Production Unit Inlet Occupancy Control for Flexible Goods Transport
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current warehouse management systems in production environments face significant deviations between real and assumed component stocks, leading to inventory surpluses and shortages, inefficiencies, and high maintenance costs, limiting flexibility and automation in logistics.
Innovation Solution
A method for determining transport data using occupancy, component, and procurement data, processed by an optimization algorithm, to optimize the transport of components between production units and storage locations, ensuring accurate inventory management and flexible logistics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional warehouse management systems are used, then inventory management is maintained, but significant deviations occur between actual and assumed component inventories leading to excess inventory and idle time
Solution Approach 1:
The system performs preliminary actions by continuously monitoring occupancy status of storage locations and calculating procurement data in advance. The optimization algorithm determines transport requirements before actual component shortages occur, enabling proactive replenishment rather than reactive responses to inventory deviations.
Solution Approach 2:
The system implements feedback mechanisms by continuously comparing actual occupancy status with assumed inventory levels. Sensor data provides real-time feedback on component locations and quantities, allowing the system to correct deviations between actual and assumed inventories and adjust transport plans accordingly.
2Reliability
If rigid supply algorithms are used, then inventory control is maintained, but maintenance costs and system complexity increase significantly
Solution Approach 1:
The system transitions from rigid, static supply algorithms to dynamic, adaptive algorithms that continuously adjust transport plans based on real-time occupancy status and procurement data. The optimization algorithm dynamically recalculates transport requirements as conditions change, providing reliable inventory control without requiring complex manual intervention.
Solution Approach 2:
The system enables self-service by allowing the optimization algorithm to automatically determine transport requirements and generate transport plans without external intervention. The system monitors its own inventory status and autonomously initiates replenishment processes, reducing the complexity of manual inventory management while maintaining control reliability.
3Extent of automation
If traditional logistics systems are used, then basic transport functions are provided, but flexible automation of logistics according to Industry 4.0 is not possible
Solution Approach 1:
The system achieves flexible automation by dynamically changing parameters such as transport timing, routing, and prioritization based on real-time occupancy status and procurement data. The optimization algorithm adjusts transport parameters adaptively to meet varying production requirements, enabling Industry 4.0 level logistics flexibility while maintaining high automation levels.
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
The invention relates to a method for providing transport data (8) for controlling a goods transport in a production environment (1), comprising the following steps, in order to allow more flexible and more reliable logistics: - determining occupancy data (5) on the basis of sensor data of a sensor unit (4) on the production unit (2), wherein the occupancy data (5) relate to an occupancy state of at least one goods inlet (3) of a production unit (2) in the production environment (1) with stored components, - determining component data (6) which indicate which components are required at the production unit (2) for a production order assigned to said production unit (2), - determining procurement data (7) for the required components, wherein the procurement data (7) indicate how long transport of a required component (2) from a relevant storage location to the production unit (2) is expected to take, - determining transport data (8) depending on the occupancy data (5), the component data (6) and the procurement data (7), wherein the transport data (8) describe a transport process to be carried out.