← Products
01Overview

DutchBoy PLANT · Refining & Gas Plants

Before it stops — ahead of the trip. See degradation and its cause first

DutchBoy PLANT reads thousands of tags stored in your DCS and historian against normal baselines for each operating mode. It finds where degradation begins and which tags are driving it before limits are reached, and draws on past maintenance and action records to suggest a response. Your existing control and information systems stay as they are.

Applicable Processes

Oil & gasPetrochemicalsfine chemicalsSteel (ironmakingsteelmakingrolling)Water treatmentpurificationWastewaterWater infrastructure

Data Analyzed

W

Wave

DCS/SCADA continuous tags

T

Table

Lab results · maintenance history

P

Pulse

Batch process recipes

02Challenges on the Floor

What existing systems tell you — what happened. What's still up to people — why, and what's next.

Challenge 1

Degradation is slow; alarms wait for the limit

Fouling, wear and catalyst decline develop over weeks, but alarms sound only when a limit is reached.

Challenge 2

Too many alarms

False alarms flood in whenever the operating mode changes, making real signals hard to pick out.

Challenge 3

Plenty of data, little analysis

Tags pile up in the historian, but people still decide which ones to look at first.

Challenge 4

Maintenance know-how lives with people

The same trips and failures recur, while past fixes stay buried in the records.

03What Gets Analyzed, What Comes Out

The data you already have, read as one — anomalies, root causes and actions, delivered.

Input · existing systems and data

WDCS · PLC · SCADA tags
WProcess historian
TLab (LIMS) results
TMaintenance (CMMS) history · trip records
Vibration monitoring · APC · MES results

DUTCHBOY ANALYSIS

1

Collect & clean

Align scattered data on one timeline

2

Detect anomalies

Score deviations from the normal baseline

3

Find root causes

Where, what and why it differed

4

Connect to action

Next steps backed by past cases and evidence

Sensor, waveform, measurement and image data are all converted to time-series and analyzed by one engine — no need to build a new model for each data type.

Output

  • Anomaly scores against normal baselines for each operating mode
  • Degradation trends and warnings before limits are reached
  • Likely causal tags and how the issue propagates through the process
  • Comparison across parallel equipment and trains
  • Past trip and maintenance cases and the actions taken
  • Shift handover and equipment health reports
04How This Differs From Existing Systems

Your existing systems, unchanged — just the 'why' and 'what next' added on top.

DCS alarms

Limitation

Fixed limits, false alarms when operating modes change, late warning of slow degradation

What DutchBoy Adds

Anomaly scores against mode-specific baselines and trends before limits are reached

Process historian

Limitation

Stores data and shows trends, but people choose which tags to view

What DutchBoy Adds

Shows 'where it started' with a ranking of contributing tags and the process flow

Vibration monitoring

Limitation

Sees only the vibration of a single rotating machine

What DutchBoy Adds

Separates causes by looking at vibration together with flow, temperature and pressure

CMMS · EAM

Limitation

Maintenance records pile up as text and are hard to reuse

What DutchBoy Adds

Searches past cases and actions by symptom pattern, and verifies a return to normal after maintenance

LIMS

Limitation

Lab results arrive late and are viewed apart from operating conditions

What DutchBoy Adds

Aligns lab results with operating tags in time and analyzes them together

05Application Scenarios

One approach, different problems — solved in every process.

Refining · chemicals

Heat exchanger and compressor degradation

  1. 1Anomaly score starts rising
  2. 2Compare parallel equipment · contributing tags
  3. 3Past maintenance cases and timing
  4. 4Confirm a return to normal after the fix
Steel

Rolling and casting equipment anomalies

  1. 1Abnormal motor, roll or hydraulic signals
  2. 2Link quality defects on one timeline
  3. 3Past replacements and actions
  4. 4Confirm a return to normal after the fix
Water

Efficiency loss at pumping stations and treatment plants

  1. 1Detect rising power draw relative to flow
  2. 2Compare equipment of the same type
  3. 3Past wear and clogging cases
  4. 4Weekly report · maintenance plan
06How the 6 Modules Work Together

Only the modules you need, added on top of what you have — Core to start, automated reporting and conversational AI as Add-ons. Every module running on the plant data Weave designs.

Agent · Query & reasoning
Visualize · Evidence & reporting
Sense
Recall
Watch
Weave · Factory data design

Your existing systems — unchanged

DCSPLC/SCADAHistorianLIMSCMMSVibration monitoringMES/ERP

Weave

Data design

Collects and cleans tags, defines unit-equipment-tag relationships, and time-aligns lab results

Core

Sense

Detection & RCA

Mode-specific anomaly detection, degradation trends, contributing tags, parallel equipment comparison

Core

Recall

Recall & response

Past trip and maintenance cases and recommended actions, post-maintenance verification

Core

Watch

Integration & alarms

Brings DCS alarms, LIMS, CMMS and vibration monitoring results together, with rule-based alarms

Core

Visualize

Evidence & reporting

Shift handover and weekly equipment health reports

Add-on

Agent

Query & reasoning

'Why did compressor 2 vibration go up?' → answers with evidence

Add-on

Why an LLM alone isn't enough — Time series from just 150 sensors add up to millions of numbers (about 5.4 million in our technology video example), far more than an LLM can read directly. DutchBoy's manufacturing-specific tools condense them into a few lines of key evidence — severity, pattern, scope of impact and past cases — and hand them to the Agent.

Could this fit your process?

From feasibility to expected impact, the AIBIZ team will walk you through it directly.

Book a Consultation