Samsung electronics co., ltd. (20240201638). METHOD AND DEVICE WITH PROCESS DATA ANALYSIS simplified abstract
Contents
METHOD AND DEVICE WITH PROCESS DATA ANALYSIS
Organization Name
Inventor(s)
Namyeong Kwon of Suwon-si (KR)
METHOD AND DEVICE WITH PROCESS DATA ANALYSIS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240201638 titled 'METHOD AND DEVICE WITH PROCESS DATA ANALYSIS
The abstract describes a method and device for process attribution identification using machine learning models.
- The method involves generating a process result using a machine learning model with input data containing feature values for multiple process features.
- Sample data is generated by modifying reference data based on dependencies between process features.
- An attribution of process features is identified based on the generated process result and sample process result using machine learning models.
- The process aims to improve the understanding of the relationship between process features and outcomes.
Potential Applications: - This technology can be applied in various industries such as manufacturing, healthcare, finance, and more to optimize processes and improve efficiency. - It can be used in predictive maintenance systems to anticipate equipment failures based on process data analysis.
Problems Solved: - Helps in identifying the key factors influencing process outcomes. - Enables better decision-making by understanding the impact of different process features.
Benefits: - Enhanced process optimization and efficiency. - Improved predictive capabilities for future outcomes. - Better understanding of complex process relationships.
Commercial Applications: Title: "Process Attribution Identification Technology for Enhanced Efficiency" This technology can be commercialized as a software solution for industries looking to streamline their processes and improve overall performance. It can be marketed to manufacturing companies, healthcare providers, financial institutions, and other sectors seeking to leverage data for better decision-making.
Questions about Process Attribution Identification Technology: 1. How does this technology differ from traditional process analysis methods? - This technology utilizes machine learning models to identify process feature attributions, providing a more data-driven approach compared to traditional methods.
2. What are the potential challenges in implementing this technology in real-world applications? - Challenges may include data quality issues, model training complexities, and the need for domain expertise to interpret the results effectively.
Original Abstract Submitted
a method and device with process attribution identification are provided. the method may include generating a process result using a first machine learning model provided input data, where the input data incudes feature values corresponding to a plurality of process features, generating sample data by a first modifying of at least a portion of reference data based on dependency between two or more of the plurality of process features, where the reference data includes a plurality of feature values for a reference process result, identifying an attribution of the plurality of process features based on the generated process result and a sample process result generated using the first machine learning model, or a second machine learning model related to the first machine learning model, provided the generated sample data.
