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Manufacturing verified Verified Outcome TRL 9

Industrial Data Fabric for Factory Digital Twins

domain Client: A global technology and manufacturing conglomerate handshake Provider: Siemens Xcelerator / Snowflake schedule Deploy: Q2 2022 (Launch)
91 Impact
Enterprise Ready
Evidence Score: 5/10
Strength: High

Executive Summary

ANALYST: COI RESEARCH

To bridge the gap between Information Technology (IT) and Operational Technology (OT), the company implemented an Industrial Data Fabric. This architecture virtualizes data access across disparate factory systems (ERPs, PLCs, MES), treating factory data as a consumable product for the 'Industrial Metaverse' and predictive maintenance apps, without requiring massive data replication.

rate_review Analyst Verdict

"The solution to the 'Brownfield' problem. Most factories run on legacy legacy systems that cannot be easily replaced. A Data Fabric approach leaves data where it is but creates a virtualized 'product' layer on top, enabling modern analytics on legacy hardware."

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

warning The Challenge

Factory data was locked in proprietary silos (machines, SCADA). Creating a 'Digital Twin' required manual data extraction and cleaning, which was obsolete by the time it was finished. There was no standardized way to query 'Machine State' across different plant locations.

psychology The Solution

The Data Fabric connects to various data sources using specialized connectors. It applies a semantic layer (ontology) to normalize the data (e.g., defining what 'temperature' means across different sensor types). This governed data is served as a product to the Digital Twin application.

settings_suggest Technical & Deployment Specs

Integrations
Teamcenter, SAP
Deployment Model
Hybrid Cloud
Data Classification
Industrial IoT
Estimated TCO / ROI
High
POC Summary (2020-01-01 to 2021-01-01)

"Internal deployment at Amberg plant."

shield Risk Register & Mitigation

Risk Factor Severity Mitigation Strategy
Semantic Complexity High Industry standard ontologies (OPC UA).
Latency Medium Edge processing for critical control loops.

trending_up Impact Trajectory

Audited value realization curve

Integration of >100 distinct OT protocols Verified Outcome
Primary KPIReduction in data integration effort by ~40%
Audit CycleReal-time latency for Digital Twin synchronization

policy Compliance & Gov

  • Standards: IEC 62443 (Industrial Security)
  • 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 global technology and manufacturing conglomerate without exposing sensitive IP or identities.

Private
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1. Raw Evidence

Audit ID: #PRIV-902
Evidence: Direct SQL Logs
Public
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2. Verified Asset

Outcome: Verified
Ref ID: #COI-902

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