MCCI: Hackathon
challenging an industrial challenge
Milling is a widely used manufacturing process. It subtracts material from a block to provide a part that can be used in an assembly. This removal is done by a rotating cutting tool that cuts material away resulting in material chips and a (hopefully) smooth surface. And this is where the story of MCCI starts.
When the cutting tool cuts into the material, chatter can occur. This chatter are practically speaking vibrations where the cutting tool is not at the target height. As a result, the surface is not smooth but has chatter marks. While chatter is difficult to avoid, the detection of chatter is very helpful. Once detected, the operator of the machine or even the machine itself can change parameters to reduce the effects.
Challenge the challenge - get hands on at kaggle - deadline is October 5th
AI-Model for chatter detection in milling
make the machine feel chatter before it occurs
In this hackathon, the starting point is a model that was developled by AIRISE. But we think, there must be someone out there to create a better solution. This is the challenge.
- check out the existing model and understand its performance
- use the data and see how signals change when chatter occurs
- come up with your own idea to develop a solution that detects chatter early
- submit your solution
We have created a challenge on the kaggle platform. It will be open from June 28th.
If you achieve a more robust implementation or an implementation that detects the chatter earlier than the given one, then please submit. We will rank the achievements according to the criteria as listed on the platform.
We will promote good solutions and we offer benefits to the best ones. Come and talk to us if anything is unclear.