Manufacturing Control Chart for Statistical Indicators
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Solution Overview
Problem
Current manufacturing processes face challenges in simultaneously monitoring and controlling multiple statistical indicators for quality assurance, leading to increased analysis time and manufacturing costs, particularly in high-production environments like the aeronautical industry.
Innovation Solution
A process that calculates and combines multiple statistical indicators, such as capability indices and centering coefficients, into global validation, sanction, and control sets, allowing for automated analysis and adjustment of manufacturing conditions based on measured characteristic dimensions, enabling simultaneous monitoring and control of multiple indicators on a single graphical representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple statistical indicators are monitored separately using traditional control charts, then comprehensive quality information is obtained, but analysis time and manufacturing costs increase
Solution Approach 1:
The patent combines multiple statistical indicators (Cp, Cpk, Ccm, Pp, Ppk, Ppcm) into a single integrated control chart that displays all indicators simultaneously. This merging approach allows comprehensive quality monitoring without requiring separate analysis of each indicator, thereby reducing analysis time while maintaining complete quality oversight.
Solution Approach 2:
The control chart is designed to serve multiple functions simultaneously: it monitors process capability (Cp, Cpk), process centering (Ccm), and predicts future quality performance (Pp, Ppk, Ppcm). This multi-functional design eliminates the need for multiple separate charts and analysis procedures, reducing both time and computational resources required for quality monitoring.
2Manufacturing precision
If multiple statistical indicators are monitored separately, then quality control coverage is improved, but device complexity and manufacturing costs increase
Solution Approach 1:
The patent integrates multiple statistical indicator calculations and visualizations into a single control chart interface. This consolidation reduces the complexity of the control system by eliminating the need for multiple separate charts and analysis tools, while still providing comprehensive quality control coverage through simultaneous display of all indicators.
3Productivity
If production rate is increased, then productivity improves, but quality control capability deteriorates
Solution Approach 1:
The control chart calculates and displays future quality performance predictors (Pp, Ppk, Ppcm) based on current process data. This preliminary assessment allows quality issues to be identified and addressed before they manifest in actual production defects, enabling maintain high production rates without compromising quality control capability.
Solution Approach 2:
The control chart provides real-time feedback on process capability and centering through multiple statistical indicators. This immediate feedback mechanism allows operators to quickly adjust process parameters to maintain quality standards even as production rates increase, preventing quality deterioration that would normally accompany higher productivity.
Data Source
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AI summary
The invention relates to a process for manufacturing parts that is based on the simultaneous analysis of a plurality of different statistical indicators representative of a characteristic size of the parts, in which: an overall validation set corresponding to a set-theoretic combination of the various validation sets of each statistical indicator is defined; an overall sanction set corresponding to a set-theoretic combination of the various sanction sets of each statistical indicator is defined; and an overall control set comprising the pairs (μ;σ) not contained in the overall validation set and in the overall sanction set is defined; and it is determined to which overall set, from the overall validation set, the overall sanction set and the overall control set, the pair comprising the mean μm and the standard deviation σm of the measured characteristic size belongs, and the manufacture is controlled depending on the overall set thus determined.