For Continuous Improvement
Turn station data into process gains.
Cycle time, idle time, error clusters, activity breakdown — continuous measurement for kaizen, not quarterly spreadsheets.
Your improvement projects start with a stopwatch. They shouldn't have to.
Your CI team runs improvement projects with stopwatches, spreadsheets, and floor walks. Time studies take weeks to plan, execute, and analyze. By the time you have results, the process has already shifted.
You need continuous, automatic measurement at every station, every shift — not point-in-time snapshots that are stale before you act on them. And you need before/after data that proves the gain, not anecdotal feedback that it "feels faster."
WMS data tells you what shipped. It doesn't tell you cycle time per station, idle time between orders, or which operators follow the standard work. The data an IE team actually needs doesn't exist in your current systems.
The breakthrough
40% faster pack times.
Yusen Logistics, a company built on kaizen-based performance improvement, deployed Rabot to gain real-time visibility into packing operations — and measured a 40% improvement in pack times without changing existing workflows.
Continuous measurement at every station. Every shift. Every process change.
Continuous time-and-motion data
Cycle time, idle time, activity breakdown captured automatically at every station, every shift. No stopwatches. No sampling. No observer effect. The data is always on.
Bottleneck identification
See exactly where time is lost: between orders, during dunnage, waiting on exceptions. Per-station activity data reveals what floor walks miss. Prioritize improvements by impact, not gut feel.
Before/after measurement
Run a kaizen event, see the result in station data the next day. No waiting for quarterly reviews. Prove the gain. Sustain it. Catch regression the moment it starts.
Standardized work verification
Verify operators follow the standard work via Pulse work instructions. Measure adherence, not just output. When the standard work changes, the system updates every station immediately.
Customer story
Yusen Logistics measured a 40% improvement in pack times — without changing workflows.
Yusen Logistics, a global leader in end-to-end supply chain solutions with kaizen-based performance improvement at its core, deployed Rabot's Vision AI platform at their Hardeeville, South Carolina facility to gain real-time visibility into packing operations.
During the pilot, the platform analyzed over 5,000 orders, surfacing improvement opportunities that were previously invisible. Productivity insights and bottleneck identification came without changing existing workflows — the data simply made better decisions possible.
40%
Faster pack times
5,000+
Orders analyzed in pilot
0
Workflow changes required
"Our partnership with Rabot reflects Yusen Logistics' continued focus on innovation and operational excellence for our customers. Rabot's Vision AI platform provides actionable, data-driven insights that help us improve pack accuracy, enhance productivity, and better support our frontline teams."
Rick Brunelle
Director of Automation, Yusen Logistics (Americas) Inc.
Measured. Improved. Sustained.
DaVinci
30%
Processing time decrease
DaVinci
7.5% to 2%
Exception rate
Staci Americas
33% across 19 stations
Productivity increase
Staci Americas
69%
Pack speed improvement
See your first week of station data.
Install in one day. No WMS changes required. Start measuring what actually happens at every station from day one.