A Moore’s Law for 3D printing

Moore’s Law (transistors per chip) and Hendy’s Law (pixels per dollar) have been useful predictors of where processing power and digital photography were going. Tech thinker and write Johnny Ryan believes something similar would be really useful for 3D printing. He already tried to plot a law for the quality of print per dollar of 3D printers for an article he has been working on for the McKinsey Quarterly, but he doesn’t have the data. So he needs your help to gather it. What he wants, is to plot something along these lines: quality (lower microns etc. + multi-materials) improves at the same cost every X months/years. Plotting this would help people plan for, and benefit from, the disruption of 3D printing.

3D printing will create massive opportunities. But it will also disrupt many businesses. According to Dr. Ryan, we need to be able to plan properly for it to get the best out of this transition. A Google spreadsheet has been set up where anybody can contribute data points to at: https://spreadsheets.google.com/spreadsheet/ccc?key=0AvV-pHeoX7ZYdG1OQkVNRVFnTEZLd3NoVUdHMTBIS2c&hl=en_US.

The data he needs are the following:

At least one machine per year (where possible, at the low end of the market) showing:

  1. the resolution in microns (1/1000 of a millimeter, or 0.001mm) that it could achieve, and,
  2. where relevant, the materials that the build machine works with. In particular (i) how many materials of different properties (including colors) can the machine print in, and (ii) the degree to which they can be blended,
  3. Update 25/Aug/2011 – additional data requirement: Speed (mm per sec),
  4. Update 25/Aug/2011 following suggestion from Ulf Lindhe – cost of materials. Expressed as material cost per gram of printed output.

It will also be important to have the price per unit (this may include supporting equipment necessary to operate the machine). In general, the machine should be at the lower price end, rather than a high price innovation.

Find out even more on Johnny Ryan’s blog or follow him on Twitter.