Everything at a glance: The digital twin in intralogistics

Updated on 19. May 2026

Digital twins have established themselves as a forward-looking tool in intralogistics, production and engineering. They promise numerous advantages and raise optimization potential in order processing. But what is behind the term, where are digital twins used and what are the benefits of real-time localization in warehouse operations?

Major changes in the market are affecting manufacturing companies and the logistics sector: customers expect ever faster delivery on a small ecological footprint in increasingly complex global supply chains. Solutions are revealed in technological progress: IoT, AI and autonomous forklift trucks promise optimized workflows in the global marketplace. Their integration in the warehouse is accompanied by numerous challenges, from reliable operation and data security to the question of return on investment (ROI). Digital twins are on everyone’s mind in this context and serve as a platform for integrating process-optimizing technologies. They enable the simulation and optimization of virtual processes before they are implemented in the warehouse. But what exactly is behind these digital twins?

Summary:

The term “digital twin” is on everyone’s lips – but what it actually means and what it concretely delivers in warehouse operations often remains unclear.
A digital twin is the virtual real-time representation of a physical object, system or process – fed by sensor data and linked to all available order information.
There are four types: product, process, asset, and system twins – differing in complexity and level of detail depending on the application.
The foundation of any meaningful digital twin is real-time data. The more current and complete the data, the more precise the predictions and control options.
identpro generates the warehouse digital twin automatically via LiDAR sensors on existing forklifts – accurate to the centimeter and second, without labels or floor markings.
Best practice: ELA Container reduced loading time from 2 hours to 10 minutes using identpro’s Warehouse Execution System (WES) – with an ROI of under 15 months.
The digital twin optimizes transport routes, reduces empty runs, supports preventive maintenance, and creates transparency across the entire supply chain.
It is the technical foundation for deploying autonomous guided vehicles and AI-driven decision-making in the warehouse.
The path there follows clear steps: from needs analysis through pilot project and technology selection to full scaling.
The result: a fully transparent, search-free, and future-proof warehouse – with measurable impact on cost, quality, and sustainability.

Definition: What is a „digital twin“?

The digital twin is the virtual replication of a physical object, system or process. This digital representation makes it possible to collect, analyze and simulate data in order to better understand, optimize and predict the real world counterpart. The digital twin is provided with data by sensors (such as position and distance sensors, temperature sensors, optical sensors, gas and chemical sensors or force and pressure sensors) and other data sources that reflect the state, working conditions or location of the physical object. This makes it a powerful method for virtually mapping physical worlds to gain profound insights, improve decision-making and optimize processes.

Examples: “digital twins” in production, engineering and logistics

Digital twins are made up of a physical object that is depicted in the virtual model. It simulates the physical object and replicates it. The prerequisite for this is data (big data). The more data and the more up-to-date it is, the more meaningful the predictions of the digital twin are. Real-time data is essential in the automated factory, for example in the warehouse when using autonomous forklift trucks or robots. Networks and communication protocols that enable data exchange between the physical object and the virtual model are another key component. There are various types of digital twins that differ in terms of complexity, depth of detail, data sources and interaction options depending on the specific requirements in the area of application:

Product twins are virtual images of individual products. They simulate the entire life cycle of a product and provide insights into quality, behavior and condition in the respective phase. They are used in product development and are used for virtual tests, simulations, error analyses and optimizations.
Process twins depict processes such as order picking, packaging or internal transportation in the production warehouse and model the process flow and the interaction of different components. They enable the analysis and optimization of processes, the identification of bottlenecks and the prediction of results. In this way, they form the basis for optimized turnaround times.
Plant twins are virtual images of machines and devices in the warehouse. They can be used to monitor the status and performance of systems, schedule preventive maintenance and thus extend the service life of equipment.
System twins describe the comprehensive representation of the entire warehouse or production system. They take into account the interaction between the components of the system as well as external conditions. They therefore offer real-time insights, support decision-making and enable optimized control.

Best Practice: ELA Container introduces digital twin for transparent warehouse processes

ELA Container is a globally active company for mobile space and building solutions made from containers. The time-consuming manual warehouse management in the 50,000 container rental park was to be replaced by a solution that offers complete transparency of the warehouse stock with automated bookings using real-time localization (3D position data). A completely search-free warehouse was chosen with the Warehouse Execution System from identpro. It switched from WLAN to LTE for future-proof signal transmission. The forklift trucks were equipped with LiDAR sensors to record the surroundings and all movements to the nearest centimeter and second. Software modules for creating the digital twin in real time, visualization and a 3D forklift guidance system were set up. As a result, the loading time was reduced from 2 hours to 10 minutes and an ROI of less than 15 months was achieved. Evaluations of the real-time warehouse data successively lead to further warehouse and route optimizations.

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Benefits: Transparency, optimized processes, informed decision-making

Digital twins enable real-time monitoring of all movements in the warehouse. The virtual simulation of the warehouse allows companies to determine optimal routes for the placement of goods, picking and packing processes and the use of automation technologies. The analysis of the material flow within the warehouse or between different locations enables the identification of optimal transport routes, the coordination of industrial trucks for maximum capacity utilization or more efficient picking and sorting processes.

