Data Collection & Scoping

Verifone

POS terminal repair, refurbishment, and lifecycle management across three Reconext facilities. This page provides the complete data collection playbook for deploying the multi-modal AI optimization loop on the Verifone program.

3 SitesPOS TerminalsMulti-SKUCross-Border Logistics

Facility Locations

🇲🇽

Reynosa

Tamaulipas, Mexico

High-volume processing facility near the US-Mexico border. Handles bulk POS terminal intake, testing, and component-level repair with cross-border logistics integration.

Primary — largest volume
Data Collection: Week 1–2
🇲🇽

Mexico City

CDMX, Mexico

Central Mexico operations hub supporting Verifone device refurbishment, quality assurance, and regional distribution for the Latin American market.

Secondary
Data Collection: Week 3
🇺🇸

Grapevine

Texas, USA

US-based facility managing Verifone program coordination, advanced diagnostics, customer-facing quality gates, and North American fulfillment.

Secondary
Data Collection: Week 4
Per-Site Checklist

Data Collection Checklist

Complete this checklist for EACH of the three Verifone sites. Every item must be completed before the AI model can begin processing.

Spatial / 3D Capture

6 items
1
Schedule Matterport Pro3 scan of entire facility (all areas where Verifone devices are processed)
2
Capture receiving dock, incoming inspection, test stations, repair benches, cosmetic grading, packaging, and shipping
3
Ensure scan covers material flow paths between areas — the AI needs to understand physical layout
4
Export as Matterport Digital Twin (.e57 point cloud + web link)
5
Minimum resolution: 4K (3840x2160) per scan position
6
Estimated time: 4–6 hours per site depending on facility size

Video Capture

9 items
1
Record 15–30 minute continuous video at EACH workstation type (test, repair, cosmetic, packaging)
2
Capture at least 2 full shifts to show variation between operators and shift patterns
3
Resolution: minimum 1080p (1920x1080), preferred 4K. Frame rate: 30fps minimum
4
Landscape orientation ONLY — mount iPad/iPhone on tripod at operator eye level
5
Include wide-angle establishing shots showing the full line layout (1 per area)
6
Capture close-up detail shots of hands-on operations (component-level repair, soldering, testing)
7
Record dock-to-stock flow: follow a batch of POS terminals from receiving through to shipping
8
Include audio — capture ambient sound, machine noise, and operator communication
9
Label each video file: {SITE}_{AREA}_{STATION}_{DATE}_{SHIFT}.mp4

Plus (MES) / IFS (ERP) Data

10 items
1
Extract 30 days of production data from Plus covering the video capture period + 30 days prior
2
Include: production orders, cycle times per station, defect/failure codes, yield rates, throughput per SKU
3
Extract equipment BST (Bill of Standard Times) data for every station captured on video
4
Pull operator performance data (anonymized by operator ID) for the same period
5
Extract defect/failure code distributions with counts and rates per station per SKU variant
6
Export material flow data: units received, units processed, units shipped per day
7
Pull IFS data: cost per unit, material costs, labor costs, CAPEX/OPEX for Verifone program
8
Generate data dictionary listing every field, type, unit, and meaning
9
Export in JSON (API) + CSV (bulk) formats
10
Configure MCP connector for real-time Plus data access (if not already done)

Audio Capture

6 items
1
Deploy audio recording devices at each major work area (test, repair, cosmetic, packaging)
2
Record minimum 2 hours continuous per area during peak production
3
Format: WAV (uncompressed), 44.1kHz sample rate, 16-bit depth minimum
4
Capture machine sounds (test equipment cycling, pneumatic tools, conveyor belts)
5
Capture ambient noise levels at different times of day
6
Label each file: {SITE}_{AREA}_{DATE}_{TIME_START}-{TIME_END}.wav

Equipment & Labor Data

7 items
1
Complete equipment registry: every machine, test station, and tool used in Verifone processing
2
Include: equipment ID (matching Plus), make/model, age, PM schedule, last PM date, condition rating
3
Export PM completion logs and downtime logs with reason codes for the past 6 months
4
Compile labor roster: operator ID, role, contract type, shift assignment, hire date, certifications
5
Export skill/certification matrix: which operators are qualified for which stations and SKUs
6
Pull CAPEX records for equipment purchases in the past 24 months
7
Export OPEX data: maintenance costs, consumables, tooling replacement costs per station

Enrichment Data

7 items
1
Collect BOMs (Bill of Materials) for every Verifone SKU variant processed at the site
2
Gather technical spec sheets for each device model (component specs, test parameters, tolerances)
3
Compile all work instructions (WIs) for each operation (test, repair, cosmetic grading, packaging)
4
Collect quality standards and grading criteria documents
5
Gather any existing process flow diagrams or value stream maps
6
Include customer (Verifone) requirements documents and SLAs
7
Collect any existing training materials for new operators

Folder Structure

Copy this exact folder structure for each site. The AI model expects this consistent organization to cross-reference data across modalities.

