LAUNDRY MANAGEMENT SYSTEM · CATEGORY · TYPE
A hospital loses ₹50,000 a month to lost laundry. A student project went looking for why.
A final-year engineering capstone at CET, done with a team of four and guided by faculty, studying real laundry operations at KIMSHEALTH Hospital in Thiruvananthapuram. The core project covered data collection and predictive scheduling; UX research and UI design were Edwin's own addition on top of the required scope — an attempt to make the system's findings usable, not just documented.
- Engagement
- Academic capstone project — team of four, faculty-guided; UX research and UI design were Edwin's individual contribution, pre-uxbubble.
- Duration
- ~1 year
- Scope
- UX research and UI/UX design for a role-based hospital linen tracking system (nursing station, loading/unloading, washing, scheduling), layered onto a team project covering data analysis and predictive scheduling algorithms.
- Year
- 2024
Hospital laundry runs on paper logs and manual counts. At KIMSHEALTH Hospital, that meant no reliable way to track linen through its cycle — no visibility into where a batch was, whether it came back to the right department, or whether it was lost along the way.
This started as a final-year engineering capstone at CET, done with a team of four and guided by a faculty advisor. The core research — data collection at KIMSHEALTH, a literature review across prior studies on hospital laundry optimization, and the predictive scheduling algorithms — was team work, submitted for the Industrial Engineering degree.
UX research and UI design weren't part of the required scope. Edwin added them — the chance to take the team's findings past a spreadsheet and into something a nursing station, a loading point, or a washing area could actually use day to day. Roughly a year end to end, delivered in 2024.
Data collection at KIMSHEALTH surfaced three specific, quantifiable problems — not assumptions about what might be wrong, but numbers pulled from the hospital's own operations.
Based on primary data collected at KIMSHEALTH Hospital, cross-referenced against a review of 12 published studies on hospital laundry operations.
The only tracking system was a physical logbook
Every batch of linen moved through sorting, washing, drying, and folding with no digital record — just a general log kept in a book. That made it functionally impossible to say where a specific batch was at any given moment, or to confirm it came back to the correct department.
Sorting was the bottleneck, not washing
Sorting took an average of 56 minutes per load — about 22 seconds per cloth — and every downstream stage waited on it. Washing, drying, and folding weren't the slow points; the slowdown happened before any of them started.
Rewashing was quietly expensive
An average of 449 items were rewashed per day, roughly 17 per load. Each rewash meant the whole load waited longer and consumed washing capacity twice — a cost that never showed up as its own line item, because nothing was tracking it separately from normal throughput.
Nothing's deployed yet — what exists is a calculated estimate: ₹77,500–93,500 in monthly savings, projected from the hospital's own data.
The project reached prototype stage, developed alongside an internship at KIMSHEALTH and ongoing discussions with the hospital, but was never implemented into daily operations. There's no before-and-after to report — no measured drop in rewash rates, no tracked reduction in lost linen.
What can be said honestly: the team calculated the projected impact from real operational data — cloth loss reduction, faster turnaround, fewer manual errors — landing at an estimated ₹9.3–11.2 Lakhs annually if implemented. A projection, not a result, and worth reading as exactly that.
The project ended at prototype stage. No further discussions with KIMSHEALTH since the internship and academic submission concluded — the system exists as a validated concept with real data behind it, not as something moving toward deployment.
The math works. Nobody's tested it on a real Tuesday yet.