Manufacturing Process Data Modeling with Feature-Space Proxels
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Solution Overview
Problem
Conventional data processing devices for manufacturing processes are time-consuming and costly, lacking versatility due to the need for individual modeling of each manufacturing facility, even for similar processes, which limits simulation accuracy and product quality optimization.
Innovation Solution
A data processing device that collects and analyzes data groups from various manufacturing processes, calculates effects for each step, divides the feature space to classify data groups by their effects, and outputs specific data for each region, enabling the calculation of 'Proxels' which represent the minimum data unit for similar changes in the manufacturing process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If individual modeling is performed for each manufacturing facility to improve simulation accuracy, then manufacturing precision is improved, but device complexity and time consumption increase
Solution Approach 1:
The patent creates a universal model that can be applied across multiple manufacturing facilities and process types. Instead of building separate models for each facility, the system develops a generalized model framework that handles various manufacturing processes (semiconductor fabrication, display manufacturing, etc.) and different process types (deposition, etching, coating, etc.) through a single unified approach, thereby reducing device complexity while maintaining simulation accuracy
Solution Approach 2:
The patent segments the manufacturing process into standardized process types and steps that can be universally modeled. By categorizing diverse manufacturing processes into common process types (such as deposition, etching, coating) and representing them through standardized process flow diagrams and data structures, the system enables a single model to handle multiple specific processes without requiring facility-specific customization
2Manufacturing precision
If individual modeling is performed for each manufacturing facility to improve simulation accuracy, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The universal model framework allows the same model to be rapidly deployed across multiple facilities without requiring time-consuming individual modeling efforts. The model can be applied to different manufacturing facilities and process types through parameter configuration rather than complete model reconstruction, significantly reducing the time required to achieve accurate simulations
Solution Approach 2:
The patent performs preliminary analysis to identify common process types and patterns across different manufacturing facilities before creating the universal model. By pre-categorizing processes and establishing standardized data structures and process flow representations in advance, the system eliminates the need for repetitive modeling work when analyzing new facilities, thereby reducing overall modeling time
3Measurement precision
If conventional data processing is performed to improve analysis capability, then measurement precision is improved, but loss of time and cost increase
Solution Approach 1:
The patent creates simplified representative copies of complex manufacturing processes through process flow diagrams and standardized data models. Instead of processing raw data through complex facility-specific analysis routines, the system uses pre-defined process templates and representative process models that capture essential process characteristics, thereby maintaining analysis precision while significantly reducing processing time and computational cost
4Measurement precision
If conventional data processing is performed to improve analysis capability, then measurement precision is improved, but adaptability decreases
Solution Approach 1:
The system achieves both high measurement precision and broad adaptability through its universal model framework. The model can accurately analyze data from diverse manufacturing facilities and process types by using standardized process representations and common analysis methodologies, eliminating the need for facility-specific analysis procedures while maintaining precision across different process types including semiconductor fabrication, display manufacturing, and various coating and deposition processes
Data Source
AI summary
A highly versatile data processing is implemented on data collected in a manufacturing process. A data processing device includes: a calculation part configured to collect a plurality of data groups associated with a predetermined step of a process, and calculate effects in the predetermined step for each of the plurality of data groups; a dividing part configured to divide a feature space such that a distribution of each of the plurality of data groups associated with the predetermined step in the feature space is classified for each of the calculated effects; and an output part configured to output specific data that specifies respective regions of the divided feature space.