News
18.06.26
Simulation in industry: efficiency right from the start
Executive Summary: Those who use simulation in industry early on in the development process shift the focus from ‘finding faults’ to ‘preventing faults’. Digital models make assumptions measurable, speed up decision-making and ensure innovation and efficiency right from the start.
Within the Siemens ecosystem, it is ensured that design, simulation and product life management data are seamlessly integrated – without any loss of data at the interfaces.
Why simulation is indispensable in industry today
Pressure to bring products to market quickly, increasing complexity (software, electronics, new materials) and a shortage of skilled workers all call for robust, rapid decision-making. Simulations provide precisely this foundation: they make volatile variables transparent, test alternatives digitally and reduce costly iterations in the physical world.
Industrial companies use simulation solutions from Siemens, including high-end solutions such as Simcenter STAR-CCM+ or Simcenter 3D, CAD-integrated solutions such as Simcenter FLOEFD and the NX Performance Predictor, and Simcenter X as a cloud-enabled simulation platform.
From components to factories: where simulation makes a difference
1
Component and system levels
Multiphysics models (structure, thermal, fluid flow, EM) help to optimise designs, verify tolerances and mitigate risks at an early stage.
Simcenter AMESIM boosts the productivity of system simulation and is one of the leading integrated, scalable mechatronic system simulation platforms. It enables designers to virtually evaluate and optimise system performance.
The result: fewer prototypes, more reliable products and shorter development cycles.
2
Mechanical and Plant Engineering
Manufacturers are speeding up design and production processes by using simulation as a standard tool for analysis, validation and optimisation. This has a positive impact on quality, costs and the pace of innovation – and enables ‘digital continuity’ between CAD, simulation and manufacturing.
Efficiency right from the start: The business lever in four phases
1
Concept & Design
Early-stage simulation assesses load-bearing capacity, dimensioning and material selection. Different variants can be compared digitally at low cost, rather than having to carry out costly modifications later on. SIEMENS SIMULATION addresses aspects such as structural strength and fatigue, amongst others.
2
Detailing & Verification
Multiphysics couplings (e.g. thermal ↔ mechanical) reveal boundary cases. SIEMENS SIMULATION provides modules and workflows for this purpose, enabling the robust design of process and product parameters.
3
Start-up & Operation
Digital twins ensure that changes are implemented reliably and capacities are fine-tuned. Empirical knowledge is fed back into the model – the next iteration starts at a higher level. (Consistent continuation of the approaches presented by the providers.)
Practical benefits – concrete and measurable
Fewer prototypes, faster approvals: Digital verification reduces the number of iterations in the test laboratory and on the shop floor. SIMCENTER technologies bring FEA and durability expertise into the process chain.
- Multiphysics instead of silos: Combined analyses (thermal, fluid, EM, structural) prevent conflicting objectives late in the project. SIEMENS provides building blocks and example models for this purpose.
- Digital continuity: from CAD to simulation to manufacturing – fewer data disconnects, greater traceability. SIEMENS Software addresses this workflow with an industry-specific focus.
Technology Landscape: An Overview of Tools and Ecosystems
Siemens NX + Simcenter 3D: Creation and preparation of CAD-associated simulation models within a single environment. CAE engineers can carry out and evaluate a wide variety of analyses.
NX-CAD integrated simulation solutions: Whether it’s Performance Predictor, Topology Optimizer or CFD Designer – these tools enable designers to carry out simple simulations simultaneously with the actual component development within a single environment, and to make well-informed design decisions at the earliest possible stage. Simcenter STAR-CCM+: A high-end multiphysics solution with a bidirectional interface to common CAD systems.
Process model: How to roll out industrial simulation across the board
1
Refining use cases
Which KPIs are decisive (e.g. mass, stiffness, heat build-up, OEE, throughput)? What constraints apply? Clear objectives guide the search space and the efficiency of the analyses. (Derived from supplier guidelines and practical examples.)
2
Curating data and models
Quality trumps quantity: reliable material data, well-defined boundary conditions, standardised models and geometries. Comparing these with experimental data helps to continuously improve the simulation models and better assess the accuracy of the predictions.
3
Automate workflows
From parameterisation to reporting – automating recurring tasks, versioning results, defining review gates. SIEMENS addresses digital continuity in manufacturing here.
4
Running and validating scenarios
Systematically run through ‘what-if’ scenarios, test results against measured values, and document assumptions. Siemens simulation tools describe how they support projects throughout all project phases.
5
Standards & Templates
Transferring successful setups to libraries – for reuse and faster onboarding. Sample models and templates are available to serve as a starting point.
Governance & Risk: How to keep ESO under control
- Traceability: Requirements ↔ Models ↔ Results must be linked and versioned – the basis for audits and series approvals. SIEMENS emphasises the role of integrated toolchains for documentable approvals.
- Validation: Every model requires reference cases and acceptance criteria. SIMCENTER resources demonstrate how physical couplings are correctly parameterised.
- Transition to operation: Simulation findings must be incorporated into the layout, work plans and operating parameters – SIEMENS highlights the need for support ‘before, during and after’ the simulation.
KPIs for efficiency right from the start
-
First-pass yield (proportion of designs/processes approved on the first attempt)
-
Iterations until approval (digital/physical)
-
Prototype reduction (units & costs)
-
Throughput / OEE (in manufacturing simulation)
-
Ramp-up curve (time to rated output)
These key performance indicators directly link industrial simulation to business objectives: quality, speed and cost. (Derived from best-practice models of the aforementioned vendor ecosystems.)
Common pitfalls – and how to avoid them
-
Silo models: Modelling disciplines in isolation leads to conflicting objectives. Multiphysics forces a holistic view.
-
Late integration: Simulation after the CAD freeze costs time and money – ideally, it should start right from the beginning.
-
Unclear data basis: Missing material or process data invalidates results – maintain and version control data centrally.
-
Lack of implementation: Simulation without shop floor follow-up comes to nothing. Consultancy and implementation must be closely integrated.
Outlook: Industrial simulation as a driver of innovation
The combination of Siemens NX and Simcenter (design, FEA, durability), as well as CAD-integrated solutions that are easily accessible to designers, provide the building blocks for digitally planning and robustly scaling value chains – from the initial idea through to series production. Those who view simulation in industry as a continuous improvement process build a sustainable competitive edge: faster decisions, more resilient processes, better products. That is efficiency right from the start.
Topics
Multiphysics process simulation
Risks & Model Validation
Simulation in Industry: Benefits
Mehr entdecken