Capillar IT member of ALICE
06/03/2024
After the Collaborative Innovation Day in Rome in 2018, it was a pleasure to join the @ALICE ecosystem in Brussels for a new edition of
Digital twins in logistics
Data-enriched decision-making, including: descriptive analysis, predictive modeling, result validation.
Why apply simulation with digital twins in logistics?
Digital twins in logistics are information system that simulates the real system to test, modify, and optimize operations in a virtual environment before implementing changes in the real world, including the development of algorithms and functionalities.
It is based on a proprietary optimization engine that integrates the capillar IT logistic design methodology to combine sustainability, decarbonization, and business efficiency.
It allows simulating logistic scenarios to find the optimal solution for each situation. Exploring and comparing different scenarios, such as demand spikes, supply chain disruptions, or regulatory changes, and considering uncertainties associated with simulations based on:
1. The reliability of logistic environment characterization.
2. The reliability of vehicle and equipment operational characterization.
3. The robustness of optimization algorithms.
These highly reliable simulations allow evaluating the resources needed for the transition to the optimal scenario and preparing for it adequately.
More information about digital twins in logistics: Optimización de procesos logísticos
How does our digital twin in logistics work?
Digital twins in logistics like the one we have at Capillar IT allow, in particular::
1
Optimize routes:Simulate different routes and scenarios to find the most efficient option in terms of time, cost, emissions, and overall sustainability.
2
Design the optimal logistic system, including the placement of spatial infrastructure such as hubs of different capacities, and charging points with or without autonomous energy generation.
3
Analyze current capabilities:Evaluate and optimize the capacities of current storage, transportation, and distribution resources, to formulate cost-reduction strategies by identifying inefficiencies and areas of improvement, as well as market development opportunities with the subsequent investment.
4
Continuous improvement:As more data is gathered, the digital twin "learns" and provides increasingly accurate recommendations.
5
Integration with other technologies:Digital twins can be integrated with Internet of Things (IoT) systems, Artificial Intelligence (AI), and other emerging technologies to enhance accuracy and real-time decision-making.
6
Training and education:New employees or those changing roles can use the digital twin to become familiar with the system without disrupting ongoing operations.
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Digital twin simulations
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