Generative and Evolutionary Design in
Design Education
Teaching
Associate, University of Kassel, Department of Product Design,
Generative Design
Lab, Germany
e-mail:digitalpool@uni-kassel.de
Teaching
Associate, University of Kassel, Department of Product Design,
Generative Design
Lab, Germany
e-mail:ole_werner@web.de
Abstract
This paper discusses the experience made when starting to
establish “Generative and Evolutionary Design” as a new teaching subject in the
curriculum of our design department. It discusses different approaches,
successes and shortcomings in teaching this subject by presenting some
exemplarily projects of last years courses.
1. Why to teach Generative and Evolutionary
Design
The generative Design lab in Kassel was set up in 2001 as part of the Asia-Link program.
Subsequently we started to integrate Generative and Evolutionary Design as a
new teaching subject in course scheme
of our design department. Even though this field wasn't completely new in our
department – at least not since Prof. Dr. Hans Dehlinger started to teach in
Kassel (1) – we had to gain new experiences to establish it as a teaching
subject with beneficial effects for the design education as a whole. First of
all why should we teach Generative and Evolutionary Design?
Looking at the divers field of Generative / Evolutionary Design
and the wide variety of theoretical and methodical contributions we had to find
some common ground on which to base. We define Generative / Evolutionary Design
in a more open way, as rule based design (2) which is as well common in
‘normal’ design processes. This allows to meet students at their actual level
of knowledge and to bridge between "normal" Design and Generative /
Evolutionary Design. To discover and to formulate rule systems for design
problems trains design thinking and acting because it focuses on the generating
aspects of design practice. Especially in early stages of design projects one
tends to make decisions that have far-reaching consequences and may endanger
design thinking. These decisions are often unconsciously based on personal
views , historico-cultural or ideological background and narrow down the view
on the problem without reflected reasons. Additionally not only designers but
human beings in general also tend to conceive unknown and future situations on
the base of already known situations. They extrapolate something known instead
of inventing something new (3).
Teaching Generative / Evolutionary Design offers a good
opportunity to stimulate the conscious debate on design processes and design
decisions. Students gain new insights and become aware of certain
particularities that are typical for so-called wicked problems (4). It's very
difficult to describe design processes or to locate oneself within the process
while one is still in progress. Of
course one is able to justify decisions but just after the fact. To become more
aware of the process one needs to bring every single step to external, every
single decision even though the step seems to be unimportant for the
moment.This is exactly the point where the difficulties in using generative
procedures occur for most of the students. It is not the result they have to
focus on first but the description of the process. And this description needs
to be comprehensible not only for themself but for others as well.
„In other words, we must learn to design with our hands tied. To
design without the hand, using logic alone. The task is to „bring into the
open“ the (subconscious) thought processes at work in the brain, and make them
available to (verifiable by) anyone.“
Makoto Sei Watanabe, 2002 (5)
By setting up these description or rule systems the benefit for
the students gets obvious: they better understand the basic methodical
difficulties and properties of a design process and start to develop their
analytical competence in addition to their aesthetic one.
Despite these aspects there are many more that recommend teaching
Generative and Evolutionary Design, the keywords are: continuous digital
workflow, paradigm shift in modern science, increasing
interest
in dynamic systems, parallel development, changed human perspective due to
global interconnection, bottom-up design strategies ...
One aspect, we also would like to point out in this context, is
the development of mass customized products (6). The enhancement of computer
aided communication and production technologies as well as economic changes
during the last ten years led the way to this new type of products. Within
certain boundaries the design of these products (material and immaterial) can
be influenced by the customers suggestions and needs. In an ideal case it gets
tailored on the base of individual measurements and aesthetic preferences. Mass
customized products demand design concepts, that imply a range of different
instances and not one static design solution. Generative design methods are
very useful to fulfill this task because they always refer to solution spaces.
2. How to teach
Generative and Evolutionary Design
Upon discussing why we should teach Generative and Evolutionary
Design it is time to ask how to teach and how to integrate the new teaching
subject in the course scheme of our design
department. As we mentioned before the field of Generative / Evolutionary Design
is very wide. It includes too many approaches, ideas, concepts, methods and
tools to be taught just in one seminar and would cause confusion rather then
understanding.
