cpu-friendly setups (now with working screenshots :) )

[MaexxDesign]

Hello everyone !

I try to build as cpu-friendly as possible.
So, belts are no option.
That means as few robots as possible and direct feeding like this setup for red science:

red science.png (1.48 MiB) Viewed 3944 times

It produces 81 (<-- click) red science packs per minute and is upgradeable:

red science upgrade.png (1.98 MiB) Viewed 3944 times

Robots just have to transport ore to one blue chest.
The rest happens automatically.

For example:
4095 red science packs per minute (50x81) need about 150 robots (with worker robot speed level 21).

I have setups for all science packs and a few intermedicate products like rocket fuel, low density structure and rocket control unit for the rocket silo.

I would like to see similiar setups.

[Koub]

slightly off-topic, but can't display your images, they're hosted on a website with invalid certificates.
To avoid this problem, you should upload them on the forum directly instead.

[MaexxDesign]

Oh, thank you !

Should be fine now.

[Lubricus]

1. Perfect ratios is not always the most optimized for CPU but try to make it better with ratios in mind. You could for example let 1 gear assembler feed into 2 red science assembler.
2. You get better beacon coverage if the beacon rows are offset 1 tile to the assemblers. Move the bottom row of beacons 1 tile to the left or right
3. Long handed inserters should have enough throughput everywhere in your design (with max stack size research), it could enable more beacon.
4. Make it take resources from one train and dump the science packs into another (no need for CPU hungry bots)

[Lubricus]

Red science.png (1.7 MiB) Viewed 3720 times

This is what I come up with to counter your design. Hope someone can beat it. 6 beacon on each science assembler.
String:

Code: Select all

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