This Dashboard is designed using PowerBI
The dashboard provides a comprehensive view of supplier quality and its correlation with defect rates. It includes various visualizations that offer insights into overall performance, trends over time, and relationships between different metrics.
Key Insights:
Supplier Quality: The overall supplier quality score is 82.44, indicating a generally good performance. However, there's a significant range in scores (80.00 to 185.76), suggesting a need for more consistent quality management across suppliers.
Defect Rate Trend: The defect rate has fluctuated over the years. There have been periods of improvement, but also instances of increased defects. This indicates a need for ongoing quality control measures to address root causes and maintain consistent performance.
Supplier Quality vs. Defect Rate: There seems to be a general inverse relationship between supplier quality and defect rate. As supplier quality increases, the defect rate tends to decrease. However, this relationship is not perfectly linear, indicating other factors influencing defect rates.
Production Metrics: The production volume and production cost charts show a general increase over time. While there's no clear correlation between these metrics and defect rate, it's worth exploring whether increased production or costs might impact quality.
Maintenance Hours: The maintenance hours chart shows a steady increase, possibly indicating a need for more maintenance efforts to support increased production or address equipment issues.
Energy Consumption: The line chart reveals a general trend of increasing energy consumption from 2010 to 2018, with some fluctuations throughout the years. The highest consumption levels occurred in 2012 and 2014.
Energy Efficiency: The bar chart shows variations in energy efficiency across different months of the year. There are periods of high efficiency (e.g., around January and August) and periods of lower efficiency (e.g., April and December).
Additive Process Time: The line chart shows fluctuations in additive process time over the specified period. There are peaks and troughs, indicating variations in processing efficiency or complexity.
Additive Material Cost: The second line chart reveals a similar pattern for additive material cost. The cost fluctuates, potentially influenced by factors like material type, quantity used, and pricing.