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Case Study: Root Cause Analysis Using Air Quality Data for a Leading FMCG Company

Industry: Consumer Goods / FMCG

Engagement Type: Targeted Air Quality Monitoring for Process Diagnostics


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🧩 Challenge


A leading consumer goods manufacturer faced recurring failures in a critical engineering process within its production line. Traditional diagnostic methods could not identify the root cause, prompting the need for a data-driven investigation into possible environmental factors.


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💡 Ai-DEA Labs’ Solution


Ai-DEA Labs deployed a targeted Indoor Air Quality (IAQ) monitoring solution featuring high-resolution CO₂ sensors to continuously track carbon dioxide concentration within the process area and industrial incubators.

The objective was to correlate CO₂ fluctuations with process deviations and identify whether air composition was affecting product stability or performance.


Solution Highlights


  • Precision CO₂ sensors with fine resolution for accurate analysis

  • Continuous data logging and trend visualization

  • Configurable alerts for CO₂ threshold exceedances

  • Data analytics to correlate process failures with environmental variations


⚙️ Implementation


  • 2 person-days of detailed system study

  • Solution deployed within one month

  • Data collected from industrial incubators and process zones

  • Integration with Ai-DEA Labs’ EMS for real-time monitoring and historical trend reports


🚀 Results & Impact


  • Identified CO₂ concentration as the key factor causing process instability

  • Detailed analytical report provided clear correlation between elevated CO₂ levels and failure events

  • Enabled precise corrective measures to maintain CO₂ within safe operational thresholds

  • Resulted in improved process reliability and reduced wastage


📊 Key Takeaway


By applying advanced air quality analytics, Ai-DEA Labs helped the customer pinpoint the root cause of process failures, demonstrating how intelligent environmental monitoring can directly support quality assurance and operational efficiency in manufacturing.

 
 
 

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