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Manufacturing verified Verified Outcome TRL 9

Digital Twin for Manufacturing Process

domain Client: A major CPG bottling company handshake Provider: Microsoft Azure schedule Deploy: Q2 2021 (Scale)
88 Impact
Enterprise Ready
Evidence Score: 5/10
Strength: High

Executive Summary

ANALYST: COI RESEARCH

To optimize production across 56 plants, the bottler implemented Azure Digital Twins. By creating virtual replicas of the filling lines, they analyze sensor data to simulate production scenarios, predict energy consumption, and identify bottlenecks without disrupting physical operations.

rate_review Analyst Verdict

"Moving beyond dashboarding to true simulation. The Digital Twin allows for 'what-if' analysis (e.g., 'What if we increase speed by 5%?') that physical testing prohibits. It is a key enabler for energy efficiency and carbon reduction goals."

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Full Audit Report Available Includes Risk Register, Technical Specs & Compliance Data.

warning The Challenge

Production lines are complex systems; a small tweak in the filler can cause a jam in the labeler. Operators relied on experience rather than data to tune lines. Energy usage was measured at the plant level, not the machine level, making optimization difficult.

psychology The Solution

IoT sensors on machines stream data to Azure IoT Hub. Azure Digital Twins models the relationships between machines. Azure Synapse analyzes the data to recommend settings adjustments. Mixed Reality (HoloLens) is used for remote expert support on the twin.

settings_suggest Technical & Deployment Specs

Integrations
Siemens/Rockwell PLCs
Deployment Model
Hybrid Cloud
Data Classification
Industrial IoT
Estimated TCO / ROI
High
POC Summary (2019-01-01 to 2020-01-01)

"Pilot at a single plant in Austria."

shield Risk Register & Mitigation

Risk Factor Severity Mitigation Strategy
Data Latency Medium Edge computing for real-time control loops.
Model Accuracy Medium Continuous recalibration of the twin against physical reality.

trending_up Impact Trajectory

Audited value realization curve

Digital Twins of 26 production lines Verified Outcome
Primary KPIMeasurable reduction in energy/water usage
Audit CycleIncrease in Overall Equipment Effectiveness (OEE)

policy Compliance & Gov

  • Standards: Manufacturing Standards
  • Maturity (TRL): 9
  • Evidence Score: 5/10
  • Data Class: Industrial IoT

folder_shared Verified Assets

description
Verified Case Study
PDF • Version 1
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Technical Audit
PDF • Audited
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The "Blind Verification" Protocol

How we verified these outcomes for A major CPG bottling company without exposing sensitive IP or identities.

Private
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1. Raw Evidence

Audit ID: #PRIV-839
Evidence: Direct SQL Logs
Public
public

2. Verified Asset

Outcome: Verified
Ref ID: #COI-839

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