Manufacturing Data Mapping for Position-Based Process Optimization
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Solution Overview
Problem
Existing manufacturing processes, such as glass manufacturing, face challenges in optimizing process parameters due to the complexity of data collection and analysis from various stages of the process.
Innovation Solution
A computer-implemented method that transforms time-sequenced manufacturing data into a positionally-dimensioned data structure, allowing for the determination of new process parameter values using algorithms, thereby optimizing the manufacturing process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manufacturing data is collected from multiple data sources and stages, then the completeness and accuracy of process analysis is improved, but the complexity of data collection and processing increases
Solution Approach 1:
The patent segments manufacturing data into distinct categories (process parameters, quality parameters, equipment data) from different stages (melting, forming, annealing, coating). This segmentation allows systematic collection and processing of data from multiple sources while maintaining organizational structure, thereby improving analysis accuracy without overwhelming complexity
Solution Approach 2:
The patent introduces an intermediary data processing system that receives data from multiple sources, transforms it into a standardized format, and prepares it for analysis. This intermediary layer simplifies the complexity of direct multi-source data collection by providing a unified interface and standardized data structure
2Loss of information
If time-sequenced data is transformed into positionally-dimensioned data structure, then the relationship between process parameters and product quality is clarified, but the data processing complexity increases
Solution Approach 1:
The patent transforms time-sequenced data into positionally-dimensioned data structure by mapping temporal data to spatial positions along the manufacturing line. This dimensional transformation clarifies the relationship between process parameters and product quality by showing their spatial correspondence, while the systematic transformation method manages the processing complexity
3Adaptability or versatility
If multiple parameters are monitored and analyzed simultaneously, then the comprehensiveness of process optimization is improved, but the computational requirements and processing time increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing and organizing manufacturing data into structured formats before analysis. Data is categorized, validated, and transformed into positionally-dimensioned structures in advance, reducing the computational burden during actual optimization and decreasing processing time while maintaining comprehensive multi-parameter analysis
Data Source
AI summary
Provided are a system, method, and computer program product for optimizing a manufacturing process. The method includes generating a time-sequenced data structure associated with a manufacturing process and transforming the time-sequenced data structure to a positionally-dimensioned data structure by identifying a zone for each parameter of a plurality of parameters, determining a time delay factor for each zone, and generating the positionally-dimensioned data structure using a data matrix transformation based on the time-sequenced data structure, each zone, and each time delay factor. The method also includes identifying a set of empty entries in the time-sequenced data structure or the positionally-dimensioned data structure and imputing data. The method further includes determining a new value for a process parameter value based on the positionally-dimensioned data structure and at least one algorithm and optimizing the manufacturing process based on the new value.