Digital twins also do their service in maintenance and system management: real-time data monitoring allows the status of warehouse automation systems to be predicted and maintenance requirements to be identified at an early stage. This significantly reduces unplanned downtime. Safety and quality management scenarios can be simulated, as can the optimal use of resources to achieve ecological sustainability goals.

Digital twins create visibility across the entire supply chain and therefore also beyond the warehouse: delays can be identified at an early stage and counteracted. Digital twins also support collaboration with suppliers and logistics service providers. Simulations also help to make informed decisions before investments are made in expanding warehouse capacities or introducing new technologies.

This is what identpro’s real-time digital twin brings to your warehouse:

Real-time localization (RTLS) for optimal warehouse utilization
Live mapping accurate to +-10cm
Consideration of dynamic warehouse changes
Scan-free warehouse processes
Paperless management
Empty runs are significantly reduced
Warehousing with minimum stock levels
More flexibility in the event of market changes

Seamless connection to ERP or WMS
Optimal use of resources for sustainable warehouse management
Use of existing manned forklift trucks
Cost reduction through optimized processes, preventive maintenance, reduced downtime and lower operating expenses
Well-founded decision-making

Future prospects: Digital twins in a global networked world

Digital twins are the basis for fully interlinked and autonomous warehouses with extensive use of IoT and AI. They are already an essential part of modern manufacturing companies and intralogistics. Where large players already have a knowledge advantage over smaller market players with fewer resources, the actual optimization potential is far from exhausted. The industry is moving towards warehouse management that is controlled by networked digital twins and autonomous as well as manned forklift trucks. This is because both competitive pressure and rising customer expectations are increasing the need for optimized, transparent logistics processes. AI, machine learning and real-time data analysis are making digital twins increasingly efficient. Cross-linked and synchronized digital twins across company boundaries promise increasingly efficient supply chains. Falling implementation costs due to technological progress and targeted support programs will further accelerate the development of a standard and the increasing implementation of virtual twins in the coming years.

Next Step: Seven steps to a digital twin

analysis of requirements and target setting

proof of concept and pilot project

data infrastructure and integration

technology selection and partners

implementation and training

monitoring and optimization

scaling and further development

Wiki: Digital twin

Augmented Reality: A technology that embeds digital information in the real world. It can be used to display data and visualizations of the digital twin in the physical environment.

Big Data: The large amount of structured and unstructured data that is collected. Digital twins often require the processing and analysis of big data to enable precise models and predictions.

Cloud Computing: The provision of computing resources via the internet. Cloud services are often used to store and process data and to access digital twins.

Cyber-physical system (CPS): A combination of computerized elements and physical processes that are closely connected and influence each other. Digital twins are often part of CPS.

Digital Thread: A consistent digital representation of information over the entire life cycle of a product or system, which enables the connection between design, production, operation and maintenance.

Digital Twin: The virtual representation of a physical object, process or system that makes it possible to monitor, analyze and simulate its behavior and performance in real time.

Edge Computing: Processing data close to the source where it is generated (e.g. in a warehouse or factory) to reduce latency and improve real-time processing.

Internet of Things (IoT): A network of physical devices, vehicles, buildings and other objects equipped with sensors, software, electronics and connectivity to collect and exchange data.

Machine Learning and Artificial intelligence (AI): Technologies that enable the digital twin to learn from data, recognize patterns and make decisions to improve or automate processes.

Simulation and modeling: The process of creating models that replicate the behavior of a real object or system. These models are often used for predictions, analyses and tests.

Frequently Asked Questions (FAQ) on the Digital Twin in Intralogistics

A digital twin is the virtual real-time representation of a physical warehouse, vehicle, or process. It is continuously fed by sensor data – for example from LiDAR or IoT sensors – and maps all movements, stock levels, and states during live operations. In warehouse management, this enables seamless transparency: Where is each product located? Which transports are currently running? Where are bottlenecks forming?

WMS and ERP systems manage master data and orders – but they don’t know what’s actually happening in the warehouse right now. The digital twin fills exactly this gap: it delivers the real-time state of the warehouse and automatically passes this data to the connected systems. This means stock levels are no longer updated with a delay, but in the very moment a movement takes place.

Essentially any operation where goods are moved by industrial trucks – from production warehouses and logistics centers to open-air sites with large-volume goods. identpro has implemented the digital twin in industries including paper manufacturing, container rental, beverage logistics, and building materials distribution.

The investment depends on warehouse size and the number of vehicles. The ELA Container example shows that an ROI of under 15 months is realistic – through reduced search times, fewer empty runs, automated bookings, and lower staffing requirements. The key advantage: existing forklifts are retrofitted, with no new vehicles or complex infrastructure required.

Implementation follows a structured process in seven steps: from needs analysis and feasibility study through technology selection to scaling. A pilot project can typically be started without interrupting ongoing operations, as the sensor technology is retrofitted onto existing vehicles and no structural modifications are required.

Yes. Without complete, up-to-date warehouse data, neither AI can make meaningful control decisions, nor can automated guided vehicles (AGVs) navigate safely. The digital twin is therefore not just an optimization tool for today, but the technical basis for the gradual automation of the warehouse – from forklift navigation to the collaborative use of AMRs.