Batch Mix-Up Detection JIG

Objective: Prevent batch and line mix-ups via Automatic QR Scanning JIG.

DEVELOPED BY

P. Lakshmana Sai Kaushik

QA Supervisor

Molbio Diagnostics Limited

October 2025 – December 2025

💡 KEY VALUE PROPOSITION

Automated in-house jig that eliminates batch and line mix-ups — delivering 100% verified accuracy with zero additional cost.

PROJECT STATUS

✅ Testing Complete — Ready for Handover

100%

Accuracy

0

False Rejections

300+

Cartridges Tested

QR Validation

📊

Full Traceability

📋 The Challenge

Creates traceability gaps and operational inefficiencies

6+

Mix-up Incidents

Repeated across multiple batches

🔍

Root Cause

Wrong batch, wrong mould, cross-line mix-up & QR tampering

Risk Level

CRITICAL

⚠️ Manual verification alone is not reliable.

📊 CPSR Today

Scans and counts QR codes; does not validate Line ID, Batch, or QR range.

👤 Manual Checks

Inconsistent for wrong batch, cross-line mix-ups, or tampered labels.

⚠️ Result

Rework, delays, and traceability gaps.

📋 QMS Traceability Issues

Due to mix-ups: delays in closures, reworks, batch compilation errors

Common Mix-up Scenarios:

▸ Wrong batch▸ Wrong mould▸ Cross-line mix-up▸ QR tampering

💡 The Solution

Automatic QR Scanning JIG that prevents batch mix-ups without operator intervention

🎯 Our Solution: Automatic QR Scanning JIG

We developed an intelligent QR Scanning JIG that automatically validates every cartridge and prevents batch mix-ups without any operator intervention.

How Our JIG Works

1. Scans QR Code

GM65 scanner reads the 14-character QR code from each cartridge

2. Validates Automatically

System checks if QR belongs to current batch (Line ID, Batch Range, Format)

3. Auto-Diverts Cartridges

Based on validation result, ACTJ actuators automatically route cartridges to PASS bin or REJECT bin

4. Zero Operator Intervention

No manual decisions required — fully automated validation and routing

How It Reduces Batch Mix-ups

🔍 Line ID Validation

Extracts Line ID from QR Position 2 → Ensures cartridges from Line A don't mix with Line B

📊 Batch Range Check

Validates QR is within configured Start/End range → Rejects wrong batch cartridges

🔄 Duplicate Detection

Tracks scanned QRs in session → Prevents re-scanning same cartridge multiple times

🎯 Format Validation

14-char alphanumeric check → Rejects invalid or tampered QR codes

Key Features of Our JIG

💡 LED Visual Indicators

GREEN = Pass | YELLOW = Duplicate | RED = Reject — Instant visual feedback for operators

🔊 Buzzer Sound Alert

Audible beep for rejected cartridges — Alerts operator immediately when issues detected

📺 Tkinter UI Display

Real-time statistics visible on JIG screen:

  • • Total Scanned: Live count of all scanned cartridges
  • • Batch Number: Current batch being processed
  • • Pass Count: Number of validated cartridges
  • • Reject Count: Number of rejected cartridges
  • • Duplicate Count: Already scanned QRs detected
  • • Timeline: Session duration and time tracking
  • • Last Scanned QR: Most recent QR code processed

🔧 Multi-Mould Batch Support

Handles batches with multiple moulds — Configure QR ranges for 1, 2, 3+ moulds per batch seamlessly

🌐 Flask Web Dashboard

Remote access to scan logs via browser (:8080) — View history, download CSV reports, audit trail

📋 Complete Traceability

CSV logs + SQLite database — Every scan recorded with timestamp, batch, result, operator details

💾 Auto-Resume & Data Persistence

Zero data loss even during power interruptions:

  • • Automatic State Recovery: JIG resumes from last scanned QR when powered back on
  • • Count Preservation: All counts (total, pass, reject, duplicate) retained in database
  • • Session Continuity: Display shows exact state before shutdown — no manual re-entry needed
  • • Persistent Storage: SQLite database ensures no scanned data is ever lost

→ Operators can continue exactly where they left off, maintaining workflow continuity

🎯 Implementation Strategy

By implementing this QR Scanning JIG in our production line, we can eliminate batch mix-ups and automatically detect cartridges mixed in wrong batches.

We used the existing ACTJ Jig for automated detection — it scans QR codes, validates Line ID, Batch range, and format in real-time, then automatically routes cartridges to PASS or REJECT bins. No manual intervention; zero human error.

