Automated SPC Data Wrapper for Real-Time Trend Analysis
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Solution Overview
Problem
Current statistical process control (SPC) methods face inefficiencies due to manual and time-consuming data collection and analysis processes, leading to reactive decision-making based on historical data rather than real-time information, which hampers proactive quality control and predictive modeling.
Innovation Solution
An automated system for real-time collection, extraction, transformation, analysis, and presentation of SPC information, using monitored information handling systems to generate and process data, apply new specification limits, and integrate predictive models for immediate corrective actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual data collection and analysis processes are used, then data processing can be performed with simple systems, but the process becomes lengthy, time-consuming and inefficient
Solution Approach 1:
The system enables self-service through automated data collection, extraction, transformation, and analysis processes. The SPC system automatically accesses operational measurements, performs statistical processing, generates control charts, and identifies trends without manual intervention, allowing the system to serve itself in data processing tasks.
Solution Approach 2:
Manual mechanical processes of data collection and analysis are replaced with automated computational systems. The patent substitutes human-operated manual data processing with computer-based automated SPC systems that perform statistical analysis, generate reports, and identify trends algorithmically, dramatically improving efficiency and reducing time loss.
2Loss of information
If data is collected and analyzed over a predetermined period, then comprehensive historical data is available, but real-time monitoring and predictive capabilities are reduced
Solution Approach 1:
The system implements continuous data collection and analysis rather than periodic batch processing. The SPC system continuously monitors operational measurements, performs ongoing statistical processing, and maintains up-to-date control charts and trend analysis, ensuring information is always current and available in real-time for immediate decision-making.
Solution Approach 2:
The system performs preliminary statistical processing and analysis on data as it is collected, preparing information in advance for immediate use. By continuously performing statistical calculations and maintaining ready-to-use control charts and trend analyses, the system has predictive information prepared beforehand, enabling proactive rather than reactive decision-making.
3Reliability
If reactive decisions are made based on historical data, then decisions can be made with available information, but proactive quality control and predictive modeling are hampered
Solution Approach 1:
The system implements continuous feedback loops where statistical analysis results feed back into the monitoring process. The SPC system uses control charts and trend analysis to provide ongoing feedback about process performance, automatically identifying when trends indicate potential quality issues before they occur, enabling proactive corrective actions that improve reliability while maintaining real-time predictive capabilities.
Data Source
AI summary
A system and method is disclosed for the automated real-time collection, extraction, transformation, analysis and presentation of statistical process control (SPC) information. One or more monitored systems or processes generate operational process control information that is stored in its native form. An SPC system iteratively accesses this information, transforms it as required, and performs statistical processing to generate database tables, control charts and other predetermined forms of data output. The statistical processing output is then extracted by an automated SPC data extraction system in real-time. The extracted data is placed in a data wrapper and submitted, likewise in real-time, to one or more statistical analysis systems or models, which process the data to derive new specification limits. The new specification limits are applied to monitored systems and processes resulting in the generation of new operational measurements, which are in turn collected and processed. The process continues to repeat automatically, providing a real-time view of trends for involved control metrics.