MOBILE / CAMP & Honeywell Oil Analysis
CAMP Systems — Eliminating Paper from Aircraft Oil Analysis
THE PROBLEM
Paper checklists were the problem. Errors, delays, and resubmissions.
Honeywell partnered with CAMP Systems to modernize the oil and filter sample submission process for aircraft maintenance teams. Paper checklists were creating frequent identification errors, incorrect filter usage, and costly resubmissions — in an industry where a missed maintenance signal is a safety and compliance risk. I was brought in as the sole UX designer to replace the paper process entirely with a guided mobile experience, live on Google Play.
THE CORE TENSION
Aviation maintenance demands zero-error data. The workflow had no way to enforce it.
In aircraft maintenance, a wrong filter or incomplete submission doesn't just cause rework — it compromises engine health data and delays safety diagnostics. I brought this framing to product and engineering before any design work began, making the case that every UI decision had to close the error gap at the point of entry, before mistakes reached the lab.
CHALLENGE
Complaints were surface-level. The real issues ran deeper.
Technicians described delays and missing context but couldn't articulate why — they had normalized the friction and worked around it daily. I ran workflow observations to get past the surface complaints and map what was actually breaking the process.
RESPONSE
Latent needs the users didn't know to request.
I collaborated with maintenance teams to map real-world workflows, then brought findings to product and engineering before any forms were designed. Validation logic and guided entry were specified against actual submission failure patterns — not assumed pain points.
MY ROLE
Led UX research and design for CAMP Systems — from workflow analysis and field research through mobile UI and final handoff.
WHAT I OWNED
End-to-end UX — workflow analysis with maintenance teams, wireframes, interactive prototypes, modular UI component design, contextual filter recommendation logic, lab proximity mapping, and final mobile UI screens.
HOW I WORKED
Designed for the CAMP Systems platform — the primary interface where operators view SOAP results, compliance, and engine trend reports. I worked directly with engineering to align on integrations with Honeywell's HEAT and HDA diagnostic toolkits, Ensemble for real-time data transmission, and Forge IoT APM for predictive engine health analytics — so design specs accounted for real data behavior before any screens were finalized.
THE CONSTRAINT
Aviation maintenance has zero tolerance for data errors. Every UI decision — validation logic, filter selection guidance, lab routing — had a direct downstream impact on sample accuracy, turnaround time, and technician safety confidence in the field.
OUTCOMES
Streamlining oil sampling and reducing errors — the GoDirect SOAP app shipped on Android.
REDUCED ERRORS & RESUBMISIONS
Guided input and validation logic eliminated duplicate entries and filter misidentification — the primary drivers of costly resubmissions. Fewer errors at point of entry means fewer failed samples reaching the lab and lower rework cost per submission.
IMPROVE SAMPLE ACCURACY
Filter-hour calculations, contextual recommendations, and lab proximity routing reduced errors that compromised data integrity in the field. Accurate samples mean faster, more reliable engine health decisions for every aircraft in the maintenance program.
FASTER MAINTENANCE DECISIONS
Real-time filter-hour calculations and lab routing gave technicians the information they needed at point of collection — not after a failed submission. Maintenance teams received cleaner data faster, reducing the lag between sample submission and actionable engine health decisions.
LIVE ON GOOGLE PLAY - ANDROID
The GoDirect SOAP app is available for Android on the Google Play Store.
PROJECT GALLERY
From field research notes to live submission app on Google Play
Research Notes
Concept Sketch
Final Design
What I'd do differently
Get into the field earlier. The most valuable insights came from watching technicians work in real conditions, but that happened later in the process than it should have. Earlier field access would have shaped the validation logic and filter guidance from the start. I'd also push for testing against real lab workflows before handoff, not after. Edge cases in sample routing and filter selection only surfaced once the system met actual submission conditions.