Author: Yeh-Liang Hsu, Chi-Yu Tai, Ting-Chin
Chen (1999-09-03); last updated: Yeh-Liang Hsu (2001-02-16);
approved: Yeh-Liang Hsu (2000-04-19).
Note: This paper is published in the Journal of Chinese Society of
Mechanical Engineers, Vol. 21, No. 4, pp.369-377, 2000.
A design process model based on
Design is a
dynamic problem solving process. All designs start with a problem to be solved,
and sub-problems are generated dynamically while solving the central problem.
To reflect this dynamic problem-solving process, this paper presents a new
design process model, which describes the ‘states’ of the product evolving
during the design process, instead of describing the design activities. The
design process is viewed as dynamically moving around a ‘product state space.’
A ‘product state’ is a representation of the product that the designers use to
generate information to answer or evaluate the current design sub-problem, and it
is usually represented by a design prototype. Mappings from design sub-problems
to proper product states are important design decisions. This paper starts by
describing design as a sequence of prototyping process. An industrial safety
helmet design example is used throughout the paper to demonstrate the ideas.
Then the product state space is defined. Finally this paper describes how the
design sub-problems are mapped to the product state space. Using this model,
designers are encouraged to focus more on “what sub-problem to solve,” “what
tool to use,” instead of “what activity should I do next?”
Keywords: design process model, design prototype,
plays an important role to the success of development of a product. Design
process influences performance, quality, cost, and developing time of the
product. Most researches in design process try to establish a structured model
to describe or facilitate design. Design process models are usually categorized
into descriptive models, prescriptive models, and cognitive models (Finger and
Dixon, 1989; Cross, 1994). According to Cross, descriptive models simply
describe the sequences of activities that typically occur in designing. These models
usually emphasize the importance of generating a solution concept early in the
design process. Prescriptive models attempt to prescribe a better or more
appropriate pattern of activities. They usually offer a more algorithmic,
systematic procedure to follow, and they emphasized the need for more
analytical work to precede the generation of solution concepts.
process models, descriptive or prescriptive models, divide the design process
into several sequential phases based on the essential activities that the
designers perform or should perform. These activities are often presented in a
flow chart manner, with feedback loops showing the iterative returns to the
earlier phases. Ulrich and Eppinger (1995) pointed out that structured design process
models are valuable because they make the decision process explicit, they act
as ‘checklists’ of the key steps in a development activity, and they are
largely self-documenting. Moreover, one goal of design research is to build a
computable design process model for realizing intelligent computer-aided design
systems (Takeda et al., 1990). A well-structured design process model will be
of great help for constructing such systems.
However, it is
arguable that the design activities described in the design process models are
general enough for designers of different experiences, and for various types of
design. Designers at different experience levels may start a design from
different phases. In the case study interviews, Baker et al. (1991)
demonstrated that experienced design engineers tend to directly generate
solutions to the problems given, rather than using structured design
methodologies. Based on new knowledge involved in the product, Culverhouse
(1993) classified design into four different types: repeat order, variant
design, innovative design, and strategic design. Four different ‘design routes’
were proposed for the four different types of design.
has one important characteristic that may not be fully reflected in the
structured design models: design is a dynamic problem solving process. All designs
start with a problem to be solved, and sub-problems are generated dynamically
while solving the original problem. Gero (1990) pointed out that designers
begin designing with incomplete information and before all the relevant
information is available. Actually design is an exploration process, as Gero
further stated, “what is relevant only manifests itself as the design proceeds
and varies with the decisions taken.” Most design process models model the
design process from the designers’ point of view, as a structured pattern of a
series of designers’ activities. Given the dynamic and unpredicted nature of
the possible design activities, it may be worthwhile to re-examine the design
process from how the design evolves during the design process.
presents a design process model in an attempt to reflect this dynamic
problem-solving process. Instead of describing a structured pattern of
designers’ activities and tasks in the design process, this model describes the
current ‘state’ of the product. A ‘product state’ is a representation of the product
that the designers use to generate information to answer or evaluate the
current design sub-problem. A product state is usually represented by a design
prototype. The design process is viewed as dynamically moving around the ‘product
starts by describing design as a sequence of prototyping process. An industrial
safety helmet design example is used throughout the paper to demonstrate the
ideas. Then the product state space is defined. Finally this paper describes
how the design sub-problems are mapped to the product state space. Using this
design process model, designers are encouraged to focus more on “what
sub-problem to solve,” “ what tool to use,” instead of “what activity should I
Design as a Sequence of Prototyping Process
mechanical design process, building prototypes is a very effective way to communicate and evaluate design ideas, learning
and solving design problems at hand, and discovering new design problems. A
general comprehension of the word ‘prototype’ is a physical approximation of
the product that is usually in full scale and fully functional, such as an a-prototype or a b-prototype. In design literatures, the
word ‘prototype’ has a much broader meaning. Wall et al. (1992) stated that “a
prototype is the first thing of its kind.” Their definition of a prototype
includes “both electronic and physical representations of the part or product.”
