2018-08-27 3 min read


Planning & Strategy.

Making & Manufacturing.

  • After something like four years sneaking around the metal printing circuit, Velo3D finally announced what they've been working on: A step improvement in laser metal powder bed fusion, with "up to 90%" first article success rates. As it happens, I've seen their systems in operation and they've printed a few of my parts with few to no support structures whatsoever. The whole process is impressive, beginning with their dedicated build prep software (which does melt pool simulations and pre-deforms the part to compensate for thermal stresses), to their zero-contact recoater (the official word on how this works is "magic"), to their 15-minute fully automated changeover time. Oh, and also they can apparently stack parts vertically in the build like it's SLS. Each of these is a pretty big deal for metal printing, and Velo also announced that they've already got three systems out in the wild at customer sites. I'm looking forward to more here...
  • BYD announced plans for a large lithium ion battery factory. Once it and another planned facility come online, their total capacity will be about 60 GWh/year. For comparison, CATL had a capacity of about 17 GWh in 2017 (with plans to double that) and Tesla's current capacity is about 20 GWh (with plans to reach 50 GWh).
  • Boston Dynamics says that they'll build 1000 SpotMinis by the end of 2019; it's unclear what the robots will do.
  • Tailored fiber placement is a process by which functional fibers (carbon, etc) are sewn onto a substrate to be used as preforms for fiber reinforced composites.

Maintenance, Repair & Operations.

Distribution & Logistics.

Inspection, Testing & Analysis.

  • A really excellent overview of always-on home appliances: "Cable boxes alone account for almost 1.5% of the total residential energy usage in the US." Listen to the whole podcast here - it does a very good job explaining the decisions that result in this level of consumption, and the criticism it lobs towards Comcast et al is measured and totally appropriate.
  • A multi-part series (start here) on using unsupervised machine learning (plus a bunch of additional data processing) to automatically detect anomalies in CNC machining.


Audi's electric motor assembly process.

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