Tracking and fleet management system

The combination of AI-based object identification and the W2MO optimization suite makes transports most efficient!

easy to use and powerful

AI-based tracking of transporters without complex navigation technology on-board

phenomenal google geographic data

Transporter navigation with route visualization using intelligent algorithms to select optimal paths considering the current workload

easy to use and powerful

3D cockpit and live view of current situation in the digital twin with permanent localization of transporters, people and further objects e.g. pallets, pick carts, etc.

easy to use and powerful

Determination of standard times based on MTM and comparison with actually required time to evaluate the efficiency and derive appropriate optimizations

easy to use and powerful

The digital twin includes an integrated simulation engine for planning scenarios to evaluate changes in workforce, shift times or transport resources

easy to use and powerful

Easy integration into the existing system environment with SAP and database connectors and possible combination with automated guided vehicles (AGVs)

AI-based tracking and navigation

  • Combination of computer vision and machine learning technology together with a 3D layout model in the digital twin enables precise tracking and navigation with accuracy better than 1 mm. The accuracy of the localization with the help of interpolation is better than 1 pixel of the camera resolution. With 4K resolution of the camera, the localization can be more precise than 1 mm on an area of 8㎡. Even with approximately 100㎡ you can still achieve accuracy better than 4 mm with a 4K camera.
  • Localization of all conveying means without complex navigation technology on the transporter
  • Real-time tracking and visualization in the 3D cockpit of the digital twin
  • Comprehensive analysis options and visualization of travel times, routes, capacity utilization, stop times and bottlenecks

By using permanently installed cameras with machine learning stick on board and localization in the W2MO digital twin, a great overview of all areas in the warehouse can be provided. Movements of AGVs, forklifts, pick carts and all other relevant objects can be identified by Logivations AI technology and the information about their exact locations can be transferred to W2MO in real time.

Logivations uses Machine Learning technologies and markers which are attached to the transporters for the identification. Therefore, no expensive and complex navigation technologies (e.g. lasers) are required anymore. As a result, additional transporters can be added very easily.

By using heatmaps, an overview of the driven speed, driving/idle times, stops and routes can be provided.

This transparency is a great base for further optimizations.

Forklift navigation

  • 3D visualization of the route from the start to the desired destination directly on the forklift
  • Calculation of the routes by using intelligent algorithms
  • Consideration of the current aisle load when calculating the fastest route
  • Assistance systems for early collision warning with other transporters and pedestrians as well as hints about different speed limits on certain routes or areas

The system contains a complete model of the existing warehouse structure including racks, bins and routes. Internal orders can be calculated automatically or can be imported from the warehouse management system. Integrated and adjustable optimization algorithms calculate the best possible route from the start to the destination for each transporter to use resources most efficiently. The system provides latest information about the workload in different areas at any time. Since the system knows the total number of all current and future transports, the current and expected traffic situation can be considered when calculating the fastest route to the destination. Due to permanent localization in real-time and the 3D layout in the digital twin, information about the expected traffic/speed limits at junctions can be provided in advance, also in difficult situations.

Transparency about the use of workers and resources

  • Comprehensive simulation model is an essential part of the digital twin
  • Standard times and comparison with actually required transport and working time
  • Consideration of multi-level transport chains
  • Load forecasting across all stages and time periods of transports

Picking and replenishment times are calculated in the W2MO model and used in the digital twin. The times are not calculated with average times but depending on the exact position of the bin within the rack which determines the expected workload for each pick. The expected time for a transporter can be determined due to its speed and the distance to be covered. Multi-level transport chains as e.g. putaway and retrieval from a narrow aisle warehouse using transfer points or storage on buffer areas at the inbound are taken into account. Thus, constantly expected and actually needed working hours can be compared. Therefore, an overview of the current efficiency can be provided at any time. Moreover, load forecasting can be used to react in time to possible bottlenecks that may occur across all transport stages (see also Workforce planning). Changes of a layout or processes, such as adjustments of the workforce or transport resources can be simulated in advance.

Integration into existing system environment

  • Add-on to existing warehouse management system
  • Cloud-based access for quick availability
  • Data exchange via database interface and web requests
  • Independent mobile devices (tablets) on the forklift
  • Possibility to be combined or extended by AGV

The W2MO transport control system is a comprehensive add-on to other IT systems due to its configurable algorithms, meaningful evaluations and various visualization options. The underlying modern web technologies enable an easy and quick access via the cloud or via installation in the company intranet. Data exchange with other IT-systems takes place via a database interface and web requests. As an SAP Application Development Partner, Logivations also has a standardized interface to SAP EWM. Tablets are used to display the relevant information for a forklift driver or a picker. This provides flexibility and vendor independence in hardware selection. The installed camera infrastructure can be easily extended to control the Logivations AGV.

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