Which statement best describes how copper weight affects the overall thickness of a PCB?
Think about how adding more copper material changes the physical dimensions of the board.
More copper weight means thicker copper layers, which add to the total thickness of the PCB.
Given a PCB with 4 layers, each having copper weights of 1 oz, 2 oz, 1 oz, and 0.5 oz respectively, what is the total copper weight?
TotalCopperWeight = SUM({1, 2, 1, 0.5})Add all copper weights from each layer.
Sum of 1 + 2 + 1 + 0.5 equals 4.5 oz total copper weight.
Which visualization type best shows copper weight differences across multiple PCB layers clearly and accessibly?
Think about comparing quantities across categories clearly.
Stacked bar charts clearly show quantities per category and allow easy comparison of copper weights per layer.
Which data model design best supports analysis of PCB materials and copper weights by layer and board type?
Consider how to organize data for flexible filtering and aggregation.
A fact table with measures and linked dimension tables allows efficient analysis by layer and board type.
Given this DAX expression to calculate average copper weight per layer:AverageCopperWeight = AVERAGE('PCB Layers'[CopperWeight])
Which issue will cause this measure to return incorrect results?
Think about what happens if layers from different boards are mixed in the calculation.
Without filtering by board type, the average copper weight mixes layers from different boards, leading to misleading results.
