– DISCLAIMER –
– THIS IS NOT ABOUT CAD –
– THIS IS ABOUT DESIGN –
I have a theory. If an idea is good it will occur in what seems like a vacuum and then one day you will find it by accident but it will be somewhere else and it will probably predate whatever you thought of by some considerable period of time.
Remember those toys that were about design and actually building things. What if those toys grew up in to series tools and manufacturing processes.
Maketron is likewise design ( AnD ) patterns ( AnD ) nodes in software for the world of real things and the real world.
In the kind of system I am talking about the user asks for objects
These objects themselves generate constraints widgets and interaction with which they can be managed.
Design possibilities exist as arrangements of these complex object definitions held together with constraints that have captured expertise.
In many instances this looks like inverse kinematics but the intent is different.
When engaging with such a system you always have somewhere to begin and something to choose from and answers to your design questions.
You may have heard of this before as ECAD or EDA.
“Electronic design automation (EDA or ECAD) is a category of software tools for designing electronic systems such as printed circuit boards and integrated circuits. The tools work together in a design flow that chip designers use to design and analyze entire semiconductor chips.”
That seems to me a pretty limited definition of ECAD which to my mind is really just about solving paths as is inverse kinematics.
This definition is not to be confused with an expert system
In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning about knowledge, represented primarily as if–then rules rather than through conventional procedural code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of AI software
In the Makertron the more complex the object the more sophisticated the interaction that it asks for.
You can get some feeling for this in the Makertron interface itself.
You can also see how tools can gradually scale in complexity to meet the requirements of components.
For example the bezier curve tool for the handle bars.
Each bezier curve controls a portion of a standard bicycle drop bar geometry.
It captures the sort of expertise you might find in an article like this
When a node editor is added you begin to get a system that perhaps looks something like this ,
This is completely the inverse of a third generation cad tool which typically has a work flow that will consist of
- Solids Editor
- Assembly Tool
It takes on average two semester modules at University to learn the basics of Autodesk Inventor.
Four semesters to learn Catia.
Add another year to be even vaugely proficient and actually start doing something useful. Then add another year to that before you can begin to even consider trying to manufacture the things you have drawn.
While your at it add an engineering degree and a life time of workshop experience to build something safe / useable competent.
Cad is complicated. It is a world of tiny annoying things and by the time your done the creative impulse will be long gone and you will have an enormous grey beard and the world of real things will be long forgotten.
This is I feel one of the largest obstacles to changing how we design things and ultimately how we manufacture them.
Quite a bit of difference exists between the capture of expertise and giving people somewhere to start and the notion of capturing ideas from the crowd and honing those down to a series of winners Quirky
Quite a bit of difference exists between a box full of tools and an empty work bench Tinkercad