Kemeera Inc., (dba Fathom) (20240351287). Data Aggregation and Analytics for Digital Manufacturing simplified abstract
Contents
Data Aggregation and Analytics for Digital Manufacturing
Organization Name
Inventor(s)
Carlo Quinonez of Oakland CA (US)
Skyler Brungardt of Oakland CA (US)
Data Aggregation and Analytics for Digital Manufacturing - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240351287 titled 'Data Aggregation and Analytics for Digital Manufacturing
Simplified Explanation:
The patent application describes systems and methods for aggregating and analyzing digital manufacturing data. An aggregator collects data from digital manufacturing machines, filters it, and stores it in a database for clients to access via an API.
- The aggregator collects output data from digital manufacturing machines.
- The output data is filtered and transmitted to a server for storage in a database.
- Clients can access the data in the database through an API.
- The system can extract 3D printer data, transform it into a canonical form, and upload it to a network-based database.
- Client-centric messaging systems like Kafka are used for interaction between services.
Potential Applications:
This technology can be applied in various industries such as manufacturing, 3D printing, and data analytics. It can help companies improve their production processes, monitor machine performance, and make data-driven decisions.
Problems Solved:
This technology addresses the challenges of collecting, filtering, and analyzing large volumes of data generated by digital manufacturing machines. It streamlines the data aggregation process and provides clients with easy access to valuable insights.
Benefits:
The benefits of this technology include improved data management, enhanced decision-making capabilities, increased operational efficiency, and better overall performance in digital manufacturing processes.
Commercial Applications:
Potential commercial applications of this technology include offering data analytics services to manufacturing companies, developing software solutions for digital manufacturing optimization, and providing consulting services for implementing data-driven strategies in production environments.
Prior Art:
Prior art related to this technology may include existing data aggregation and analysis systems in the manufacturing industry, as well as technologies used for monitoring and optimizing digital manufacturing processes.
Frequently Updated Research:
Research on advancements in digital manufacturing technologies, data analytics tools, and communication systems can provide valuable insights for further development and improvement of this technology.
Questions about Digital Manufacturing Data Aggregation and Analysis:
1. How does this technology improve the efficiency of digital manufacturing processes? 2. What are the key features that set this data aggregation and analysis system apart from existing solutions?
Original Abstract Submitted
systems and methods for aggregating and analyzing digital manufacturing data are disclosed. an aggregator can collect output data generated by a number of digital manufacturing machines. the output data can be filtered and transmitted to a server for storage in a database. one or more clients can access the data in the database via an api. this can extract 3d printer data, transform it into a canonical form, and upload it to a network-based database. these services can interact using a client-centric messaging system like kafka or, more generally, a message manager. when a client's producer sends a message, the messaging system responds that the message request either can or cannot be processed. if the message can be processed, then the aggregator sends the message; otherwise the producer can retry at a future time.
