Soldering lightsaber

The fastest soldering ever

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I am obsessed with creating the quickest soldering station ever. If a sports car can go from 0 to 60 in less than 3 seconds, I want my soldering iron to go from 25*C to 400 in 2 seconds. Between picking it up from the stand and touching its tip to the PCB it should be ready to fire. The answer to this challenge? Machine learning on a simple microcontroller.

Beginnings and purpose

   I created another soldering iron in the past and I've been improving the firmware ever since then.

   This soldering station has the following sensors which I plan to keep on this new iteration and use in the new firmware algorithm: Tip temperature, PCB temp (and initial ambient temperature), Voltage measurement sensor, Internal timer. 

   So these pictures I uploaded into the gallery are the actual prototype I experiment with. It uses the PCB from the Hakko Revenge project and once I'll have some measurable results with the firmware I plan to move ahead and design a 2020 PCB version for this one. 

   Since I use a t12 (or Ts100) tip which can heat up really quick, I was able to achieve good heating times. This previous project of mine goes up from the room temperature (25*C) to the soldering temperature (above 320*C) in about 6 seconds. Also, when it heats up from the standby temperature (190*C) to the soldering temperature it only takes about 3 seconds. Of counrse, this can only happen if I power it at higher voltages between 24 and 29V. 

   Fast, fast, fast! I always wanted to be able to make it faster and smaller and since I am redesigning everything now, I thought this is a good time to come up with a new approach. As you can see from these recent pictures, I also added a 0.96'' OLED display to it and now looks way much better. 

Why I cannot make it faster in the conventional way?

This type of t12 tip might be small and of a low mass, but it has the drawback of having the thermocouple connected in series with the heating element. This means that I have to power the heating element blindly for a while and then disconnect the power source and perform the temperature measurement on the same two wires. So this results in not being able to keep the heating element always on and it must be controlled through a PWM cycle that cannot be greater than 60 or 70% in some cases. So 30% of the time I have to read the tip, hence, I get to power the heating element less.

In order to make it even faster than it currently is, I tried to experiment with the PWM and with shrinking down the thermocouple reading times so I can expand the time frame for powering the tip. 

   It doesn't work. I cannot shrink down the sensor's reading window, since if I do the reading right after I apply power to the lines, I get all sorts of inductive noises bouncing off inside this circuit. So I really have to wait for some couple of ms for the line to quiet down before I can perform the reading of the thermocouple. I even tried to setup the PWM module to operate the heating element automatically at different frequencies and to only interrupt this PWM from time to time less often to perform the reading. I got the same thing and if I try to do the reading less often, then the tip's temperature becomes more bouncy and less accurate. So this was not a solution.  

Solution: May the force be with you

The solution i'm thinking of is to power the heating element at 100% PWM blindly, for an undefined period of time at startup. <grin> so not only I have a sports car that can do 0 to 60 in 3 seconds, but the driver is also blindfold. How can I power the heating element for the right amount of time without reading the temperature sensor not a single time during this operation and still stop at the proper temperature? Moreover, how can I do that at different input voltages or at different room temperatures?

   This is where the machine learning part comes in. I am planning to have the microcontroller sample different heating times at different input voltage values and then based on these dates, to work out a linear regression and estimate the necessary heating time. Then it should subtract the ambient temperature ∆⁰C variation from the nominal 25⁰C and add...

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Hakko revenge_5_bott.stl

New case that looks better with the OLED display

Standard Tesselated Geometry - 459.16 kB - 08/04/2020 at 04:09


Hakko revenge_5_top.stl

New case that looks better with the OLED display

Standard Tesselated Geometry - 78.60 kB - 08/04/2020 at 04:09


plain - 60.00 kB - 03/27/2020 at 07:00


Soldering lightsaber_1_bot.stl

Stl file for case

Standard Tesselated Geometry - 459.16 kB - 03/27/2020 at 01:18


Soldering lightsaber_1_top.stl

Stl file for case

Standard Tesselated Geometry - 75.08 kB - 03/27/2020 at 01:18


View all 7 files

  • Added a new look to the case

    Marius Taciuc08/04/2020 at 04:08 0 comments

    Check the Files section for the actual stl file.

  • Update firmware

    Marius Taciuc03/27/2020 at 07:10 0 comments

    In this 2.1 Firmware version I corrected the AI preheat function. It works much better now, avoiding overheating the tip due to pre-existent tip temperatures or ambient temperature. 

