Reducing friction in factory work-order management
Operators and managers were dealing with a fragmented workflow for creating, assigning and tracking work. I redesigned the experience around how work actually moves through the factory.
Role
UX Designer
Company
Manufacturing / Industrial IoT
40%
Faster task handling
70%
Fewer manual errors
30%
Operational efficiency
Live previews
Overview and design context
I designed an AI-assisted operations platform that turns scattered, reactive maintenance into one connected flow — surfacing what's critical first, automating handoffs, and putting the right technician on the job with full context.
The Problem and scenario
Maintenance teams in high-stakes manufacturing operate without shared visibility work orders, data, and coordination scattered across disconnected tools, forcing every stakeholder to work in isolation under pressure.
The result: engineers spend more time documenting than fixing, ops heads can't track live progress or dispatch the right technicians, and service workers arrive under-informed — turning every failure into avoidable downtime and reactive firefighting.
Understanding the problem
Why solving this matters
Less downtime, more output straight to the bottom line
- Every minute of downtime costs money — when a machine stops, production stops. Faster fixes mean less lost output and lower costs.
- Clarity replaces chaos — one shared, real-time view helps teams act faster, make fewer mistakes, and reach the machine sooner.
- Reacting becomes preventing — a connected workflow spots patterns early, stopping repeat breakdowns before they happen.
Who are the users
Three teams, one broken handoff
| What they own | Where it broke | User set |
|---|---|---|
| Validate failures, create work orders | Buried in documentation instead of fixing | Plant Engineers |
| Assign technicians, track progress | No real-time view to act or allocate | Operations Heads |
| Resolve issues on-site | Arrived with incomplete repair context | Service Teams |
The business impact
Higher uptime, leaner operations, and smarter maintenance over time — every fix keeps machines running, cuts wasted spend, and builds data that moves the plant from reactive firefighting to predictive control.
| Stakeholder | What they own | Where it broke |
|---|---|---|
| Plant Engineers | Validate failures, create work orders | Buried in documentation instead of fixing |
| Operations Heads | Assign technicians, track progress | No real-time view to act or allocate |
| Service Teams | Resolve issues on-site | Arrived with incomplete repair context |
Solution & polished UI
01 / 03
~35–40% faster resolutionTask handling
Manual coordination delayed every work order
Prioritized, streamlined flow
02 / 03
Up to 70% fewer errorsManual errors
Scattered data caused frequent mistakes and rework
Single source of truth
03 / 03
~25–30% more efficientOperational efficiency
Reactive firefighting drained time and resources
Connected, real-time workflow
Conclusion and takeaways
From Chaos to Clarity
- I led the entire design from research to final UI
- Created lifecycle tracking, skill-based assignment, and real-time status updates.
- Improved response time by 40% & managers gained full visibility.
- Learned how to align multiple stakeholders and standardize workflows.