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SolutionsManufacturing Data & AI

Manufacturing / Manufacturing Data & AI

Connect the plant. Understand the next decision.

Bring operational signals, production context and enterprise data together to understand data readiness, asset health, quality and supply risk.

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A factory and operational signals
Industry contextA factory and operational signals

Decision pathway

From connected sources to a reviewed answer

01
Connected sources
OT historians & PLC / SCADAMES & SAP ERPQuality & LIMS
02
Shared meaningDefinitions + relationships + context
03
Evidence review
Source evidenceHuman reviewExplicit gaps
A business question this workflow can support“Which assets are driving OEE loss, and what maintenance evidence supports that conclusion?”

Workflow overview · not a customer outcome

The business challenge

Disconnected evidence.
Connected decisions.

Factory signals rarely arrive with the asset, shift, batch and material context needed to explain them. Separate views of maintenance, quality and suppliers leave teams solving the same data problem for each new use case.

What your team gains

  • 01A prioritized AI-readiness remediation plan
  • 02Maintenance and quality decisions with traceable drivers
  • 03Visibility across plant and supplier dependencies

Use cases

Built for the decisions
your team makes.

01

Plant-to-enterprise data readiness

Map source inventory and lineage, assess quality and contextualization, and prioritize gaps before deploying production AI.

02

Asset health & OEE

Connect telemetry to maintenance history and asset criticality. Decompose availability, performance and quality losses into evidence-backed maintenance priorities.

03

Quality & defect intelligence

Correlate inspection results with process parameters, material lots and shifts to investigate upstream drivers and detection blind spots.

04

Supply chain resilience

Traverse supplier tiers and part dependencies to reveal shared sub-suppliers, single-source exposure and demand-capacity mismatches.

How it works

A reviewable path.
Not just a result.

  1. 01

    Connect

    Inventory OT, production and enterprise sources and their lineage.

  2. 02

    Contextualize

    Map signals to shared assets, batches, shifts, parts and sites.

  3. 03

    Investigate

    Correlate patterns and traverse relationships with source evidence.

  4. 04

    Prioritize

    Review readiness gaps, risks and containment actions with the responsible team.

Control stays with your team.

Coverage gaps and example findings remain explicit. Maintenance, containment and supplier decisions stay with your operational teams.

Data your team brings

  • OT historians & PLC / SCADA
  • MES & SAP ERP
  • Quality & LIMS
  • CMMS maintenance logs
  • Supplier masters & BOM

Go deeper / Original solution brief

Manufacturing Data & AI

Connect plant data readiness, asset health and OEE, quality, and supply-chain resilience in one manufacturing workflow.

Brochure collection · 16 pages · PDF

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Frequently asked questions

Before you get started.

What data should we bring?

OT historians & PLC / SCADA, MES & SAP ERP, Quality & LIMS, CMMS maintenance logs, Supplier masters & BOM. We’ll discuss available fields, source coverage and access requirements with your team.

How are findings reviewed?

Coverage gaps and example findings remain explicit. Maintenance, containment and supplier decisions stay with your operational teams.

Does the brief show verified customer results?

These materials describe solution workflows. Any example datasets, findings or industry scenarios in the PDFs should not be interpreted as measured Datapane customer results.

Your next step

Start with your own
business context.

Discuss this workflow, the data it needs and the controls your team requires.

Talk to Our Team