📂 Verifone/
  📂 Reynosa/
    📂 01_Spatial/
      📄 matterport_scan_{DATE}.e57
      📄 matterport_web_link.txt
      📄 floor_plan_annotated.pdf
    📂 02_Video/
      📂 receiving/
      📂 test_stations/
      📂 repair_benches/
      📂 cosmetic_grading/
      📂 packaging_shipping/
      📂 establishing_shots/
      📄 video_index.xlsx
    📂 03_Plus_IFS_Data/
      📂 raw_exports/
      📂 aggregated/
      📄 data_dictionary.xlsx
      📄 mcp_config.json
    📂 04_Audio/
      📄 {AREA}_{DATE}_{TIME}.wav
    📂 05_Equipment_Labor/
      📂 equipment/
      📂 labor/
      📂 financial/
    📂 06_Enrichment/
      📂 boms/
      📂 spec_sheets/
      📂 work_instructions/
      📂 quality_standards/
    📄 collection_checklist.xlsx
    📄 README.md
  📂 Mexico_City/
    📂 (same structure as Reynosa)
  📂 Grapevine_TX/
    📂 (same structure as Reynosa)

7-Day Collection Sprint

Execute this sprint at each site. The Dream Team travels to each facility and completes all data collection within 7 business days.

Day 1
Matterport 3D scan of entire facility (4–6 hours)
Set up video capture equipment at all stations
Day 2
Video capture: Shift 1 — all stations (test, repair, cosmetic, packaging)
Audio recording deployment across all areas
Day 3
Video capture: Shift 2 — all stations (variation capture)
Dock-to-stock flow recording (follow batch end-to-end)
Days 3–5
Plus (MES) data extraction via API/MCP
IFS (ERP) data extraction
Equipment registry and labor roster compilation
Days 5–7
Enrichment data collection (BOMs, spec sheets, WIs, quality standards)
Data validation and cross-referencing
Upload to shared folder structure and complete checklist

AI Optimization Targets

Line balancing across multi-station POS repair workflows
Takt time optimization per SKU variant (different device models have different complexity)
Component harvest vs. whole-unit repair decision modeling
Cross-site workload distribution and capacity planning (Reynosa vs. Mexico City vs. Grapevine)
Defect pattern recognition across device generations
Operator skill-to-station matching optimization
Material flow path optimization (minimize travel distance between operations)
Test station utilization and bottleneck identification
Shift-to-shift performance variance reduction
Predictive maintenance scheduling based on equipment usage patterns

Dream Team Verifone Assignments

What each Dream Team member specifically does for the Verifone data collection and optimization deployment.

AI Model Coach

Define optimization targets specific to POS terminal workflows (takt time per SKU, harvest vs. repair thresholds)
Validate that video captures show representative production conditions (not staged or atypical shifts)
Review initial AI outputs and provide structured feedback on line balancing and bottleneck recommendations
Design cross-site comparison experiments (Reynosa vs. Mexico City vs. Grapevine performance)

Data Capture Specialist

Operate Matterport Pro3 for 3D scans at all three sites (travel required)
Set up and manage video capture equipment (iPad/iPhone tripod mounts) at each station
Extract Plus data via API for all three sites — ensure consistent field mapping across sites
Configure MCP connector for real-time Plus data access from each site's instance
Deploy audio recording devices and manage file naming conventions

Operations Analyst

Coordinate with site managers at each location to schedule data collection during representative production days
Compile equipment registries and labor rosters from each site (may require local HR/ops support)
Map the current process flow at each site — identify site-specific variations in the Verifone workflow
Track collection progress against the checklist and flag any gaps before the team leaves each site

Engineering & Quality Lead

Collect BOMs for every Verifone SKU variant processed across all three sites
Gather work instructions and quality standards — note any site-specific variations
Validate that test parameters and tolerances are documented for each device model
Ensure defect code definitions are consistent across all three sites in Plus

Project Manager

Plan the 4-week travel schedule: Reynosa (Week 1–2), Mexico City (Week 3), Grapevine (Week 4)
Coordinate logistics: travel, site access, equipment shipping, local contacts
Run daily standups during each site sprint; produce end-of-sprint completion reports
Manage the master checklist across all three sites — ensure nothing is missed

Key Risks & Mitigations

Cross-border data transfer (Mexico → US)

Mitigation: Ensure data is stored on compliant cloud storage; verify no PII in video captures; use encrypted transfer

Site-specific Plus instances may have different field mappings

Mitigation: Data Capture Specialist validates field consistency across all three sites before extraction

Video capture during non-representative production days

Mitigation: Operations Analyst coordinates with site managers to schedule during normal production volume

Incomplete BOM coverage across all SKU variants

Mitigation: Engineering Lead cross-references Plus SKU list against collected BOMs; flags gaps immediately