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Manufacturing Readiness Level (MRL) ASSIST

Manufacturing Readiness Level (MRL) Assist Tool  tool is designed to allow continuous insight into manufacturing, quality, production, and industrial-base risks to acquisition programs and technology development efforts. For more information visit: https://www.mrlassist.bmpcoe.org/


Eight Levels of Analytics Model by SAS



1. Standard Reporting
        - Historical perspective
        - Standard KPI or data parameters
        - Focused on short term goals and objectives

2. Customized Reporting
        - Flexible reporting
        - Focused on problem solving
        - Historical perspective

3. Drill down analysis
        - Root cause analysis
        - Stratification analysis
        - Used extensively in DMAIC processes

4. Alerts and Notification
        - Management by exception
        - Pre-defined business process
        - Real-time feedback

5. Statistical Analysis
       - Correlation analysis
       - Discriminant Analysis
       - Regression Analysis

6. Forecasting
        - Trends
        - Pattern recognition
        - Decision making capability

7. Predictive Modeling
        - Prognostics
        - Data driven decision

8. Optimization
        - Enable innovation
        - Continuous improvement
        - Adaptive feedback


Reference: http://www.sas.com/news/sascom/2008q4/column_8levels.html

Spindle Bearing Degradation Monitoring

Unexpected failure of spindle bearings can lead to severe part damage and costly machine downtime. Finally, it will affect efficiency and productivity. The Watchdog Agent bearing monitoring system performs diagnostic tasks to detect bearing defects, visualize them, and then quantify defects on a different stage. It provides an illustrative and quantitative explanation on high-speed machine maintenance for spindle health.



Challenge
Isolate bearing defect vibration signature from environmental noise
Predict bearing remain life with high-speed machine working environment

For easier detection of bearing defects, the envelope detection technique has been used together with Fast Fourier Transforms. First, Envelope Detection (ED) at the spindle system resonance frequency located in high range is applied. The amplitude demodulation by ED allows detection of localized bearing defect without interference of noise vibration from other structural sources.



Finally, artificial intelligent algorithm (self-organized map) is applied to recognize different defect vibration pattern and quantify the defects at different stage. The bearing monitoring tool is embedded in Watchdog Agent Machine Health & Maintenance system to facilitate the engineer in understanding the current condition of spindle bearing and diagnosing bearing defects.