## 3 Results
### Digital Twin Design and Development  
Based on the activities conducted, the design of the DT can be funded. To support the data listed in the existing data inventory and the development of the DT, IoT systems will support the data generated to meet user requirements and related technical requirements for the following concerns:  
* Pallet for location in the warehouse: the IoT system aims at optimizing the warehouse, involving geolocating pallets stored in the outdoor warehouse and enhancing tracking capabilities.
* Forklift and bicycle transport routes: the IoT system aims at enabling real-time monitoring of transport routes, encompassing forklifts and bicycles, to ensure efficient and safe movement within the factory.
* Verification of the use of means of transport such as forklift and bicycles by authorized personnel: the IoT system ensures that only authorized personnel use specific means of transport, such as forklifts and bicycles, to enhance safety and control.  
The data collected in the DT will be used to support algorithm implementation for:  
* Warehouse task optimization: AI aims at using data to define the most productive scenarios and task assignments.
* Real-time collision risk alerts: AI aims at supporting on-board, real-time alarms on forklifts which will alert drivers to potential collision risks with bicycles in unauthorized areas, thus acting as a preventative measure against possible incidents.
* Asynchronous feedback for safety management: AI aims at communicating with safety operators in the factory, who will receive asynchronous feedback to identify areas with the highest levels of criticality, enabling them to take proactive measures to enhance safety.  
The BIM model provides a visual representation of the warehouse and geolocation, while the IoT sensors provide real-time data and GPS tracking on assets. The use of a cloud platform for data aggregation and analysis aligns with current trends in digital twin technology, ensuring scalability and accessibility.  
Based on the digital twin architecture in the literature and a previous project within the Focchi company [44], the architecture of the digital twin for the ETO company is designed in line with user requirements, technical requirements, the KPIs defined, and the existing data inventory (Figure 4). This design is based on the following:  
* Data source:
* ETO field systems include existing dynamic data sources used by the company to support engineer-to-order processes such as ERP and product scheduling. A BIM-based 3D model of the warehouse is used, providing a visual representation of the physical layout and enabling spatial analysis. The BIM includes a georeferencing of the facility as well as the definition of warehouse areas, locations, and pedestrian paths.
* IoT field systems are designed to collect real-time data on pallet locations and forklift and bicycle movements.
* Data interoperability:
* The communication layer moves from data sources to a Data Lake using on-site gateways or a connector with API or MVC solutions.
* The Data Lake has multiple Data Bases (DBs) related to data sources.
* The data integration layer connects data from DBs for dynamic data representation and data visualization and analytics tools, and to manage BIM in the DT.
* The business intelligence layer contains a dashboard for the business intelligence analysis of the Data Lake.
* ETO AI services, with their intelligent layer, are deployed in the DT algorithms to meet user requirements for warehouse optimization and safety.  
* The ETO digital twin includes the front end with the user interface and the visualization engine for desktop and mobile.