger confidence in QC reporting.
Client Snapshot
Industry
Polymer extrusion / custom tubing manufacturing
Products / Applications
Supports medical, aerospace, automotive, and industrial sectors
QC Stage (Incoming / In-Process / Final)
In-process inspection
Users (Roles / Shifts)
Inspectors / factory staff
Materials / Surfaces Tested
Tubing samples (polymer extrusions)
Key Constraints
Minimal workflow disruption; high repeatability; 24/7 usability
The Challenge
Existing workflow
In one plant, inspectors measured contact angle to assess surface energy using an analog protractor method, manually aligning the midpoint of a water droplet to estimate angles.
Pain points
- Manual alignment and estimation increased human error.
- Limited repeatability in a manufacturing QC context.
- Measurement variance could be significant (reported around 5-10 degrees).
- Variance risked downstream adhesion issues and QC failures.
- Reduced confidence in QC documentation shared with partners.
Why it mattered
Errors at the 5-10 degree level could lead to poor adhesion between materials, compromised product functionality, and QC failures that disrupt downstream processes. Partners also rely on QC documentation to verify product integrity, so variance eroded confidence.
Success criteria
Achieve lab-grade measurement precision in a production environment with minimal training overhead and improved data traceability.
The Solution
What Was Deployed
A smartphone-based goniometer system sourced from Droplet Lab, selected for higher accuracy and improved usability in a production workflow.
Before vs After
Implementation
Timeline (high level)
Week 0
Discovery, sample review, and baseline understanding
Week 1-2
Guided demo and fit assessment with real sample geometry
Week 3-4
Custom holder delivery and first-site deployment
Month 2+
Continuous usage feedback and iterative refinement
Proof / Validation
Test method
Young Laplace Method
Sample size and operators
100+ samples across 3 operators
Repeatability / reproducibility
Gage R&R study completed
Results
Measured Outcomes
Old method
~±5–10° variance (manual analog estimation)
New system performance claim
up to 0.01° accuracy
Usage
Instruments used continuously for over three months at one facility
Operational Outcomes
Improved consistency: factory staff can achieve lab-grade style data more reliably
Improved partner confidence: more detailed, reliable QC reporting supports downstream trust
Continuous improvement enabled by real-world use: feedback informing software/hardware refinements
Client Quote
"Overall, we've been very impressed. It's been working really well and we really have enjoyed using it. It's a bit different than what we're currently using. It's much more technologically advanced than how we currently do it, which is good. Also, I wanted to let you know we completed our gage R&R study on the unit we have and it performed very well. We’ve been happy with the machine learning add in too, it saves a lot of time on measurements."— Corporate Quality Engineer, Development
What's Next
Delivered
Smartphone-based goniometers deployed (five units)
Custom tube holder delivered
Continuous use informing iterative improvements
In Pilot
ML baseline detection retraining using real-world image sets
Lighting redesign (brighter LED module; mount elevated by 2cm)
Splitters supplied to allow simultaneous charging and mouse usage
Planned
Desktop interface (medium-term)
Oracle ERP integration via API to eliminate manual entry
Longer-term migration toward RAW cameras (bypassing phones)
Client fabrication of collapsible enclosures using open-source designs and their machine shop