Estimated reading time: 9 minutes

Design of Experiments

1. Drill methods: (-) resharpened 4-8 times (0) resharpened

2. Drill diameter: (-) 0.008” (0) .014” (+) 0.020”

3. Infeed rate: (-) xx in. per min. (0)  xx in. per min (+) xx in. per min

4. Construction: (-)Std. Foil-Lam (0) Thick-prepreg w/foil-Lam (+) Std. Core-Lam.

The results are the hole quality (rms roughness %) and max. innerlayer mushrooming in microns.

The best quality was 0 microns mushrooming and

The fourth experiment, shown in Figure 4, is to further find the highest hole quality and to look at drilling productivity. The variables and levels were a fractional factorial design of three variables at two levels:

1. Drill method:  (-) new drills (+) resharpened 6 times

2. Stack height: (-) 1 high (+) 3 high 

3. Panel venting dams: (-) no-flow dams  (+) full venting dams

The results are the hole quality (rms roughness %) and max. innerlayer mushrooming in microns.

The best quality was < 4% rms hole-wall roughness using a plane of new drill bits for stacks of 1-high  with any appropriate venting dams. Analysis shows that the old resharpened drills could be used with drill stacks 3-high and has a usable hole-wall roughness but it interacts with drill infeed rates.

Figure 4: Two more examples of DOE for hole quality in multilayer boards. Full factorial design on the left was conducted to optimize drilled hole quality. Fractional factorial DOE on the right further optimizes hole quality and production productivity.

Notice that this last experiment was a fractional factorial. The power of a scanning experiment using the fractional factorial methodology is that N number of variables can be reviewed with only N+2 experiments. This is useful to find main effects, but not interaction, while later experiments will provide examination of interactions and optimization.

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