The experiences form the first seminar “Generative Prozesse und
Verfahren” in 2001 made clear, that the expectation to bridge the gap between
understanding a new design concept and applying it successfully to a design
subject was somehow too optimistic (7). This first seminar was discussing
various examples of different methods in different fields of application
(design, art, architecture), accompanied by some subjects of broader interest
like e.g. methodical problems of Generative and Evolutionary Design. To
complete the seminar students should apply gained knowledge experimentally to a
design subject. Although not required, they have been encouraged to implement
their approaches as Ideas-macro-scripts.
Results and student feedback have shown that this was just too
much to deal with within only one seminar. It turned out that it was especially
necessary to draw a clear borderline between the Principles of Generative /
Evolutionary Design and its implementation on computers and applying Generative
/ Evolutionary Design in real design projects.
Consequently we split the wide field into three different groups
(8):
1. concept and principles of Generative / Evolutionary Design
2. implementation on computers (for example scripting courses)
3. applied projects
2.1 Teaching concepts and principles of Generative / Evolutionary
Design
Seminars of this first group can be seen as a introduction into
the field of Generative / Evolutionary Design. It imparts the basic principles
and methods with the help of various examples. The students gain an overview
and learn more about frequently used methods like Cellular Automata, Genetic
Algorithms, L-Systems, Neuronal Networks and others. To link knowledge and
practical experiences the participants
of the seminar have to apply their knowledge to different small exercises like
the Christmas Tree Generator (9):
The task of this exercise was to design a rule which will result
in the generation of a Christmas tree when being applied. Students have been
free to decide what method they want to use, how (and how strictly or vaguely)
it should be interpreted in the generative process. The goal of this exercise
was to give the students the opportunity to make a first experience with rule
based design. The results have been surprisingly playful and versatile as you
can see below [Fig. 1].
Fig. 1: Christmas Tree Generator
(Bruno Winter)
Even though it's likely to implement generative rules on a
computer, it's not necessary at all. The conception of rule systems is much
more important. To invent rules means to grasp somebodys intention. The
implementation may adopt differnt ways. It's often already sufficient to
generate some instances by hand and to
explain the system using illustrated flow charts.
To develop generative ideas, to analyse and understand existing
rule systems and to perceive Generative / Evolutionary Design as an enrichment
of ones design education have been the primary goals of this seminar.
Additionally the students should be encouraged to use their new knowledge
adequately in their future design projects.
To teach the unit described above, it does not always need a
seminar on its own. The content - not in it's total depth but partly - may also
be integrated in other courses like Prof. Dr. Hans Dehlinger did during last
years course on "theories and methods of planning".
2.2 Teaching the implementation on computers / Scripting courses
Although it's not implicitly necessary and although it's very time
consuming, there are advantages of teaching the implementation of generative
concepts on computers. It extraordinary helps (sometimes forces) the students
to train their analytical and logical competence. It can be compared with
learning a foreign language. It includes new vocabularies, orthography, syntax
and grammar. But the implementation on computers demands the most strict
notation and does not excuse the smallest inaccurateness. Due to this the
descriptive rule system needs to be worked out much more carefully and detailed
then students are used to. When they start to implement on a computer they
realize shortcomings in their rule systems they never thought of, even though
they were convinced to have thought of everything before. They would never have
noticed the potenential gaps without giving it a try on a computer.
Another important point is something we call, aha experience. The workflow of generative
design projects differ from what students are used to: it needs quite a lot of
time until first results can be seen. A lot of thinking needs to be done to set
up the right rules and constraints and
it's drawn-out work to implement these rules. These project stages are hard to
overcome and afford a lot of patience. But the minute the program runs, a bulk
of models can be produced.
In "normal" design processes students percive the
progress as slow but continious
- apart from some up and downs - while in generative design
processes they do not really see any progress for a long period of time until
they are finally confronted with this bulk of models. This aha experience it strongly related to the
power / speed of computers processing the rule system. It's not possible to
achieve the same strong impression and the same amount of generated models by
performing the rule system manually.
The CAD-education in the Department of Product design / University
of Kassel is among others based on the software platform Rhinocerous. Teaching
is done on two different levels: basic / advanced courses and upper grade
seminars.
