I'm now pretty familiar with SolidCAM (a SolidWorks CAM plug in), and I've had a look at the screen shots and sales blurb for a bunch of others. I am not impressed.
The state of the art CAM seems to be stuck on an unnecessary plateau: Slick but dumb. The user is presented with a fixed toolbox of slightly adaptive machining strategies and expected to choose an appropriate sequence of them to apply to various parts of the stock in order to produce an acceptable result. The process is both slow and demanding of human skill and attention, and the results are far short of optimal.
The better tools do have some optimisations that help a bit: Adaptive step over when milling with a ball nose, to limit the scallop to some maximum height; Feed rate adaption to varying cutting load; Solid modelling so that later machining steps only cut the material left by previous steps; etc.
However, this falls far short of what is possible: fully automatic generation of a far more optimal set of machining instructions. It seems to me that the local definitions of a good cut are fairly simple. A cut that is within the capabilities of the machine, at optimal feed rate and chip load, leaving only an acceptable scallop, and not gouging the part, is a good start, and would be better than the current approach can uniformly produce.
Ratings for all of these cut properties can be calculated, and a single merit function could be a weighted product of those ratings. This allows us to use any local search strategy to generate a complete tool path, by creating a sequence of locally (near) optimal cuts.
Global merit would include completing the task in minimum time, with minimum machine and cutting tool wear, with maximum quality. A simple hill climb optimisation would produce an improved but still substantially sub-optimal path. Simulated annealing, a genetic algorithm, or similar, would further improve the result.
In future posts I'll propose an algorithm in detail and get in to the implementation details, with the intention of cutting alpha release code in python and starting an open source project to get this in practical use.