  • Added case files

    Marius Taciuc03/27/2020 at 01:22 0 comments

    Check the files section for the stl case models I added today

  • Added video demonstration

    Marius Taciuc03/20/2020 at 08:20 0 comments

    The video can be accessed on this project's page or at:

    Stay tuned as I might be adding firmware updates in the future. 

  • Added first firmware

    Marius Taciuc03/18/2020 at 12:34 0 comments

     Tested this today and it works fine. So far so good. 

    I'm going to paste two of the functions that are responsible with handling the regression here so you can see them without opening the code file. 

    I have to mention here that I got inspired by this video which helped me implement the mathematical regression in this firmware. So if you want to research more, here's the link to the video:

    Credits and thanks to Eugene O'Loughlin for posting this video. 

    This version is pretty stable for experimenting with it and I think there is no major risk at this point. Like I mentioned in previous instructions, if you want to replicate this project, please read the disclaimer on this project's page first and exercise caution at all times. 

  • Testing the regression

    Marius Taciuc03/12/2020 at 06:24 0 comments

    I finished reading the learning procedure and I was able to take the first samples for my linear regression. I then manually created quick graph, because I was so curious if this data could really be estimated as a line and how accurate my automatic predictions could be. 

    The results are pretty promising.  

View all 6 project logs

  • 1

    I plan on adding the first code draft, which I write and test now. But before I do so, I want to leave this disclaimer here. 

    !!! Disclaimer - read this !!! 
    This firmware is purely for experimental and demonstrative purposes. This AI firmware is not the final tested version and it could take erroneous decisions that could lead to hazards. The designer assumes no responsibility for any of these consequences. Hazards could include, but are not limited to: severe injuries, explosions, domestic fires, death.
    !!! Exercise caution at all times when testing it at your own risk !!! 

    I just get chills when I think that I entrust a 50W - 400*C heating element into the hands of a self learning, decision making machine who could set my house on fire when I leave the room. Errr! So please be careful. At least in the prototype phase until we conclude that is safe. 

  • 2
    How to connect the 0.96'' OLED display

    Like I said, before I redesign this, I will use the PCB from my previous project. I uploaded the layout here so you don't have to go looking for it. This is how I connected the OLED display and the LED. 

    Then I bent the LED underneath the display and used a thicker piece of copper wire to secure the OLED into position like in the picture below:

    I am planning to use that backlight LED to illuminate around the knob of the encoder. Or I might print a transparent case and the LED will shine through. 

View all instructions

Enjoy this project?



kempil wrote 07/01/2021 at 14:51 point

Hi Marius, can you provide the schematic?

  Are you sure? yes | no

salmanisheikh wrote 08/26/2020 at 15:02 point

where is the parts list? I got PCBs made for the project.

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valle wrote 06/10/2020 at 17:32 point

Hey Marius,

love the idea! Great project and very interesting. I, too always find that soldering irons do take too long.

About your AI firmware part:

I would recommend a slightly different approach. You could model the soldering iron with all its thermal capacities, resistances and temperatures and use an unscented kalman filter to determine these. It's sort of like your linear regression but on steroids. This should allow you to get pretty accurate results and it continuously readjusts itself to the environment.

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salmanisheikh wrote 04/19/2020 at 03:04 point

how much is the pcb to make? I uploaded the board to pcbway but need to see the quote. Was looking for cheaper than oshpark as it’s a bit pricey there (but helping US over China if I get from osh Park and purple 🙂)

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ralf.waldukat wrote 03/28/2020 at 10:47 point

You could also implement a negative thermal resistance.

The problem is that when you connect your soldering iron to the thing to be soldered the temperature drops. This can be offset. But you are feeling the temperature of the heating element, not the tip, and not of of the thing which is soldered.

There are multiple resistances in the way. You could cancel those out in Software. So if the heating element is outputting 40W you would have to lift the target temperature by xx degree to offset the thermal resistance.

The same is done in expensive power supplies.

And yes, you have to be careful with positive feedback loops ;) Ideally you shouldn't set a resistance which is higher than the lowest possible resistance.

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Dan Maloney wrote 03/04/2020 at 16:39 point

An interesting idea. I look forward to updates.

  Are you sure? yes | no

Marius Taciuc wrote 03/11/2020 at 06:57 point

Thanks, Dan. So far, so good. The firmware seems to be coming together nicely and I will soon post a first draft and maybe a short video of the prototype. Stay tuned. Blessings from PNG.   

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