Production Data Linking for Multi-Process Visualization
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Solution Overview
Problem
Current techniques for monitoring production lines do not provide a means to visually represent collected data, limiting user understanding of production processes and potential issues.
Innovation Solution
A data collection device that links production data with product identifiers across multiple processes, generating visualization data to represent changes in production work values over time, allowing for graphical representation and differentiation of data for each product.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is collected from each process in the production line, then the quantity of production information is improved, but the ease of visualizing and understanding the data deteriorates
Solution Approach 1:
The patent segments the collected production data by process stage, organizing data from multiple processes into distinct temporal segments. Each process's data is separated and associated with its corresponding time period, making the large volume of collected data manageable and visualizable through structured segmentation.
Solution Approach 2:
The patent introduces an intermediary data structure that links process identifiers with time period information. This intermediary organization layer connects the raw collected data with visualization requirements, enabling easy graphical representation without losing the quantity of collected information.
2Reliability
If data from multiple processes is collected and associated with product identifiers, then the reliability of production monitoring is improved, but the device complexity increases
Solution Approach 1:
The patent implements a universal data collection framework that handles multiple process types through a single standardized interface. The collection device uses unified data structures and association methods that work across different processes, reducing overall system complexity while maintaining reliable multi-process monitoring.
Solution Approach 2:
The patent changes the organizational parameters of collected data from process-specific formats to a unified time-period-based structure. By transforming data organization parameters rather than adding complex process-specific handling, the system achieves reliable multi-process monitoring with reduced complexity.
3Measurement precision
If detailed production data is collected for each process, then the measurement precision of production metrics is improved, but the difficulty of detecting and measuring anomalies increases
Solution Approach 1:
The patent organizes detailed production data into periodic time segments corresponding to different process stages. This periodic structure allows precise measurement within each period while simplifying anomaly detection by establishing regular patterns against which deviations can be easily identified.
Solution Approach 2:
The patent adds a time period dimension to the detailed production data, transforming it from a flat multi-process dataset into a structured multi-dimensional dataset. This dimensional organization maintains measurement precision while enabling easier anomaly detection through temporal pattern recognition.
Data Source
AI summary
A data collection device includes a data collection unit that collects data of a data item related to production work from a production line that produces a target through a plurality of processes, and an acquisition unit that acquires an identifier of the target produced in the production line. For each process, the data collection device links the identifier of the target with data collected from the process during a period in which a production operation is performed on the target in the process, and generates visualization data visualizing the data of each process linked with the identifier.