This definition has expanded the concept of a prototype from a physical
artifact into an electronic representation of the design, such as a CAD model
or a computer simulation.
Ulrich and Eppinger (1995) defined a prototype as
“an approximation of the product along one or more dimensions of interest;”
“any entity that exhibits some aspect of the product that is of interest to the
development team can be viewed as a prototype.” This
definition of a prototype has ranged from graphic ideas, system equations, computer
simulation, to fully functional prototype product. They further classified
prototypes along two dimensions: physical as opposed to analytical,
comprehensive as opposed to focused. The design of a trackball on notebook
computers is used as an example to illustrate the two dimensions. As shown in
Figure 1, prototypes generated in the design process of the trackball are put
on the two-dimensional plane. Ulrich and
Eppinger stated that for physical products, fully comprehensive prototypes must
generally be physical. Therefore
the fourth quadrant of the plot is labeled ‘not generally feasible.’ We think
that using certain technology such as virtual reality, we can build a prototype
that is comprehensive, while the prototype is still an analytical one. Therefore
the fourth quadrant of this two-dimensional plane should be feasible.
Figure 1. Prototypes generated in the design
process of the trackball (reproduced from Ulrich and Eppinger, 1995).
defined a design prototype as “a conceptual schema for representing a class of
generalized heterogeneous grouping of elements derived from alike design cases
that provides the basis for the start and continuation of a design.” Gero
pointed out that routine designs can be viewed as design prototype-instance
refinement. Design prototypes are retrieved and selected, and instances are
produced and refined. Under the broad definition of a design prototype, we also
believe that the whole design process can be viewed as a procedure of building
a series of prototypes, trying to solve a series of design sub-problems
generated dynamically throughout the design process. A design may start with
customers’ needs, an abstract description of what the product is expected to
do. Then the design process is an evolutionary process that transfers from one
prototype to another, gradually obtaining more detailed and more concrete
descriptions of the product. The design process continues until a design
solution, i.e., a real product, is obtained.
A project on
redesigning the shell of an industrial safety helmet to improve its thermal
properties is described here to illustrate this concept. At the beginning of
this design project, the first question was, “what are the factors that affect
the thermal properties of an industrial safety helmet?” For convenience, this
question is denoted ‘Q1’ in
To answer this
question, a two-dimensional heat transfer model simulating a worker wearing a
hemisphere shell in a 30.0℃ sunny day, with wind blowing at 2.5 m/sec was built. Again for convenience,
this computer simulation prototype is denoted ‘P1.’ From this prototype, we
learned that radiant heat is the major heat source when wearing a helmet.
Convection is the primary way to dissipate heat from beneath the helmet shell.
Body heat only has a marginal effect on the temperature beneath the helmet
While trying to
identify these factors, more questions were raised: “how do we redesign the
helmet shell to improve its thermal properties? (Q2)” “how do other helmets do on these
was established to simulate the conditions of a head wearing a helmet (P2). The
average temperatures beneath the helmet shell, the speed of heat dissipation
through convection, and the temperature contour beneath the helmet shell, were
used to describe the thermal properties of a helmet. Helmets of different types
and makes were tested, various design concepts were examined, and some design
suggestions for improving thermal properties of industrial safety helmets were
made. According to these design suggestions, a new helmet design concept that
should provide better ventilation and better insulation against solar radiation
was generated, in the form of a concept drawing as shown in Figure 2, another
Figure 2. The concept drawing of a new helmet
shell design. The arrows indicate airflow.
Very soon many
questions were raised when this concept drawing is presented: “Can we make it
look better without hurting its thermal properties? (Q4)” “Will there be stress
concentration around the ventilation holes? (Q5)” “Is it manufacturable? (Q6)”
“Will it pass the standard impact and penetration test? (Q7)” “How do you prove
that the new design have better thermal properties? (Q8)” “Will water leak into
the helmet through the ventilation holes if it rains? (Q9)”
questions formed more sub-problems for the design. Prototypes were built to
answer or evaluate these design sub-problems. Prototypes built with paper (P4)
and clay (P5) were used to give a three dimensional feel of the appearance of
the helmet. The shape of the helmet shell was further rounded. Different colors
and coating were tried on the prototype to give it a better look.
