Digital industrial operation connected to data
Data, Systems and AI

Data, Systems and AI that turns industrial data into action on the shop floor.

We connect machines, systems, data and AI to the operation’s management routine, so OEE, quality, maintenance and planning stop being mere indicators and start guiding daily decisions.

The thesis

Data, Systems and AI is not about digitizing the factory.

It is about creating a decision routine where reliable data becomes action on the shop floor. The difference is not collecting more data, it is building a reliable chain between operational signal, decision and execution.

The operational chain

From machine to result

Each step only creates value when it connects to the next, from the signal captured at the equipment to the gain measured on the shop floor.

01

Machines

signals captured at the source

02

Data

a reliable base, without manual rework

03

Systems

ERP, MES, sensors and operations integrated

04

Analytics / AI

models applied to losses, anomalies and real forecasts

05

Management routine

owner, cadence, priority and action

06

Result

gain measured on the shop floor

Real-time OEE on the shop floor
OEE

Real-time OEE to act on losses, not just measure them.

OEE combines availability, performance and quality. Magellan structures automatic capture, loss analysis and the management routine so the indicator becomes action while there is still time to change the outcome.

  • Availability
  • Performance
  • Quality
  • Losses
  • Root causes
  • Daily management
Integrated data and systems before AI
Data & AI

Integrated data before AI.

AI only scales when machines, systems and routines share a reliable base. We integrate operational data, existing systems and analytical models to support real decisions.

  • ERP
  • MES
  • Machines
  • Cloud
  • Dashboards
  • Analytical models
  • Data governance
Predictive maintenance and quality control
Prediction

Prediction connected to execution.

Alerts, anomalies and predictive models only create value when they enter the operation’s prioritization. We connect maintenance, quality and leadership to turn signal into action.

  • Predictive maintenance
  • Quality control
  • Operational alerts
  • Anomalies
  • Action prioritization
  • Downtime reduction
Operational architecture

What we activate so technology becomes routine

Capturing data is just the beginning. Value appears when operational signals flow through a clear architecture: integration, analysis, decision and execution on the shop floor.

01

Capture

Reliable collection at the source: machines, sensors, digital records and operational events.

02

Integrate

Connection between the shop floor, ERP, MES, legacy systems, BI and databases.

03

Analyze

Analytics and AI applied to losses, anomalies, quality, maintenance, planning and forecasts.

04

Act

Management routine with owners, cadence, priorities, alerts and monitored execution.

Magellan connects technology, process and management so data does not stay isolated in dashboards.

Operational architecture of Data, Systems and AI connecting machines, data, AI and management
Where value appears

When data enters the routine, the gain appears on the shop floor.

Gains do not come from the dashboard itself. They appear when operational signals enter the decision routine and change execution.

Lever
Operational signal
Enabled decision
Expected gain
PerformancePace, bottlenecks and OEE
Pace losses, micro-stops, bottlenecks and OEE variations.
Prioritize constraints, act on root causes and adjust production cadence.
OEE improvement, higher throughput and greater predictability.
ReliabilityAssets and downtime
Recurring failures, alarms, MTTR, MTBF and anomalous asset behavior.
Anticipate interventions, prioritize maintenance and reduce unplanned downtime.
Less downtime, more predictable maintenance and higher availability.
QualityDeviations and variability
Parameter deviations, scrap, rework, complaints and process variation.
Correct the process before the loss becomes permanent.
Fewer quality losses, greater stability and repeatability.
PlanningCapacity and priorities
Demand, capacity, constraints, delays, inventory and plan adherence.
Adjust plan, sequencing and priorities based on reliable data.
Faster decisions, less improvisation and a better service level. See M-APS
Proof in real operations

Signals that became measured gains

In selected projects, digital initiatives connected to the operational routine supported gains in performance, quality, maintenance and decision-making.

+33%
OEE at a global industrial engineering group
-53%
MTTR with digitalized maintenance
-77%
urgent requests via commercial–operations interfaces
+39%
quality on a coated-fabric line

These results appear when data, systems and management routine stop operating separately.

View Data & AI cases

Results from selected projects; they vary depending on context, data maturity, systems integration and scope.

Want to know where Data, Systems and AI can capture value in your operation?

Start with a clear read of the maturity of your data, systems and management routine, before investing in more technology.

Talk to us about Data, Systems and AIStart the Data, Systems & AI maturity assessment
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