System Architecture

🔧

ACTJ JIG

📱

GM65 Scanner

🔍

Python Validation

🎛️

ACTJ Routing

📊

Flask Dashboard

⚙️ Batch Configuration Example

Real Batch Setup

📦 Batch Number: MVANC00045

📍 Batch Line: A (Line A)

🔧 Number of Moulds: 3 Moulds

🧭 Allowed Range:

VAN142536A0001 → VAN142536B9999

✅ PASS Examples

✅ VAN142536A0001 — within range

✅ VAN142536A5000 — within range

✅ VAN142536B0002 — within range

❌ REJECT Examples

❌ VAN142536C0003 — outside allowed range

❌ VBN142536B0100 — wrong line

❌ VAN142536A0001 — already scanned ⚠️ DUPLICATE

🎯 How the Validation Logic Works

1

Configure QR Start (VAN142536A0001) and QR End (VAN142536B9999) for the batch

2

When QR is scanned, system checks: Is it within this range?

3

Extract Line ID from Position 2 of QR → Compare with batch line (A)

Both checks pass → GREEN (PASS) | Any check fails → RED (REJECT)

✅ 4-Level Validation Process

1

📝 Format Validation

Check: QR must be exactly 14 alphanumeric characters

Rejects: Wrong length, special characters, spaces

Result: RED light if failed

2

🔤 Line ID Validation

Check: Does extracted Line ID match configured Batch Line?

Logic: Extract character at Position 2 from scanned QR code (A-Z)

Example: QR = VAN142536A0001 → Line = A | If batch is Line B → REJECT

Result: RED light + reject bin if Line mismatch (cross-line mix-up detected)

3

📊 Batch Range Validation

Check: Is scanned QR within this range? (e.g., VAN142536A0001 to VAN142536B9999)

Logic: Operator sets QR Start Number & QR End Number per batch

Decision: Within range → PASS | Outside range → REJECT

Result: RED light + reject bin if out of range

4

🔄 Duplicate Detection

Check: QR not previously scanned in current session

Prevents: Re-scanning same cartridge multiple times

Result: YELLOW light if duplicate, GREEN if all checks pass

📌 Current Situation & Why This Solution Works

How we addressed each gap in the existing system

❌ Existing CPSR Limitation

Only scans QR and counts — no Line ID, Batch, or QR validation

❌ Manual Verification

Cannot reliably catch cross-batch or cross-line mix-ups; slow and error-prone

✅ Range-Based Validation

Set QR Start/End → Within range = PASS | Outside = REJECT + Line ID check

✅ Physical Auto-Routing

ACTJ actuators route PASS/REJECT automatically — no human decision errors

✅ Full Traceability

CSV + SQLite + Flask dashboard — remote audit without touching the jig

🎯 Goal Achieved

Intelligent validation (Line, Batch, Range) prevents mix-ups — zero added cost

🧠 The Core Logic & How The System Works

🔐 Validation Logic Added

1️⃣ Set QR Start & End Numbers for each batch

(defines valid range)

2️⃣ Scanned QR within range?

✅ PASS | Outside? → ❌ REJECT

3️⃣ Extract Line ID from QR (Position 2)

→ Match with batch line

4️⃣ Line mismatch?

→ Immediate REJECT (prevents cross-line mix-up)

🛠️ What Stayed the Same

No hardware or firmware changes. The same ACTJ/CPSR jig and components are reused.

A Python validation layer on Raspberry Pi validates Line ID, Batch Range, and QR format/duplicates. Jig control remains unchanged.

Complete Process Flow

1️⃣

Batch Configuration

Operator inputs: Batch Number, Line ID, Mould count, QR Start/End ranges

2️⃣

QR Scanning

GM65 scanner reads 14-char QRs; system validates & auto-routes to bins

3️⃣

4-Level Validation

Format → Line ID → Batch Range → Duplicate checks ensure only correct cartridges pass

4️⃣

Visual Feedback & Routing

GREEN (pass), YELLOW (duplicate), RED (reject) + ACTJ auto-diversion to bins

📊 Test Results & Performance

15

Test Cycles

300

Cartridges Tested

100%

Accuracy

3.15s

Cycle Time

🎯 Perfect Performance

✓ Zero False Rejects

✓ 100% Detection Rate

✓ Real-time Validation

⚙️ Technical Specifications

🖥️ Processor

Raspberry Pi 3B+

📱 Scanner

GM65 QR Scanner

🔧 JIG CPSR

Automated Routing System

⚙️ Software

Python 3 + Tkinter

🗄️ Database

SQLite + Auto-Resume (scan_state.db)

🌐 Dashboard

Flask Web (:8080)

✨ Key Benefits

💯 Zero Mix-Ups

100% accurate validation ensures cartridges never go to wrong batch

💰 No Investment

Uses existing jig + Raspberry Pi, zero capital expenditure

📊 Full Traceability

CSV + SQLite + Flask dashboard provides complete audit trail

⚡ Fast & Efficient

Average 3.15 seconds per cartridge processing time

🔄 Zero Disruption

No changes to existing ACTJ/CPSR firmware or hardware

💾 Auto-Resume

Power-safe design — JIG resumes from last scan after shutdown, no data loss

🤖 Operator Empowerment

Instant LED + buzzer feedback. Operators focus on action, not manual QR checks.

