Mobile Logistics Robots for Shop Floor Data Fusion Updates
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Solution Overview
Problem
Existing systems for tracking and maintaining up-to-date information about production planning and shop floor logistics in low-volume high-mix environments are inefficient, often requiring significant infrastructure or manual updates, and lack accurate data management.
Innovation Solution
Equipping mobile logistics robots with sensors and processing units to capture and control shop floor data, using a fleet management system to distribute tasks, and a data fusion facility to merge and update master data with sensor-derived information, enabling continuous and automated data updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Real-Time-Locating-Systems with beacons and receivers are installed to automatically track locations of assets, then up-to-date shop floor information is obtained, but significant infrastructure costs and complexity increase
Solution Approach 1:
Existing mobile robots that perform logistics tasks are equipped with additional sensors to also perform data collection and tracking functions. The robots serve dual purposes: their primary logistics function and the secondary function of gathering shop floor data, eliminating the need for dedicated tracking infrastructure.
Solution Approach 2:
The mobile robots autonomously collect and transmit shop floor data during their normal operations. The system updates master data automatically using sensor information from the robots, reducing manual intervention and infrastructure requirements while maintaining data accuracy.
2Device complexity
If manual checking and prediction methods are used to keep shop floor information up to date, then infrastructure costs are reduced, but data accuracy and timeliness deteriorate
Solution Approach 1:
Manual prediction and checking methods are replaced with automated sensor-based measurement systems mounted on mobile robots. The sensors continuously capture actual shop floor states, providing accurate and timely data without requiring complex infrastructure or manual intervention.
Solution Approach 2:
The system continuously collects real-time data from sensors on mobile robots and uses this feedback to automatically update master data. The closed-loop feedback mechanism ensures data remains accurate and current by comparing sensor measurements with stored master data and making corrections as needed.
3Extent of automation
If sensors and processing units are added to mobile logistics robots for data collection, then automated and accurate shop floor tracking is achieved, but device complexity and cost increase
Solution Approach 1:
Sensors originally designed for robot navigation and operation are leveraged for additional data collection functions. The same sensors that help robots navigate shop floors are also used to capture asset locations, buffer utilization, and production status, achieving automation without proportionally increasing complexity.
Solution Approach 2:
Data collection functions are merged with the existing robot control and navigation systems. The processing units that already exist for robot operation are extended to handle shop floor data processing, combining multiple functions into existing hardware rather than adding separate dedicated systems.
Data Source
AI summary
A production plannings of products and goods or shop floor logistics in producing, trading or distributing products/goods is provided in which it is addressed to maintain or keep data about the production planning of the products and goods or the shop floor regarding the logistics in producing, trading or distributing the products and goods up to date, and at least one mobile logistics robot to automate a logistic transport of the products, the goods or production material for the products and goods within a shop floor is equipped each with a sensor technology appropriate to measure or capture and control a current state or changes of the shop floor by sensor data, when each the robot is managed by a fleet management system for distributing or scheduling logistic tasks among the at least one robot executing transport tasks of a transport task queue maintained by an automated logistics planning system.