How to use artificial intelligence as a catalyst without compromising the physical robustness of your digital twins.
Artificial intelligence is currently the hot topic in production and logistics. It is also raising high expectations in the field of simulation: Everything is set to become faster, more automated and ‘smarter’. But how much of this is already robust in the harsh reality of planning?
Our experience from current projects paints a nuanced picture: AI is no substitute for simulation, but it is arguably the most powerful accelerator we have seen in years.
Here are 7 practical insights on how to harness the synergy of both worlds:
1. The “data clean-up team”: The biggest lever at the start of a project
The bottleneck of every simulation project is the data set. In reality, ERP and MES data are often incomplete or inconsistent. This is where AI shines: it automatically checks and structures large volumes of data.
Your benefit: Manual effort is drastically reduced, and projects start weeks earlier than before.
2. Speed: Initial assessments in seconds
Planners often need immediate answers, yet complex models require computing time. AI can be trained to predict typical simulation results without physically calculating every scenario.
Practical benefit: You receive initial trends in seconds rather than hours, enabling you to separate the wheat from the chaff more quickly.
3. Intelligent variant search: Focus rather than volume
Instead of simulating thousands of scenarios ‘blindly’, AI filters out promising options. The simulation is then used only for the final, highly precise validation of the top variants.
4. Why “correlation” does not replace “causality”
A critical point: AI recognises patterns in historical data, but it does not understand the physics behind them. Simulation, on the other hand, models real mechanisms of action.
Important: Only the combination of both ensures that a solution found is not only statistically probable but also technically feasible.
5. Avoid the black box: decisions need to be traceable
In production, millions in investment depend on planning results. A simple “The AI calculated it this way” is not sufficient justification. Proposals must remain explainable to humans and verifiable by experts.
6. Think hybrid: the division of roles in the future
The greatest benefits arise from teamwork:
- AI handles data preparation, pattern recognition and pre-selection.
- Simulation delivers robust, physically sound results for final validation.
7. Implement pragmatically: Start small, expand strategically
No one needs to overhaul their entire planning landscape overnight. We recommend clearly defined pilot projects. This minimises risks and allows for the targeted development of internal expertise.
Summary
AI does not render simulation obsolete, but it makes it more accessible and faster. It is the answer to the increasing time pressure in modern logistics and production planning.
Are you planning the next step towards AI-supported simulation? Let’s work together to identify where the greatest potential lies within your processes.
