7 QC Tools: Real-World Application in the Manufacturing Industry
Let’s see how the 7 QC tools can be used in a manufacturing industry scenario to address a quality issue.
Problem Scenario
A manufacturing company produces aluminum components for the automotive industry. Recently, they’ve been experiencing a high rejection rate in one of their product lines due to dimensional inaccuracies. The company uses the 7 QC tools to identify the root cause, implement corrective actions, and ensure quality improvement.
1. Cause-and-Effect Diagram (Fishbone Diagram)
Application in Manufacturing:
The quality team conducts a brainstorming session to map out potential causes of dimensional inaccuracies.
Key Categories:
- Manpower: Operator errors during setup
- Machine: Calibration issues with CNC machines
- Material: Variations in raw material thickness
- Method: Inconsistent measurement techniques
The fishbone diagram points to machine calibration as a critical factor.
2. Check Sheet
Application in Manufacturing:
The team designs a check sheet to record the frequency of dimensional defects over three shifts.
Insight:
The data reveals that the defect rate is highest during the night shift, suggesting possible operator errors or fatigue.
3. Control Chart
Application in Manufacturing:
A control chart is used to monitor the dimensions of randomly sampled components over a week.
Observation:
The chart shows that most measurements fall within control limits, but sporadic outliers occur during the night shift, confirming the issue is not inherent to the process but shift-specific.
4. Histogram
Application in Manufacturing:
A histogram is created using the data from the check sheet to analyze the variation in dimensions.
Finding:
The histogram shows a significant skew towards smaller dimensions, indicating the cutting tools may be wearing out more quickly than anticipated.
5. Pareto Chart
Application in Manufacturing:
The team creates a Pareto chart to prioritize the most common causes of rejection.
Result:
The chart highlights that 70% of rejections are due to machine calibration issues and 20% from operator setup errors.
6. Scatter Diagram
Application in Manufacturing:
The team plots a scatter diagram to study the correlation between machine calibration intervals and defect rates.
Conclusion:
A strong negative correlation is observed: as the time since the last calibration increases, the defect rate rises significantly.
7. Flowchart
Application in Manufacturing:
A flowchart is created to map the current calibration and setup process.
Bottleneck Identified:
Operators lack a clear protocol for rechecking calibration after machine maintenance.
Implemented Solutions
- Machine Maintenance: Increased the frequency of CNC machine calibrations.
- Operator Training: Conducted night-shift training on setup procedures.
- Tool Monitoring: Introduced a wear monitoring system for cutting tools.
- Process Improvement: Updated the calibration process flowchart to include mandatory checks after each shift.
Results
After implementing these measures:
- The rejection rate dropped by 40% within the first month.
- Night shift performance improved, reducing variability in dimensional accuracy.
- Customer satisfaction scores increased due to consistent quality.
Conclusion
By leveraging the 7 QC tools, the manufacturing company not only identified and resolved their quality issues but also established a proactive approach to continuous improvement. This demonstrates how these tools are invaluable for identifying root causes, prioritizing corrective actions, and optimizing manufacturing processes.
