TLDR: Please help me build a smelting array that doesn’t get jammed with single pieces of stone / iron plates in the furnaces.
I’m playing a ribbon world and I’ve designed an industrial smelter, where a train full of ores pulls in, everything is smelted, then the same train leaves with all the finished products.
The problem is that furnaces get jammed with single stones or iron plates when I’m trying to make stone bricks or steel. I need all furnaces to empty completely so that they are ready for the next train which may hold different materials.
I can read the incoming material from the train (and there will never be mixed materials on a single train) and set the stack size accordingly, but the stack size behaviour isn’t exact - an inserter will grab only one item if only one item is available rather than waiting for a full stack. Maybe there’s a mod to change this behaviour?
Edit to add screenshot and blueprint
Blueprint
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
Right, so it sounds like in total the amounts match, but they are unevenly distributed. I.e. at the end one furnace has 1 iron plate while another has 4.
If you give each furnace its own input chest, limit all chests so they are in total same amount as the train carriages, feed them with a loop so all ore ends up in a chest, and postpone inserting into furnaces until all chests are loaded, it will work.
To postpone insertion, a circuit latch that turns off when train arrives and on after a circuit timer would be my choice.
That’s a good idea, I like that. It will be slower to get started but I couldn’t think of anything that would work in vanilla. Thanks!
I’ve got a fully working solution now thanks to your help. It’s not optimal in terms of throughput but it is optimal in terms of the flavour I want for this world, which is exactly what I wanted
Cool! Can you share a picture? :D
This is version 3 of the smelter, with all the combinators combined into a little computer instead of spread everywhere. It works almost every time, but there’s a rare bug where sometimes the inserters start unloading the train before I’ve read the contents of the train… not sure how. But I’ve updated it so it can handle trains of any fill level as long as they carry a multiple of 100 items.
Nice layout! That is pretty compact, given the complexity.
Thank you! :)