To support students exploring Generative / Evolutionary Design a
new course, exclusively focusing on scripting the used CAD - software was set
up since 2003. The application programming interface of Rhinocerous enables the
user to write his own programs using Visual Basic Script or C++.
During this seminar students are able to gain basic knowledge
about scripting a CAD construction using Visual Basic Script and are asked to
apply this knowledge. According to a given task they have to write a small
program generating for example recursive line structures or pattern generators
[Fig. 2+3].
Fig. 2+3: Scripting results:
recursive line structures and pattern (printed on coffee cups).
Teaching goes along a web based tutorial that was developed
especially for this course using a lot of examples scripts gradually
introducing the world of programming. But to avoid frustration and increase the
efficiency of teaching, students are permanently supported by one or two
tutors.
This tutorial is considered as a tutorial in progress. It
continuously changes depending on
experiences made during the courses.
Besides the benefits for Generative / Evolutionary Design projects
the students gain much better understanding of CAD -tools and the mode of
operation behind the graphical interface and profit from this for all their
projects.
2.3 Applied projects
Generative / Evolutionary Design projects may have a strong
tendency to become a goal in itself.
Not only the resulting digital models may loose their relation to
the physical world; the design of a design "machine" may even become
the main purpose of the design process, completely neglecting the former
goal.To avoid this trap we introduced a third type of teaching, the applied
projects, These projects are following a tight outline and have to end up in
physical models or prototypes. They intend to close the appearing gap between
working on the abstract level of code but designing for physical reality. The
following section briefly presents two of these projects that have been carried
out this year.
3. Examples
3.1 Shelfgenerator
The shelfgenerator project was initiated during the winter term
2003/04. The students were asked to develop a generative design concept for
book shelves out of sheet material using different principles and starting
points and to detail it up to prototypes. Nine students finally came up with 5
different concepts, mostly parametric systems with some random influence.
The shelfgenerator "DimIt" is based on a flexible grid
system. The user can change the settings of the grid as well as parameters like
the total size of the shelf, the upper and lower boundaries of the compartment
size or the type of the compartments. As a function of these settings and
random input the program starts to allocate the compartments. The aim of this
generator was not the design of one special shelf but to solve problems of
space layout and division that can be applied to different aesthetic
appearances and and subjective views (10) of a shelf. The picture below [Fig.
4] showes one possible the shelf design and construction. It remains flexible
because its standardized elements can be assembled in more than just one way.
So you may run the program over and over again and look if it's possible to
build a new instance from your elements.
Fig. 4: Shelfgenerator
"DimIt", prototyp and CAD drawings (Emmy Galle, Frank Bayer)
Not random but music uses the following example. This
Shelfgenerator transfers midi-files into a structure of differently sized boxes
lined up in two rows on a wall [Fig. 5]. The user chooses a piece of music and
then selects two of several voices - one for each row of boxes. Subsequently
the program transfers length of a note, tone pitch and volume into a three
dimensional shelf structure. While the tone pitch and the length of a note
affect the size, the volume determines the color of the box. In the end the user can select an arbitrary
sequence of desired length from the generated shelf. Similar to the first
example, the problem to be solved is not only the design of a shelf but
proportioning in general. The results may be transferred to other design tasks
like glasses or vases as well.
Fig. 5: Generated
shelf structure form the song "spanish caravan" (Sibylle Manß, Ben
Kossmann)
2.3 Sweet Greens
Sweet Greens is a small lawn landscape partially covered from
roofs made out of fabric membranes supported by pneumatic structures. It was
realized as a permanent installation on an area of about 600 square meters next
to our department of product design in Kassel [Fig. 6].
Fig. 6: Sweet Greens, computergenerated
lawn landscape, 2004
The task of the project was not to design a lawn landscape but to
develop a program for the design of the lawn landscape (11). Within a
two-week-workshop the students should develop a generative idea of a possible
lawn landscape from some sort of vague description towards an intended program
implementation. The finally implemented program is based on parametric design
with some simple survive-or-die mechanisms and a certain random influence.
To run the Sweet Greens Generator the user defines (mostly
geometrical) constraints and selects
the desired plot. Most of the constraints can be limited with an upper and a
lower bound like the green radius range, the slope angle etc, others require
only a minimum or a maximum value.
