The End of CAD
By Dr. Joel Orr

Design: The ordering of intentions.

Design is mystical. Something does not exist...then it does. I think it is a special way of touching the mind of God, validating Man's having been created "in the image of God."

Design is not deterministic. Given a set of requirements, there is no formula into which they can be pumped to yield an optimum design-or even a good one. The process of design is invariably one of trial and error.

Fascinatingly, and counterintuitively, the process offers no promise of convergence: That is, there is no guarantee that if we perform more trials, we will somehow get closer to an optimum design. So, great designs are all the more impressive for that.

For centuries, the only improvements in the design process were in documentation-stable media, better pencils and pens, mechanical drafting aids, electric erasers, eradicating fluid, pin registration, and copy machines. In his 1950 science fiction story, The Door Into Summer, Robert Heinlein described "Drafting Dan," a keyboard-controlled drawing robot whose essentials began to be realized in the early CAD systems of the '60's.

Then came 3D, photorealism, kinetic motion-and design documentation acquired more and more verisimilitude at the pace of Moore's Law, by which computing power increases ten-fold every three to four years.

Design can be characterized as a dialectic, a term used by the philosopher Hegel in his attempt to explain the spasmodic rhythms of the unfolding of history. While it may not work well in history, it does work for design: In the design dialectic, the "thesis" is the concept in the mind of the designer. The "antithesis" is the external manifestation of the design-drawing, model, or prototype. Then the designer brings the thesis to bear on the antithesis, to yield the third stage of the dialectic-synthesis. This is usually a refined model or prototype, which becomes the "thesis" for the next cycle.

And although there is no guarantee of convergence, designers need to iterate-to go through multiple cycles of the dialectic-to refine the design.

That's what makes the computer a great design environment: It is a place where detailed and accurate models can be built quickly and inexpensively, and quickly tested to reveal their inadequacies, thus providing the basis for another iteration.

But for the design environment to be truly wonderful, it must be capable of as complete and precise a model as can be achieved-and as complete an environment as possible in which the model can be embedded. For example, the behavior of a product can best be modeled in a "world" in which "gravity" and "friction" are provided by the computer.

Simulation models can be produced either by analysis or by synthesis. Analysis is the hard way; you determine precise mathematical equations to represent the functioning of all parts of the model. Since many behaviors are difficult to represent in this way, building such a model can prove impossible.

The synthetic approach makes no assumptions about underlying mechanisms; instead, it simply seeks to produce a "converter"-an equation or a mechanism-that imitates reality: Given the same set of inputs, it produces outputs similar to those of the actual system being modeled.

This behavioristic approach is at the root of the powerful therapy called "neurolinguistic programming," or NLP. Ideally*, practitioners are taught to observe behaviors, and not to attempt explanations. The fact that a person makes certain behavioral choices does not "mean" anything-except perhaps that they are "stuck," and need to know about other choices available to them. No assumptions are to be made about what people think or feel.

Similarly, we can create simulation models that behave like the things we are modeling, without knowing-or caring-whether the mechanisms that convert the inputs to the outputs are in any way the same. For example, the famous "flocking" algorithm published by Craig W. Reynolds in 1987 models the behavior of flocks of birds, schools of fish, and other groups in motion, by applying simple rules to the behavior of each member of the simulated group. The visual effect is astonishingly realistic-and we do not need to know or care if birds or fish use a similar set of rules to govern their behavior when they move in groups.

"End" has multiple meanings. It can mean the terminus, the final point; it can also mean the goal. In the title of this essay, I used it in both senses. I believe that the terminus of all CAD will ultimately be the creation of simulation models, and also that the goal of computer-aided design is in fact simulation-that simulation is the highest form of computer-aided design.

Simulation is still a specialty, but it ought not to be; anyone involved in thinking about products should be able to "see them work" on the screen, where mistakes are easy and inexpensive to find and fix. We are not there yet-but if CAD vendors listen to me, in a few years we will be.

But it is not only the design of products that can benefit from simulation. The design of processes-engineering and manufacturing workflow, for example, or even information flow within an enterprise-must be designed. And the complexity of those systems makes them even better candidates for simulation than product design!

If you want to help your company realize the full potential of engineering, think about modeling the business and the role of engineering in a simulation; one tool that can help you do it simply is ithink (http://www.hps-inc.com).

But however you do it, do it: help your organization consider the full context of its business.

* Sadly, that ideal is not often achieved, but that's another article.