To answer the
sub-problem about the mechanical properties of the helmet, a finite element
model of the helmet shell was built (P6). Stress analysis showed that with a
static load on top of the helmet shell, there was stress concentration around
the ventilation holes. Reinforcement wall was added around the ventilation
holes to cope with this problem. On the manufacturablity of the new helmet
shell design, another computer simulation prototype using plastic mold flow
analysis software was built (P7) to evaluate how a plastic injection molding
can be built at a moderate cost.
To answer the
rest of the design sub-problems, physical prototypes had to be built. Several
helmets were made by vacuum molding (P8). These helmets were used in the impact
and penetration test, the thermal experiment, and the watering test. Cracks
were found on the helmet shell during the impact test, and a new sub-problem
occurred: “how to redirect the impact energy? (Q10)” Further observation of the
path of the cracks showed that the impact energy flow was blocked by the
ventilation holes. Ridges were added on the helmet shell accordingly, and new
helmets were made by vacuum molding again (P9). This time the new design passed
the impact test.
was raised during this modification process, “how to modify the shape of the
shell to further improve convection? (Q11)” A special helmet prototype made of
semi transparent plastomer (P10), with small stripes of paper attached
throughout the inside of the shell, was used to provide detail information on
how well the air flows under the shell. Finally a final engineering drawing
(P11) with all the detailed dimensions was presented to the manufacturer.
In spite of all
the test data, the manufacturer still wished to know “do the workers really
feel better wearing this helmet? (Q12)” To answer this sub-problem, a-prototypes
(P12) were built and a human description test, in which testers compared the
new helmet with other helmets, was performed. After this sub-problem was
confirmed, the manufacturer built the b-prototypes (P13) to answer the next
sub-problem “how this helmet can be built using the current facilities of the
manufacturer? (Q13)” And finally, the product (P14) was produced.
In this design
project, a total of 13 design sub-problems were raised, and a total of 14
prototypes (including the final product) were built. The design process of the
helmet can be viewed as a mapping of a series of design sub-problems to a
sequence of prototyping process, as shown in Figure 3. Actually a lot more
questions were asked during the design process, such as, the mechanical
properties of plastic materials, how to measure the impact loads, where to buy
certain components, etc. Many questions can be answered directly by designers’
knowledge, their previous design experience, or by information searching, and
are not listed as design sub-problems.
Figure 3. Mapping of a series of design
sub-problems to a sequence of prototyping process.
example we can observe that design sub-problems occurs dynamically during the
design process. Some of the sub-problems are expected in the structured design
models, but many sub-problems are not. They occur only under the special
situation the design team encounters, because a specific design concept is
presented, or certain information is obtained.
Note that the ‘prototypes’
here are not solutions to the design sub-problems. They are the representations
of certain elements of the product, the means or design tools designers use
trying to solve the design sub-problems. The ‘generation-evaluation-modification’
feedback loops exist within each design sub-problem and between design
sub-problems. To effectively and efficiently solve a design sub-problem, designers
must consider the characteristics of the current sub-problem to decide what
representations or design tools to use in order to solve this problem. Designers’
capability of using the design tools has to be considered also. Therefore, mappings
from design sub-problems to proper product states are important design
decisions. As mentioned earlier, most design process models try to provide a
structured pattern of designers’ activities. Instead of describing the design
activities, we can turn to the other side to describe the states of the product
evolving through the design process, and discuss how these decisions are made.
in the previous section, the design process can be viewed as a sequence of
prototyping process. A design prototype represents a ‘state’ of the product.
Formally, a ‘product state’ is a representation of the product that designers
use to generate information to answer or evaluate the current design
Figure 4 shows a
three-dimensional product state space. This figure is adapted from the
two-dimensional space in Figure 1, which is used to describe the
characteristics of prototypes. The first axis is still ‘comprehensive versus
focused.’ The second axis is changed from ‘physical versus analytical’ to
‘physical versus virtual,’ because the word ‘analytical’ has some flavor of
Figure 4. The three-dimensional product state
dimension added is ‘qualitative versus quantitative.’ This is an auxiliary axis
since a product state can be simultaneously quantitative and qualitative. A
representation of the product that can provide quantitative information may
also be used for qualitative evaluation. But a design sub-problem can be
strictly a quantitative problem or qualitative one. With this auxiliary axis,
it would help the designer to consider the characteristic of a design
sub-problem, and decide what design tools or representation to use in order to
answer this design sub-problem.
