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Solution · Decision platform

Digital Twin Solutions

Represent complex business processes and physical systems digitally to understand behaviour, constraints and alternatives before an investment or operational change.

Documented capability

An application portfolio, interactive process simulation and physical Solar Tracker twin are documented.

Discuss a digital-twin questionSee Dynamic Modeling in practice
From business question to tested decision
  1. 1

    Frame the decision

    Set objectives, criteria and boundaries

  2. 2

    Understand the system

    Capture flow, resources and dependencies

  3. 3

    Model the baseline

    Represent the starting state and assumptions

  4. 4

    Simulate scenarios

    Test alternatives under shared conditions

  5. 5

    Select the option

    Evaluate impact and trade-offs

Five steps: frame the decision, define the system, model the baseline, simulate scenarios and select an alternative.

Business question

Which option works across the connected system — not only in an isolated activity?

A digital twin makes assumptions, dependencies, queues, resources and trade-offs visible. Alternative decisions are compared under shared conditions before time and capital are committed.

Typical decision areas

  1. 01Compare capacity, investment and inventory alternatives
  2. 02Understand bottlenecks and how they move across the system
  3. 03Test service, workforce and logistics processes under variable demand

Application areas

One modeling approach for different system types.

The process model, simulation, visualization and KPI dashboard remain separate layers. That makes the solution transferable to new processes and future data sources.

  • 01

    Manufacturing digital twins

    Examine production flow, capacity, availability, setup, WIP and bottlenecks together.

    Typical applications

    • Production
    • Assembly
    • Capacity planning
    • Bottleneck analysis

  • 02

    Supply chain & logistics models

    Model inventory, replenishment rules, warehousing, transport and delivery performance as one connected system.

    Typical applications

    • Supply chain
    • Logistics
    • Inventory
    • Network decisions

  • 03

    Workforce & service simulation

    Compare demand, skills, handoffs, staffing and service targets in operational service processes.

    Typical applications

    • Workforce planning
    • Service processes
    • SLA impact
    • Waiting time

  • 04

    Physical asset twins

    Keep simulation, control logic and telemetry from physical systems separate and analyse them together.

    Typical applications

    • IoT
    • Telemetry
    • Simulation
    • Model calibration

  • 05

    Scenario & KPI interfaces

    Bring parameters, scenarios and management KPIs into an understandable decision interface.

    Typical applications

    • Scenario comparison
    • KPI dashboard
    • Data adapters
    • Visualization

Decision path

Understand, model, simulate, decide.

The twin is not an end in itself. It answers a concrete management question and keeps objectives, assumptions and alternatives traceable.

From business question to tested decision

  1. 01

    Frame the decision

    Set objectives, criteria and boundaries

  2. 02

    Understand the system

    Capture flow, resources and dependencies

  3. 03

    Model the baseline

    Represent the starting state and assumptions

  4. 04

    Simulate scenarios

    Test alternatives under shared conditions

  5. 05

    Select the option

    Evaluate impact and trade-offs

Five steps: frame the decision, define the system, model the baseline, simulate scenarios and select an alternative.

Documented practice

Two forms of digital twin — kept clearly separate.

The portfolio documents business-process models; Solar Tracker documents a physical twin with telemetry. The browser-based process simulation is labelled illustrative.

Documented evidence

  • Sixteen anonymized Dynamic Modeling applications across manufacturing, supply chain, logistics, energy, telecommunications and service operations.
  • An interactive, explicitly illustrative process simulation demonstrates scenarios, KPI impact and moving bottlenecks.
  • The Solar Tracker twin keeps simulation and real measurements separate.
  • The technical architecture has a defined adapter boundary for a future external simulation engine.

Claim boundaries

A model is a decision base, not a guarantee.

Its usefulness follows from the data, assumptions, model boundary and validation. Those conditions are made visible in each project.

  • The public process simulation is educational and illustrative, not mathematically exact and not a customer model.
  • Model results are not a guarantee of future operational or financial outcomes.
  • Data integration, calibration and engine connectivity are defined per project.
  • Dynamic Modeling is not positioned as a software brand or licence product.

Digital Twin Solution

Which decision should your digital twin make more reliable?

Describe the process, alternatives, data position and affected KPIs. Together, we clarify what the model genuinely needs.

Discuss a digital-twin questionvencel.somos@somos-co.com