Search Results (Searched for: )
- trackwhack
- trackwhack
Today 10:10
Replied by trackwhack on topic Perpetual License CAM
Perpetual License CAM
Category: Show Your Stuff
@becksvill
We expect to release a Five Axis product in Jan 2027. It will be a separate product and we expect to price it at a similar 199 USD on launch and 399 USD after.
We are also aiming to release TakshakTurn by the same timeline and once again it will be a separate product with similar pricing.
Overall, we will never have a subscription model, it will always be a one time purchase.
btw .. our 3 and 4 axis strategies beat the crap out of what Fusion offers. If you are willing to try it. There is a 30 day money back guarantee.
We expect to release a Five Axis product in Jan 2027. It will be a separate product and we expect to price it at a similar 199 USD on launch and 399 USD after.
We are also aiming to release TakshakTurn by the same timeline and once again it will be a separate product with similar pricing.
Overall, we will never have a subscription model, it will always be a one time purchase.
btw .. our 3 and 4 axis strategies beat the crap out of what Fusion offers. If you are willing to try it. There is a 30 day money back guarantee.
- tuxcnc
- tuxcnc
Today 08:14
"Ethercat is faster" is not a valid argument, because anything that is faster than the required minimum will be sufficient.
Replied by tuxcnc on topic Industrielle Linux CNC 5achs Fräsmaschine
Industrielle Linux CNC 5achs Fräsmaschine
Category: General LinuxCNC Questions
We don't talk about what is used in industry and why. We are talking about using Ethercat in a machine controlled by LinuxCNC. And here we have factors such as the availability and quality of documentation, sample configurations, or tools, and here Ethercat loses to Mesa. Therefore, I believe that unless there are compelling arguments for Ethercat, it is better to use Mesa.
"Ethercat is faster" is not a valid argument, because anything that is faster than the required minimum will be sufficient.
- Becksvill
- Becksvill
Today 07:55
Replied by Becksvill on topic Perpetual License CAM
Perpetual License CAM
Category: Show Your Stuff
hey this looks pretty cool. i just spend some time going through your videos and website
have been using cam for several years. started with fusion 360 but got sick of autodesk so went to bobcam with solidworks which is pretty good.
not as easy to use as fusion but more powerfull finishing tool paths. though i prefer the fusion adaptive tool paths. Obvously i prefer open source as most linuxcnc people will do so looking at freecad as its getting better.
I find with my normal cam workflow i use adaptive clearing roughing for most stuff and facing cycles etc. and then some sort of steep shallow type tool paths. so a combination of parallel and 3d contour
do you think it would be possible to offer anything for 5 axis positional stuff. i have a large 5axis that i want to try out soon. and currently no options for cam. my stuff only does 4 axis.
cheers
have been using cam for several years. started with fusion 360 but got sick of autodesk so went to bobcam with solidworks which is pretty good.
not as easy to use as fusion but more powerfull finishing tool paths. though i prefer the fusion adaptive tool paths. Obvously i prefer open source as most linuxcnc people will do so looking at freecad as its getting better.
I find with my normal cam workflow i use adaptive clearing roughing for most stuff and facing cycles etc. and then some sort of steep shallow type tool paths. so a combination of parallel and 3d contour
do you think it would be possible to offer anything for 5 axis positional stuff. i have a large 5axis that i want to try out soon. and currently no options for cam. my stuff only does 4 axis.
cheers
- muddiver
- muddiver
Today 07:38
Replied by muddiver on topic Kommunikation mit Mesa 7i92 sehr instabil, Woran kann es liegen?
Kommunikation mit Mesa 7i92 sehr instabil, Woran kann es liegen?
Category: Deutsch
Good Morning together!
the switch to r8168 did the trick for me! Communication is running, i can not say how solid, but now i can start LinuxCNC without error, and the green LED keeps flashing. Thanks for your help!
Do you think i should stay on 2.9.10 as i am now , to keep my system running?
Or how often does LinuxCNC change the Kernel during updates?
I'm not keen on holding my breath after every update if the communication is broken..
Greets, Tom
the switch to r8168 did the trick for me! Communication is running, i can not say how solid, but now i can start LinuxCNC without error, and the green LED keeps flashing. Thanks for your help!
Do you think i should stay on 2.9.10 as i am now , to keep my system running?
Or how often does LinuxCNC change the Kernel during updates?
I'm not keen on holding my breath after every update if the communication is broken..
Greets, Tom
- cmorley
- cmorley
Yesterday 02:08
Replied by cmorley on topic Error in tool_offsetview.py
Error in tool_offsetview.py
Category: Qtvcp
Hey great! I pushed the file changes.
Thank you.
Thank you.
- tommylight

