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MANUFACTURING · FOOD-MIX PRODUCTION

Same Root Causes, Four Different Workflows

Eye-tracking operational audit across production, warehousing, and pallet logistics

~15–20%
Non-productive time, all 4 workflows
+16%
Productivity gain potential, plant-wide
4
Workflows diagnosed, same root causes
6 min
Time to locate one raw-material item

The Client

Food-mix manufacturing plant with an integrated production line, raw-material warehousing, pallet logistics, and food-mix batch production.

Confidential case study — anonymized. Full details available under NDA upon request.

The Situation

The Intersect Approach

01

Eye-Tracking Operational Audit

Operators across all 4 workflows observed live with eye-tracking glasses — full process recordings and visual-attention data per workflow.

02

Root-Cause & Process Mapping

Per-workflow diagnostics plus cross-workflow pattern analysis, separating individual behavior from shared structural causes.

03

Prioritized Action Roadmap

Recommendations sequenced into Quick Wins (weeks 1–4), Medium-Term (months 1–6), and Long-Term (months 6–18), each tied to a workflow and an expected impact.

What We Measured — Evidence, Not Opinions

Estimated productivity improvement potential identified per workflow, based on the eye-tracking diagnostic.
Objective FindingMeasured Value
Non-productive time share, consistent across all 4 analyzed workflows≈ 15–20% per shift
Time to visually identify a single raw-material item on the floor (observed instance)6 minutes
Structural root causes shared across all 4 workflows3 — spatial disorganization, 5S deficit, absent SOPs — present in 100% of workflows analyzed
Estimated yield improvement potential, production line+15–20%
Estimated collection-rate improvement potential, raw-material collection+18–22%
Estimated cycle-time reduction potential, pallet identification & placement+20–28%
Estimated batch-efficiency improvement potential, food-mix production+12–18%
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Recommendations — Prioritized by Measured Impact

RecommendationRationale / Expected Impact
Delimit floor zones (collection, storage, forklift lanes, pedestrian corridors) with alphanumeric aisle/position codesQuick win (wks 1–4). Directly targets the spatial-disorganization cause found in all 4 workflows
Large shelf and pallet labels visible from rack height and forklift cabin, with scannable barcodesQuick win (wks 1–4). Removes the floor-wide searching behind the 6-minute identification time
Batch-registration form + weighing-tolerance guide posted above the scaleQuick win (wks 1–4), zero cost. Immediate quality-control impact in food-mix production
Redesign the HMI control panel — 5 core functions on the home screen, color-coded status indicatorsMedium-term (mo. 1–6). Reduces the multi-step navigation flagged on the production line
ABC slotting by turnover velocity + warehouse layout redesignMedium-term (mo. 1–6). Targets a 15–20% reduction in travel distance per shift
Full WMS integration — automated routing, real-time inventory, pick-path optimizationLong-term (mo. 6–18). Sustains the collection-rate gain beyond the pilot phase
Predictive IoT maintenance on production equipmentLong-term (mo. 6–18). Targets a 10–20% reduction in unplanned downtime
ISO 22000 / HACCP alignment, digital recipe screen, and batch-tracking systemLong-term (mo. 6–18). Builds a full audit trail on top of the new batch-registration discipline
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Why This Approach Works

All four workflows analyzed — despite covering different tasks, different equipment, and different teams — surfaced the same three root causes: no spatial organization, no 5S discipline, and no SOPs at the workstation. That pattern is the finding itself: these were not individual performance problems, they were structural gaps in the process design, repeated four times. Recommendations were sequenced by timeframe precisely because the causes were structural — floor markings and labels can be fixed in weeks; WMS integration and predictive maintenance take longer, but compound on the same root fix.

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