Leveraging IoT retrofitted Lift Trucks for Seamless, Efficient, and Transparent Production Workflows
An article by IdentPro GmbH, Troisdorf
The digital twin offers real-time data that enables transparent planning processes in production-related warehouses. This allows for AI-powered decisions that optimize internal transport processes, resulting in synergy effects throughout the entire supply chain.
Data is the driving force of our future, playing a crucial role in enhancing efficiency across all areas, including production planning and warehouse logistics. As data becomes more complex, ensuring that raw materials reach processing points at the right time and in the necessary quantities is critical for smooth material flow. Between these steps, a range of activities occurs within production-related warehouses, from moving semi-finished products to the next phase of production or relocating them to other onsite storage areas. All these processes must operate within a tight economic framework.
Logistics innovation is becoming more essential, particularly in industrial production, where the growing shortage of skilled workers adds complexity to an already intricate system. Technological advancements provide access to increasingly large amounts of data, and the goal is to continuously make the best decisions to optimize production planning. When human capacity to manage warehouse processes reaches its limits, AI steps in to transform intralogistics.
Harnessing Synergies Across the Supply Chain
Real-Time Data for Enhanced Decision-Making
The digital twin captures and tracks every product movement within the premises, combining this information with order details,
GEO positions, and data from systems like ERP or WMS to create an integrated data packet. This data, available instantly, helps companies make well-informed, AI-supported decisions that enhance production and transport efficiency.
AI at the Forefront of Decision-Making
With larger data volumes comes greater decision-making potential. While human processing capabilities and traditional spreadsheets have their limits, AI can analyze vast amounts of information and calculate optimal processes in a fraction of the time. The AI-based system processes data from LiDAR and IoT sensors to provide real-time GEO data, creating a digital twin that mirrors warehouse activities and drives smarter internal transport optimization.
Unlocking the Potential of IdentPro’s Warehouse Execution System:
- Real-time localization of assets
- Highly accurate live mapping
- Ability to adapt to dynamic storage conditions
- Scan-free, paperless warehouse operations
- Reduction in unnecessary internal transports
- Efficient inventory management with minimal stock
- Zero tolerance for errors, eliminating costly supply chain disruptions
Reducing Errors and Increasing Efficiency
In the fast-paced world of industrial production, even minor errors can have significant repercussions throughout the supply chain, leading to delays and financial losses. However, with AI-driven automation, error rates can be dramatically reduced, offering substantial cost savings.
Where forklift operators previously had to step down from vehicles to record data manually, the new system automatically captures and corrects any errors in real time. This instant feedback helps ensure that every movement within the warehouse is tracked with precision.
Achieving Full Transparency with Real-Time Data
The digital twin serves as a virtual representation of the physical warehouse, providing up-to-the-minute insights into inventory levels, conditions, and ongoing activities. This transparency enables companies to streamline processes, reduce costs, and lower their carbon footprint, all while improving inventory management, space utilization, and minimizing human errors. Paper-based processes and hand scanners become obsolete, while automated training for drivers and driverless transport systems address workforce shortages.
The Future of AI-Driven Production Planning
The future of intralogistics lies in networked, AI-powered planning systems. In an ideal world, raw materials management is perfectly synchronized, but supply chain disruptions inevitably occur. These lead to delivery delays, excess inventory, and increased costs. Effective supply chain management demands complete transparency, made possible
through the integration of interoperable systems.
Looking ahead, AI will be indispensable for handling the increasing data complexity. Additionally, the shift towards driverless transportation will address the growing shortage of skilled labor. As AI-based decision-making technology is already in place, the future of production planning has, in many ways, already begun.
Dr. Martin Welp
CEO
IdentPro GmbH