Yesterday 02:05
Replied by tommylight on topic EDM retrofit
EDM retrofit
Category: CNC Machines
1. I use Mesa for everything.
2. Not sure, but i think those are EXE something or another, and yes, LinuxCNC should work with them, from what i read here.
3. Yes, see Mesa THCAD
4. Guessing, stepper with current control should do, servos should also do, but for more info/ideas look for BAX EDM on youtube.
2. Not sure, but i think those are EXE something or another, and yes, LinuxCNC should work with them, from what i read here.
3. Yes, see Mesa THCAD
4. Guessing, stepper with current control should do, servos should also do, but for more info/ideas look for BAX EDM on youtube.
- tommylight

Yesterday 01:41
Replied by tommylight on topic Looking for consultant
Looking for consultant
Category: General LinuxCNC Questions
Todd, would be perfect for that, and he is in USA, IIRC.
- tommylight

Yesterday 01:20
Replied by tommylight on topic Anilam 1100 and Mesa 7i97t
Anilam 1100 and Mesa 7i97t
Category: Milling Machines
Seems like outputs, but, clean the chips and the board so we can see numbers and copper lines.
- tommylight

Yesterday 01:11
Replied by tommylight on topic Paid Consulting Opportunity
Paid Consulting Opportunity
Category: QtPyVCP
Not me, despite really needing the money, i never charge for any help here or when initiated from here, and i am of no use for Probe Basic, yet.
For other things related to LinuxCNC, i am here often and daily, so feel free to shoot questions here.
For other things related to LinuxCNC, i am here often and daily, so feel free to shoot questions here.
- Estley
- Estley
Yesterday 00:52
Replied by Estley on topic Probe Z offset
Probe Z offset
Category: QtPyVCP
Ah, it sounds pretty obvious once you think about it. Thanks!
- dang133
- dang133
Yesterday 23:56
Paid Consulting Opportunity was created by dang133
Paid Consulting Opportunity
Category: QtPyVCP
Hi everyone,
My team is using ProbeBasic / Linux CNC on a 5-axis CNC milling machine we are developing. We've got most everything up, but don't have the INI file for the machine working properly. To be specific, we're getting a lot of out of bounds and tool change errors. Many (most) of the example NGC files that come with LinuxCNC don't work. We fix one thing just to run into another blocker. We could use some paid help.
If you're interested, email This email address is being protected from spambots. You need JavaScript enabled to view it. with the following:
We'll get back you super soon.
Thanks so much!
My team is using ProbeBasic / Linux CNC on a 5-axis CNC milling machine we are developing. We've got most everything up, but don't have the INI file for the machine working properly. To be specific, we're getting a lot of out of bounds and tool change errors. Many (most) of the example NGC files that come with LinuxCNC don't work. We fix one thing just to run into another blocker. We could use some paid help.
If you're interested, email This email address is being protected from spambots. You need JavaScript enabled to view it. with the following:
- Your name / email / phone
- Resume (highlighting LinuxCNC work)
- Your general coding / management style
- What time zone you're in
- Your desired rate
We'll get back you super soon.
Thanks so much!
- rodw

Yesterday 23:42
Replied by rodw on topic Probe Z offset
Probe Z offset
Category: QtPyVCP
yeh, pretty sure its the same as qrdragon. Define your probe as a tool and record the height as you would any other tool, I used T99 for the probe.
- quark
- quark
Yesterday 23:34
Looking for consultant was created by quark
Looking for consultant
Category: General LinuxCNC Questions
Hi, I run a Wood manufacturing company. We currently have about eight routers. We have done a significant amount of customization of our current equipment and are looking to shift to Linux CNC and build several machines from the ground up in the next year including a feedthrough four axis machine, and a CNC lathe. I’m looking for a consultant to help guide us through this process. We have an engineering team in house. We are based in Utah. Proximity is nice, but not necessary. If you know somebody who might be a fit or would be interested yourself, I would love to hear from you.
- rodw

Yesterday 23:32
Replied by rodw on topic Industrielle Linux CNC 5achs Fräsmaschine
Industrielle Linux CNC 5achs Fräsmaschine
Category: General LinuxCNC Questions
Nonsense. ethercat drives whole factories. The advantages of ethercat remain regardless of the size of the machine. Ethercat should be a more efficient protocol than mesa hm2 so it should have more efficient bandwidth utilisation. Linuxcnc won't care if you use mesa or ethercatIn my opinion, Ethercat is a great solution for small machines that can use integrated drives.
I have mills where the individual axes are connected to the rest of the machine via a one patch cord and one power cord, and things like homing limit switches or other sensors are connected locally to additional drive inputs.
Such a machine is simple to wire and, in my opinion, more reliable.
However, if all the control is to be located in one cabinet and long and multi-core cables are to be run, Ethercat loses its advantages for now. It's just expensive and difficult to set up, and what's best about it becomes secondary...
- RLA
- RLA
Yesterday 22:56 - Yesterday 23:00
Replied by RLA on topic 5 axis tool offset
5 axis tool offset
Category: CAD CAM
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[/img]
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