Automotive & Mobility

Process flow and quality consistency,
controlled with data

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Challenges on
automotive sites

Recurring problems across press, body, paint and assembly.

One process shakes the whole line

Press, body, paint and assembly are coupled end to end, so a single piece of equipment going wrong escalates into a full line stoppage.

High power and fine control at once

High-power equipment runs on a line that also needs fine control, so tuning one side makes the other unstable.

Equipment, energy and output stay apart

Electrification and tighter quality standards demand all three together, but the data sits in separate systems.

How the problems are solved

What Refinery actually does
on an automotive site.

Vibration-based predictive maintenance for motors and rotating equipment

Problem
Rotating-equipment anomalies confirmed only after a stoppage
Approach
An AI agent reads anomalies in vibration and current trends to catch early signs, and proposes both the likely cause and the next action with the history behind it.
Outcome
Less equipment downtime and steadier production

Power usage patterns by line

Problem
Different power draw line to line, with no way to explain it
Approach
Lines, processes and assets are connected through an ontology, so each signal is given meaning — which asset it belongs to and what it measures — and power use can be compared on equal terms.
Outcome
Lower energy cost and inefficient processes identified

Demand-based compressed air control

Problem
Air compressors running regardless of actual demand
Approach
Power draw and operating patterns are read so a VSD matches supply to demand, with inspection cycles and fault diagnosis managed alongside.
Outcome
Minimal energy waste and better operating efficiency

Energy intensity tied to output

Problem
No structure for seeing efficiency against production
Approach
Production records and energy use are linked to derive energy intensity by line and vehicle model automatically.
Outcome
Efficiency made visible against output, cost structure improved

Ambient conditions and quality impact

Problem
Causes of quality issues recorded in separate systems and hard to retrace
Approach
Temperature, humidity, equipment state and quality results are joined on one timeline to trace the cause.
Outcome
Less quality variance and better process conditions

How it fits together

How field data gains meaning and turns into a decision.

Site
  • Presses
  • paint
  • assembly equipment
  • motors
  • vibration sensors
Connect
  • SCADA
  • PLC
  • MES
  • Modbus TCP⁠/⁠IP
  • RS-485
  • OPC UA
Refinery
  • Ontology
  • AI agent
  • rules and automation
Use
  • Line dashboard
  • predictive maintenance alerts
  • quality traceability

Where MES or PLC already exists, a layer sits on top of it and integrates bidirectionally rather than replacing it. Where none exists, collection is built from the ground up.

Systems we connect to

The systems and protocols commonly used on automotive sites.

SCADAPLCMESERPModbus TCP⁠/⁠IPRS-485OPC UALTE

Systems not listed here can still be connected over standard protocols and APIs. Get in touch and we will walk through it.

What you gain

Benefits across operations, engineering and management.

Less equipment downtime

Anomalies are caught early in rotating-equipment vibration, keeping production steady.

Lower energy cost

Power patterns are compared line by line to identify inefficient processes.

Better cost structure

Efficiency against output is put into numbers.

Less quality variance

Ambient conditions and quality results are joined to tune process settings.

The Refinery team will work with you to find
the answer that fits your automotive operation.

Request a demo