Planning and scheduling for additive manufacturing at a factory scale opens up an incredible array of possibilities, but also corresponding challenges. At the top of those challenges is the fact that AM – or colloquially 3D printing – tends to get hung up on a single, time-consuming step.
The upside is that with AM there is an opportunity to fit multiple components onto the same build plate, so they can be produced in parallel while incurring marginal additional time costs.
This whitepaper is about finding ways to optimize the process and incorporate the best aspects of 3D printing and traditional manufacturing together to create a better future for everyone.
This model was presented at the 2018 International Conference on Automated Planning and Scheduling. We believe this new model we explored can be extended into an end-to-end optimization model that captures all the discrete decision-making challenges in AM.