This discussion applies broadly to Quality but is also relevant to Environmental, Safety, Information Security, Laboratories, etc. If you have questions, please contact us (Connect) or call: (706) 318-5717.
Known Unknowns in Quality involve aspects or factors recognized as sources of uncertainty or variability. Their specific impact typically remains unclear or unquantified. We at Diversified Management Systems have developed these tips for your quality processes:
- Measurement Accuracy: The precision of quality measurements can be uncertain due to factors like instrument calibration, environmental conditions, and technique variability. Methods like Gage R&R, Measurement Systems Analysis (MSA), and Measurement Uncertainty Analysis help in understanding these uncertainties.
- Process Variation: Known variability in manufacturing might not have a fully understood impact on quality. Factors such as machine settings or material properties could be analyzed using techniques like Failure Modes Effects Analysis (FMEA).
- Human Factors: The influence of human operators or inspectors on quality outcomes includes variables like skill level, fatigue, or training. FMEA and studies on visual inspection reliability highlight these uncertainties.
- Raw Material Variability: Variations in raw materials due to sourcing or storage conditions affect product quality. Continuous monitoring and FMEA help in managing these known unknowns.
- Long-Term Reliability: Predicting how products will perform over time under various conditions is challenging. Techniques like FMEA, along with Mean Time to Failure and Mean Time to Repair analyses, are employed to estimate potential issues.
- Supplier Performance: The reliability of suppliers in delivering consistent quality introduces uncertainties that can affect quality control. Understanding and mitigating these involves ongoing assessment and FMEA.
Addressing Known Unknowns in quality control requires:
- Continuous Improvement: Through research, data analysis, and stakeholder collaboration.
- Resource Allocation: To investigate and reduce uncertainties.
Historical Insights on Risk Management:
- Diverse Team Input: Essential for comprehensive risk identification.
- Feedback Loops: Incorporating real-world outcomes into risk models enhances future predictions.
Training: Includes general risk management and specific techniques like Failure Modes Effects Analysis (FMEA).
By focusing on these known unknowns, organizations can bolster their quality control frameworks, leading to improved product quality and reliability.</
If you need help, please contact us (Connect) or call: (706) 318-5717.