Eye-tracking and cognitive-operational diagnostics across an entire steel-processing plant
Industrial manufacturer specializing in steel processing and structural steel components, with integrated production functions spanning assembly, welding, metal stamping, bending, painting, and internal logistics.
Confidential case study — anonymized. Full details available under NDA upon request.
Operators across 8 functions wore eye-tracking equipment during normal operation — attention, focus, engagement, awareness, alertness.
Findings broken down by role and shift, separating attention gaps from layout- and process-driven time loss.
Quick-win and medium-term recommendations, ranked by measured impact — not by visibility.
| Objective Finding | Measured Value |
|---|---|
| Time spent searching for tools/parts vs. producing, worst-case assembly operator (1st shift) | ≈ 50% of a 12-minute observed cycle spent searching, not producing |
| Time lost to component searching, assembly operators (2nd shift) | ≈ 20% of observed task time |
| Time spent on individual order transport by warehouse clerk vs. batched delivery | 40% of a 33-minute observed shift spent moving single orders one by one |
| Productive vs. non-productive time, forklift logistics (2 operators tracked) | ≈ 75% driving/idle/scanning vs. ≈ 25% productive lifting and handling |
| Dead time from traveling to another section to retrieve components (truck-loading operator) | ≈ 7–10% of observed cycle |
| Spread of individual attention and alertness scores across operators (0–1 scale) | Attention 0.18–0.99; Alertness 0.12–0.99 — wide, undocumented variance across the floor |
| Recommendation | Rationale / Expected Impact |
|---|---|
| Pre-stage tools & parts in assembly, bending, and painting | Directly targets the 20–50% search-time loss measured in assembly and stamping |
| Standardize pallet placement for forklift operations | Eliminates random searching behind the 75% non-productive forklift time |
| Batch collection & delivery for warehouse clerks | Reduces the 40% of clerk time spent on individual order trips |
| Workstation organization — shadow boards, labels, visual cues | Converts already-high measured engagement into productive output |
| Factory layout redesign for material flow (medium-term) | Reduces walking/driving distances hall-wide |
| Shift-level KPIs & dashboards | Addresses the measured alertness variance and the prior lack of monitored targets |
| Cross-train high-performing operators as coaches | Spreads the best-measured cognitive-operational profiles across shifts |
The difference from a conventional operational-efficiency review was not the improvement toolkit itself — layout redesign and standardized work are well-known instruments. The difference was the starting point: instead of manager interviews and assumptions, the diagnosis began with objective, minute-by-minute measurement of what operators actually did. Eye-tracking showed exactly where time and attention went — not where management assumed it went — and recommendations were prioritized by measured impact (time × frequency), not by which problems were most visible on a walkthrough.