Next the program loads and represents the chosen ground plot, that
consists of an area outline and restricted areas [Fig. 7]. No part of the
landscape is allowed to interfere these areas. Immediately the generator places
circles on the given plot and validates them by a series of checks. This
validation decides whether the circle remains or gets removed. This procedure
lasts until the desired amount of circles or placement attempts is reached.
Based on the position of the generated circles and limited by the chosen
settings, the program creates the landscape using the loft operation. Now the
program moves on to process the roof structure on top. When finished, the
generator draws a simplified, shaded version of the landscape with it's roof
structure and calculates the required amount of soil, an important criteria
because the students had to build the final landscape by themself.
Fig. 7: Sweet Greens Generator, round
plot and different stages of generation.
Looking at possible results the program is able to generate
something between non-usable fantasy landscapes and very boring structures. But
this mainly depends on the chosen settings and the ground plot. To use the
generator one has to experiment with the bounds to develop settings which are
tight enough to avoid the generation of nonsense and produce a variety of
results at the same time.
4. Outlook and Final
Remarks
The main goal of projects is to experiment with generative
procedures in a real design occasion. The particular interests have been to
experiment with programming as a method for structuring and supporting design
processes and to search for a generative solution which can be applied in
different environments and eventually transferred to other design tasks.
It has shown that teaching Generative and Evolutionary Design is a
highly valuable subject for design education. After taking the first barriers,
they start to clarify for themselves how they perform design, they better
understand the basic methodical difficulties and properties of a design process
and start to develop new competences.
To illustrate this, there is one encouraging example to be pointed
out: During a design project - that wasn't intended to be a generative or
evolutionary at all - one student picked up the generative idea, he learned
about in a different seminar one or two years before. His design of a lampshade
got stuck and he couldn't get any further until he gradually defined parameters
and rules for his design. The he implemented them as Rhino script and came up
with an astonishing amount of new solutions. These solutions not only showed
much more variety but were of higher interest as well.
Fig. 8: Lampshade Generator (Ulf
Cadenbach).
To give a brief outlook the next applied project is already on its
way: Computer generated in:ex:terior structures. This time it's not soil and
grass, the students will have to deal with, but concrete. In addition to form
generation we will try to integrate evolutionary structural optimization in
this project. For those who are interested in this project, see (12).
References
(1)Dehlinger, Hans (Hrsg.): Linienspiele: Mit dem
Computer erzeugte Strichstrukturen. Gesamshochschule Kassel Fachbereich
Produktdesign. 1984
(2)Galanter, P.:
What is Generative Art? Complexity Theory as a Context for Art Theory.
In: Soddu, C: Proceedings of 6th international conference
Generative Art. Generative Design Lab. Polytecnico di Milano. Mailand. 2003. p.
219.
(3)Dörner,
Dietrich: Die Logik des Mißlingens - Strategisches denken in komlexen
Situationen. Rowohlt
Verlag GmbH, Hamburg.1989. p. 190
(4)Rittel,
H. W. J.: Planen Entwerfen Design. Kohlhammer Verlag. Stuttgart. 1992. p. 77
and following.
(5)Makoto Sei
Watanabe: Induction Design. A Method for Evolutionary Design.
Birkhäuser
Verlag. Basel. 2002. p.7.
(6)
Piller, Frank T.: Kundenindividuelle Massenproduktion. Carl Hanser Verlag
München Wien. 1998.
(7)Schein
Markus: Next Generations Computer Aided Design - Next Generation CAD-Education?
In: iF International Forum Design GmbH: ICSID and Education Conference Critical Motivations and New Dimensions.
Hannover. 2003
(8)same as (7)
(9)www.generativedesign.de
(last visit: 11_04)
(10)Soddu,
C: Proceedings of 5th international conference Generative Art. Generative Design Lab. Polytecnico di
Milano. Mailand. 2002.
(11)Markus
Schein, Gregor Zimmermann, Ole Werner (Hrsg.): Sweet Greens - A
comuter
generated landscape. Books on Demand, Norderstedt. 2004
(12)http://www.uni-kassel.de/fb12/wwtwl/
(last visit: 11_04)