A point in this
three-dimensional space is a product state. To put a product state into the
three-dimensional product state space, designers should consider (a) Is this a physical
or virtual representation of the product? (b) Does it implement most attributes
or just a few attributes of the product? (c) Does it generate quantitative or
qualitative information (or both) about the product?
several extreme points in this product state space. The initial state may be a
list of needs of the customers, or a mission statement from upper management.
It is usually an abstract description of what the product is expected to do.
The customers’ needs or the mission statement are usually the most virtual, and
the most comprehensive representation of the product (while it may contain both
qualitative and quantitative descriptions of the product). So it represents the
extreme of the product state space in the fourth quadrant of the horizontal
plane in Figure 4. On the other hand, the final product is the most physical,
and the most comprehensive representation of the product. So it represents an
extreme of the product state space in the first quadrant. Note that the final
product appears in both the upper and lower half of the product state space
because the final product can generate the most detailed quantitative
information, while it can also provide all the qualitative feel. So the final
product also represents the upper and lower extremes on the qualitative versus
A product state
is usually represented by a design prototype. All prototypes used in the helmet
design project described in the previous section are product states of this
design, and are plotted in the product state space as shown in Figure 5. Note
that product state ‘P0’ is
the mission statement of the design project. The position of a product state on
a given axis represents the level of the state on that axis. For example, P5 (a
clay helmet prototype) is ‘more physical’ than P4 (a paper helmet prototype).
Therefore the position of P5 is higher than that of P4 on the vertical axis.
However, the distance between these two product states may not have exact
quantitative meaning. Similarly, P1 (a 2-D heat transfer simulation model), P6
(a finite element stress analysis model), and P7 (a mold flow analysis model)
are all computer simulation models for a single attribute of the product. Thus
the three product states occupy the same position on the focused & virtual
plane. The 2-D heat transfer model only gives a trend of the effect of various
heat sources, while the finite element gives rather precise quantitative stress
analysis results. Thus they have different positions on the quantitative vs.
qualitative axis. Finally, P12 (a prototype), P13 (b prototype) and P14 (the
final product) appear in both upper and lower half of the product state space
because they can generate both quantitative and qualitative information.
Figure 5. Design prototypes of the helmet design
Figure 3, the ‘design path’ is also plotted in Figure 6 to connect the product
states. The design path provides a clear picture of how the design problem is
solved. In the helmet design problem, the design path started from the extreme
point P0 in the fourth quadrant
of the horizontal plane (Figure 6(a)), then moved left and diverged into
several focused product states in order to solve the more focused design
sub-problems (Figure 6(b)). Towards the end of the project, the path converged
again, moved up and right toward the first quadrant for more physical and more
comprehensive product states (Figure 6(c)). Finally the path ended at the other
extreme point P14, the final product. From this figure, the design process can
be viewed as dynamically moving around the product state space.
(a) In the beginning, the
design path moves left and diverges.
(b) The design path gradually converges.
(c) The design path ends at the final product.
Figure 6. Design path shown in top view of the
design state space.
Note that many
product states along this design path are not planned beforehand. For example,
the output of each phase of a typical design process model can be plotted in
the product state space, as shown in Figure 7. In the beginning of the helmet
design project, only the mission statement (P0), the design concept (P3), the
final engineering drawing (P11), and the a-prototype, b-prototype, and
the final product (P12, P13, P14) were planned. There was a given schedule for
these product states. The rest of the product states were generated dynamically
to answer the design sub-problems occur during the design process. A CPM
(Critical Path Method) type of method can also be introduced for project
Figure 7. The output of each phase of a typical
design process model, shown in top view of the design state space.
Mapping from Sub-problems to Product States
process is now viewed as a mapping of a series of design sub-problems to the
product state space. This mapping actually represents important design
decisions during the design process. Designers must consider the
characteristics of the current sub-problem to decide what design tools or what
kind of representation to use in order to solve this problem. Note that the
sub-problems and the product states may not be a one-to-one mapping.
literatures on prototyping or rapid prototyping techniques, many researchers
report the factors to consider when selecting a prototyping tool (Wall et al.,
1992; Barkan and Lansitif, 1993; Ashley, 1995; Lange and Bhavnani, 1995;
Sorovetz, 1995). In summary, levels of approximation to the final product
(appearance, mechanical properties, accuracy) and design flexibility (time,
cost) are the factors frequently mentioned. Similar factors should be
considered when mapping a design sub-problem to a product state.
