Manufacturing guy-at-large.

The six questions I think about when I think about industrial additive manufacturing

Added on by Spencer Wright.

Prompted by an impromptu back and forth with Jordan, I was compelled to write down the things I spend so much of my time thinking about. Some of these I have a better grasp on than others, but they're all problems that I'm excited to see developments on - and work on myself.

1. What are the process parameters that affect finished part shape?

I'm in the middle of a NIST report that goes through many of these. The sad thing is that knowing what the parameters are is only half of the battle; then, you need to control those parameters on-the-fly (which is not something that all machine manufacturers currently allow).

2. What are the most reliable and effective methods of measuring, recording, and processing those parameters?

Industrial additive manufacturing machines tend to be harsh environments for sensors and sensor hardware. Once we know what parameters to measure, we'll need to build measurement systems that are robust, accurate, and reliable.

3. Given two identical finished parts with two different production process chains (additive, subtractive, etc.), how can one determine which process chain will be more expensive to complete?

This is hard. I believe that it'll be easier to automate process chain comparison than it will be to automate process chain creation; in other words, coming up with a list of steps to manufacture a part will remain hands-on, but assessing the cost difference (time/money/energy) between two process chains will be increasingly automated. Regardless, these are big problems.

4. Given two different designs, each of which has the same end functionality, how can one determine which design will be more expensive to build?

This feeds into question 3. In many cases today, design decisions are made based on a hunch. If it were easier to estimate the production cost for parts with complex production process chains, designers would be able to make more informed decisions.

5. Given the same input design and two different additive build orientations, how can one determine which build orientation will produce the most high fidelity net near shape, at the lowest cost?

Also feeds into question 3. Manufacturing engineers need to pick a build orientation quickly and be guaranteed high fidelity end parts; today, those decisions are made mostly by gut. Bonus points if this data is also made available to designers, so that they can make even more informed design decisions.

6. Given the same input design and build orientation, how can one determine which support structure design will produce the most high fidelity net near shape?

Given the early effort that startups (namely 3DSIM) are putting into this question, it stands to reason that it's an easier one to solve than question 5. It's also possible that they think it'll be easier to commercialize support structure optimization software in the near future. Either way, I see this as just part of a bigger need that 5 and 6 are pointing at together: additive manufacturing engineers need better tools to set up and process builds.

These issues outline the biggest roadblocks that I've experienced on my path to commercially viable additively manufactured parts. If you have different experiences, or know of developments on what I've described here, I'd love to hear from you.