Prague, Czechia

David Grossenbacher

This inventor holds 1 USPTO granted patent and 2 published patent applications and 1 EPO patent. Top assignee: Siemens Aktiengesellschaft. Active years: 2026.

USPTO Granted Patents = 1 

% Patents Active = 100.0

 

Average Co-Inventor Count = 6.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: David Grossenbacher - Innovator in Conveyor Line Control Systems

Introduction: David Grossenbacher is an inventor based in Prag 6-Dejvice, Czech Republic. He is currently employed at Siemens Aktiengesellschaft, where he focuses on innovations in industrial automation and control systems. Although he has not yet been granted any patents, his work is significant in the field of logistics and conveyor systems.

Latest Patent Applications: David Grossenbacher has submitted several notable patent applications. One of his latest applications is titled "Control of Conveyor Line Installations for Items of General Cargo." This process involves controlling a conveyor line for general cargo, which includes multiple consecutive conveyor line portions, each driven by a separate drive. The system utilizes sensors to detect general cargo and employs a computing unit that uses a machine learning model to optimize the control of the drives based on real-time occupancy data.

Another significant application is "Management of Processes with Temporal Development into the Past, in Particular of Processes Taking Place at the Same Time in Industrial Installations, with the Aid of Neural Networks." This application addresses the complex control of logistics systems with parallel conveyor lines. It demonstrates how neural networks can simulate and identify temporal and spatial dependencies in industrial installations, enhancing the efficiency of package handling.

Conclusion: David Grossenbacher is a promising inventor whose work at Siemens Aktiengesellschaft focuses on advancing conveyor line control systems through innovative applications of machine learning and neural networks. His contributions to the field are expected to have a lasting impact on industrial automation.

Profile summary based on public USPTO records.
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