Machine Program Analysis for Digital Thread Defect Tracing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for creating a 'digital thread' in manufacturing are labor-intensive and error-prone due to incomplete serialization, making it difficult to automate the analysis of vast amounts of low-level machine data and trace defects back to upstream programs and machines.
Innovation Solution
A system and method for machine program analysis that determines program series used in manufacturing by analyzing low-level machine data, using algorithms like HyperLogLog for distributed cardinality estimation, and determining relationships between programs to automate the identification of program series and reduce manual work.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual methods are used to create digital thread in manufacturing, then completeness of serialization can be maintained, but labor intensity and error rate increase significantly
Solution Approach 1:
The system enables automated self-service by using machine data to automatically trace and identify program series without human intervention. The algorithm autonomously processes low-level machine data, performs intersection analysis, and reconstructs manufacturing sequences, eliminating manual labor while maintaining serialization completeness through systematic data processing.
Solution Approach 2:
The patent replaces manual mechanical processes with automated computational systems. Instead of human operators manually tracking and recording manufacturing data, the system uses algorithms to process machine data, calculate intersections, and automatically reconstruct program series, substituting mechanical human labor with automated information processing.
2Productivity
If automated tools are used to analyze vast amounts of low-level machine data, then productivity increases, but system complexity increases
Solution Approach 1:
The system segments the complex data analysis task into distinct modular components: data collection from machines, intersection calculation using HyperLogLog algorithms, program series identification, and defect tracing. This segmentation allows each module to be independently developed, tested, and optimized, managing system complexity while enabling efficient automated processing of vast amounts of manufacturing data.
Solution Approach 2:
The patent introduces intermediary algorithms and data structures that mediate between raw machine data and final analysis results. The HyperLogLog algorithm serves as an intermediary for efficient cardinality estimation, and the program series reconstruction logic acts as an intermediary layer that transforms low-level machine data into meaningful manufacturing sequences, simplifying the overall system architecture.
3Measurement precision
If comprehensive data collection is performed to enable accurate defect tracing, then measurement precision improves, but data processing time increases
Solution Approach 1:
The system performs preliminary actions by continuously collecting and preprocessing machine data during normal manufacturing operations. Program series are pre-identified and stored as reference data before defects occur, enabling rapid defect tracing when needed. This preliminary data preparation maintains high measurement precision while reducing processing time during actual defect analysis.
Solution Approach 2:
The patent employs parameter changes by using HyperLogLog algorithms that provide approximate cardinality estimation with controlled error margins. This allows the system to process vast amounts of data efficiently by accepting bounded approximation in exchange for dramatically reduced processing time, while still maintaining sufficient precision for defect tracing purposes.
Data Source
AI summary
A method for machine program analysis, preferably including determining data for a set of programs and determining relationships between the set of programs, and optionally including determining an analysis based on the program relationships, acting based on analyses, and/or operating manufacturing system machines. A system for machine program analysis, preferably including one or more computing systems, and optionally including one or more manufacturing systems.