ServicesStage 03 · Model08 / 11

Simulation and Digital Twins

Evaluate changes before committing resources

Scenario simulation24 runs · throughput after line change
80100120140160month 035month 0 · median 100 · P10 100 · P90 100month 3 · median 102.9 · P10 99.2 · P90 108.9month 6 · median 105.3 · P10 100.8 · P90 113.2month 9 · median 110.0 · P10 102.5 · P90 114.7month 12 · median 113.7 · P10 103.8 · P90 119.0month 15 · median 115.6 · P10 107.9 · P90 125.3month 18 · median 119.3 · P10 108.2 · P90 130.1month 21 · median 120.3 · P10 109.2 · P90 136.9month 24 · median 122.8 · P10 108.9 · P90 139.3month 27 · median 128.4 · P10 105.3 · P90 142.6month 30 · median 132.9 · P10 107.2 · P90 145.1month 33 · median 136.0 · P10 108.0 · P90 148.9
units/h · indexmonth 35 · median 137.6 · P10–P90 111.9–151.3

Simulation and digital twins

MNC Analytics develops simulations and digital representations that help organisations investigate how assets and operations respond to different conditions. These tools support design evaluation, capacity planning, maintenance decisions and operational improvement.

We combine physical equations, operational logic and measured data according to the purpose of the model. Where ongoing connections to a physical asset or process are required, we design the data and update mechanisms needed to support a digital twin.

What we offer

7

  1. 01

    Physics-based, data-driven and hybrid models

  2. 02

    Discrete-event, agent-based and system dynamics simulation

  3. 03

    Model calibration and validation against independent observations

  4. 04

    Digital twin architecture and connections to operational data

  5. 05

    Scenario analysis, sensitivity studies and uncertainty assessment

  6. 06

    Comparison of equipment choices, operating policies and capacity changes

  7. 07

    Efficient models for repeated evaluation and interactive decision support

What this enables

A practical environment for testing assumptions and comparing options before changes are made to physical systems. Each model is delivered with a defined purpose, operating range and understanding of its limitations.

Related work

All work
01Agriculture, water and environmental systemsSaudi Arabia

Optimising pump scheduling across a water transmission network

A hydraulic model and a mixed-integer optimiser schedule pumps against tariff periods and reservoir constraints, cutting energy cost while keeping storage within agreed limits.

  • -16%pumping energy cost
  • -38%pump starts per day
  • 0reservoir limit breaches in 9 months
Read more
Monthly pumping energy cost, indexed to baselineBaselineOptimised
020406080100M1M2M3M4M5M6M1 Baseline: 100 indexM1 Optimised: 96 indexM2 Baseline: 100 indexM2 Optimised: 90 indexM3 Baseline: 100 indexM3 Optimised: 86 indexM4 Baseline: 100 indexM4 Optimised: 84 indexM5 Baseline: 100 indexM5 Optimised: 83 indexM6 Baseline: 100 indexM6 Optimised: 84 index
indexM6 · 84 index
02Buildings and infrastructureUnited Arab Emirates

Energy performance across a commercial building portfolio

Metering, building management and weather data were unified for 27 buildings, and calibrated building models now rank retrofit options by verified saving rather than by estimate.

  • 27buildings on one data foundation
  • 5 of 6retrofits within modelled saving range
  • -11%portfolio energy intensity, year one
Read more
Modelled versus measured saving, first retrofit roundModelledMeasured
05101520B1B2B3B4B5B6B1 Modelled: 14 %B1 Measured: 13 %B2 Modelled: 9 %B2 Measured: 10 %B3 Modelled: 18 %B3 Measured: 16 %B4 Modelled: 7 %B4 Measured: 8 %B5 Modelled: 12 %B5 Measured: 11 %B6 Modelled: 10 %B6 Measured: 6 %
%B6 · 6 %
Next service · 09Analytical Applications and Systems Integration

Contact

Tell us about the problem you need to solve

You may have a defined project, an underperforming process or a technical question that needs investigation. We can help assess the challenge, identify the information required and define an appropriate next step.

Discuss your projecthq@mncanalytics.com