A product state
is used to generate information about the design sub-problem. To decide its
level of approximation to the final product, the designer should consider what
is the information required to answer the current design sub-problem. The
following questions should be asked when selecting a product state:
l What is the information required? Is it about certain attributes of
the product, or is it about the whole product? How much detail do I need?
l What is the type of information required? Is it qualitative
information or quantitative information? How accurate do I need?
l How is the product state used to generate the information? Is it
through physical experiments or virtual simulation? How close in forms to the
final product do I need?
three questions directly relate to the three axes of the product state space.
After considering these questions, the designer should be able to locate
regions in the product state space to which they can map the current design
sub-problem, as shown by the gray regions in Figure 8. Note that for a design
sub-problem, several regions may be identified. Further decision has to be made
on selecting one or several design tools to build proper product states,
considering the design flexibility required.
Figure 8. Possible regions in the product state
space to map the current design sub-problem.
design sub-problems, especially in the early stage of design, various design
concepts have to be evaluated, some of the design concepts will be discarded,
and it is possible that the design will have major changes. For this type of
design sub-problems, we should consider product states that have great design
flexibility, that is, the cost and time required for generating and modifying
the product state is low.
flexibility of a product state depends on the nature of the design tools used
to construct the product state. It also depends on the availability of the
design tool and capability of the design team. For example, in general a
product state represented by computer simulation model has better design
flexibility than a physical one. However, if the simulation software is not
available to the design team, or the design team is not capable of using the
software, the cost and time required to construct such a product state will be
In Figure 9, all
design tools available to the helmet design team are plotted in the product
state space according to their characteristics. This figure can be called a
‘design tool space.’ Note that here ‘design tools’ can be hardware or software
that can help designers in designing. ‘Design tools’ can also mean designers’
capability to perform certain theoretical analysis or experiments. The design
flexibility is also ranked in a 1~5 scale for each design tool according to the
capability of the design team. The design tool space is specific to a design
team. It can be updated whenever a new design tool is available to the design
team, or the capability of using certain design tools improves. The design team
can then compare Figure 8 with their own design tool space (such as Figure 9),
and choose the most proper design tools to construct the product state,
considering the characteristics of the design tools and the design flexibility
Heat transfer analysis software
Finite element analysis software
Mold flow analysis software
Final engineering drawing
Figure 9. The design tool space
The Procedure of Using the Model
10 is a flow chart of using this design process model. To initialize the model,
the design team is presented with a design problem. The design team makes an
initial design plan for all necessary product states and their schedule of the check
points of the design project. These product states are plotted in the product
state space, considering their required characteristics. The design tool space
for the design team is also ready. As shown in Figure 10, a design sub-problem
occurs as the design team explores the initial design problem. The design team
then considers the level of approximation required to answer the design
sub-problem, and maps the design sub-problem to several possible regions in the
product state space.
Figure 10. Flow chart of the new design process
In the third
step, the design team selects a proper design tool that has the required
characteristics and design flexibility from the design tool space. Using this
design tool, the design team constructs a product state and generates
information using this product state, till the current design sub-problem is solved.
Then the designers go to the next design sub-problem. This procedure iterates
until all design sub-problems are solved.
In this design
process model, designers focus on two things: to explore the design problem and
raise new design sub-problems, and to construct product states in order to
solve these design problems. There are also two major types of design decisions
in this model: to decide what design tools to use to construct proper product
states, and to decide on the design sub-problems using information generated by
the product states. After the design project is finished, design experience can
be recorded in the form of the sequence of design sub-problems and product
states evolving through the design process. This sequence represents the
thinking logic to the design team. The design team can also update their design
tool space as their capability improves, or they should try to learn new design
tools if they realize necessary.
Design is a
dynamic problem solving process. The logic flow of the design process should be
dominated by the design problem itself, not by a given pattern of design tasks.
This paper presents a new design process model based on product states. This
new model describes the ‘states’ of the product evolving during the design
process, instead of describing the design tasks. The design process is viewed
as dynamically moving around the ‘product state space.’ Using this model,
designers are encouraged to focus more on “what sub-problem to solve,” “ what
tool to use,” instead of “what activity should I do next?”
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