📈 Project Impact & Value

🛡️ Problems Prevented

  • • Avg 2–3 hours delay per incident
  • • Rework + QA investigation time
  • • Material waste + rejected cartridges

Prevents downtime and rework

♻️ Smart Resource Utilization

  • • Used existing ACTJ/CPSR infra
  • • Raspberry Pi & scanner from maintenance
  • • 100% in-house development

Zero additional resources needed

💯

100%

Accuracy

0

Mix-ups

📦

300+

Cartridges Validated

3.15s

Avg Cycle Time

⏱️ Project Timeline

1

Concept Approval & Material Procurement

📅 Oct 6-7, 2025

Project proposal submitted and approved by QA Manager. Hardware procured: Raspberry Pi 3B+, GM65 Scanner, SD Card from Maintenance Team

2

Prototype Completion

📅 Oct 9, 2025

Prototype model completed and functioning. Demo video shared with stakeholders. Approval received for ACTJ integration and USB access

3

BigTec Collaboration

📅 Oct 10-14, 2025

Source code received from BigTec Labs (Salman Khaja). Software integration with existing ACTJ firmware (v2.6) — no firmware modifications

4

System Integration Complete

📅 Nov 19, 2025

Jig successfully integrated with CPSR. Demo with real-time run completed. 300 cartridges approved for validation testing

Testing & Performance Evaluation

📅 Nov 20 - Dec 2025

Completed: Performance evaluation with 300 cartridges. Cycle time tested: 1 min 03 sec per 20 cartridges

🙏 Acknowledgments

Leadership & Key Stakeholders

👔

Plant Head

G. Uday Bhaskar

GM-Operations

🎯

QA Management

Hameed C.R.

Assistant Manager - QA

🛠️

Design Team Lead

Gompa Naidu

HOD - DI

⚙️

Technical Support

S. Chakravarthi

Maintenance Site-III

🌟 Key Contributors

Essential Team Members & Support

🔧 BigTec Labs

Salman Khaja

Source Code & Integration

🏭 Production Lead

Santosh Yavvari

Inputs & Guidance

💻 IT Support

Raj Kumar Kanithi

USB Access & IT Infrastructure

📦 Materials Team

G. Bala Sri Ram & Vadlapudi Ramya

Cartridge Provision for Testing

🔧 Maintenance Team

Sanjeev Varma, Bhargav, Sri Ram, Yeswanth & Team

Technical Support & Field Troubleshooting

💖 Special Thanks

🌟

CH. Praneet Raj

For bringing this idea into focus and supporting every step of this journey. Your mentorship and guidance were instrumental in making this project a success.

🏆

Champions 2.0 Initiative

This project is my Champions 2.0 initiative task — an end-to-end improvement project under the program led by GM-Operations, G. Uday Bhaskar.

It demonstrates how every new joiner can implement a meaningful, impactful solution from conception to deployment, delivering measurable value to the organization.

✓ Built-in Prevention • ✓ Zero Cost • ✓ Full Traceability • ✓ Production Ready

🙏 Thank You!

✨ Testing Complete — Concept Proven

🎯 Test Results Summary

300 cartridges tested

100% detection accuracy

Zero false rejections

⏱️ Performance Tested

1 min 03 sec

per 20 cartridges

🎯 Quality Impact

Eliminates batch mix-up risk

Full traceability maintained

Complete audit documentation

🤝 Next Phase — Concept Validation Complete

Prototype successfully tested with proven performance metrics validated across diverse batch scenarios.

🔄 Production Implementation

If deemed valuable for production lines, this concept can be implemented and scaled with BigTec's support for system integration and deployment.

💡 Key Advantage

Zero production line disruption during implementation

Prototype Validated

Performance Proven

Ready for Next Implementing

💡 Final Message

Built-in prevention, compliance, and traceability — embedded in the process.

🎯 What We Achieved

Automated prevention

with zero cost

100% verified

accuracy

Complete

traceability

🏆 Champions 2.0 in action

👤 Regards

P. Lakshmana Sai Kaushik

QA Supervisor

Molbio Diagnostics Limited - SITE III