Design Principles: The Foundation of Design

Abstract

Design principles are created to codify and formalize design knowledge so that innovative, archival practices may be communicated and used to advance design science and solve future design problems, especially the pinnacle, wicked, and grand-challenge problems that face the world and cross-cutting markets. Principles are part of a family of knowledge explication, which also include guidelines, heuristics, rules of thumb, and strategic constructs. Definitions including a range of explications are explored from a number of seminal papers. Based on this analysis, the authors pose formalized definitions for the three most prevalent terms in the literature – principles, guidelines, and heuristics. Current research methods and practices with design principles are categorized and characterized. In analyzing the methodology for discovering, deriving, formulating and validating design principles, the goal is to understand and advance the theoretical basis of design, the foundations of new tools and techniques, and the complex systems of the future. Suggestions for the future of design principles research methodology for added rigor and repeatability are proposed.

Full text

DESIGN PRINCIPLES: THE FOUNDATION OF DESIGN
Katherine K. Fu
Georgia Institute of Technology
Atlanta, GA, USA
Maria C. Yang
Massachusetts Institute of
Technology
Cambridge, MA, USA
Kristin L. Wood
Singapore University of
Technology and Design
Singapore, Republic of
Singapore
ABSTRACT
Design principles are created to codify and formalize design
knowledge so that innovative, archival practices may be
communicated and used to advance design science and solve future
design problems, especially the pinnacle, wicked, and grand-challenge
problems that face the world and cross-cutting markets. Principles are
part of a family of knowledge explication, which also include
guidelines, heuristics, rules of thumb, and strategic constructs.
Definitions including a range of explications are explored from a
number of seminal papers. Based on this analysis, the authors pose
formalized definitions for the three most prevalent terms in the
literature – principles, guidelines, and heuristics. Current research
methods and practices with design principles are categorized and
characterized. In analyzing the methodology for discovering, deriving,
formulating and validating design principles, the goal is to understand
and advance the theoretical basis of design, the foundations of new
tools and techniques, and the complex systems of the
future. Suggestions for the future of design principles research
methodology for added rigor and repeatability are proposed.
1 INTRODUCTION
A number of technical research fields have grown and matured over
decades through the investigation, study, experimentation, and
validation of core principles. Accepted research methodologies and
standards similarly emerge and mature, founded on the scientific
method, but also tailored to the characteristics and scope of the field.
The life sciences and physical sciences are classical examples of this
growth and maturation process. Numerous cases are prevalent in these
fields, such as the theories and laws from classical mechanics to
explain the motion of particles, bodies, and systems of bodies.
Design research, or design science, is a relatively young field of
research investigation. With the first treatises published around the
mid-twentieth century, design science has grown steadily in the
devoted attention and depth of investigation. From the very earliest
discourse related to this field, such as Glegg’s “The design of design,”
principles of design have been postulated [4]. Because of the broad
and interdisciplinary or trans-disciplinary nature of design science,
numerous forms of design principles have been suggested across
disciplines, between disciplines, and at various levels of granularity or
specificity. The time is now apparent to carefully study these efforts,
seeking a formalization of design principles, definitions, and
supporting research methodologies.
In this paper, we seek to make strides in formalizing design principles
in terms of the various disparate theoretical, empirical, and
experimental approaches. This research will assist in enabling a
fundamental understanding and development of design principles, and
associated processes, as well as guiding researchers and practitioners
in advancements and use of such principles. Ultimately, the research
provides foundations to design science.
2 BACKGROUND
The formalization of design research methodology is the indisputable
path to the maturation of the field. Pahl and Beitz, some of the first to
propose formalized design processes and research [1]. Blessing and
Chakrabarti formulated a DRM (Design Research Methodology)
process comprised of 4 main steps: (1) Research Clarification, or
literature review to formulate a worthwhile research goal, (2)
Descriptive Study I, or empirical data analysis in an exploratory study,
(3) Prescriptive Study, or assumption experience synthesis into a
vision of how to improve upon on the existing situation, and (4)
Descriptive Study II, or empirical data analysis of the effect of the
improvement support developed [2]. Finger and Dixon extensively
reviewed design research methods, including descriptive models of
design processes, prescriptive models for design, computer-based
models of design processes, languages, representations, and
environments for design, analysis to support design decisions, design
for manufacturing and other life cycle issues such as reliability,
serviceability, etc. [3, 4]. Many of the research efforts reviewed in this
paper fall into one of these categories, whether through descriptive
models like case studies, protocol studies, and observations, or
prescriptive models of how the design process ought to be carried out
[4]. Inductive vs. deductive research methodologies are a particular
focus in this paper, where inductive research is based upon a process
in which data is collected first, patterns are extracted, and a theory is
developed to explain those patterns, while deductive research is based
upon a process in which a theory is developed first, after which data is
collected and analyzed to determine if the theory is supported. Though
not perfectly aligned in meaning, descriptive research and inductive
research methods are similar in that they both rely on discovery of
patterns and findings in data, while prescriptive research and deductive
research methods are similar in that they pose a theoretical solution or
answer, and test if it is effective or supported. The methodologies
reviewed in this paper tend to fit into one of these two categories,
though some are both. In reviewing the current research efforts to
Proceedings of the ASME 2015 International Design Engineering Technical Conferences &
Computers and Information in Engineering Conference
IDETC/CIE 2015
August 2-5, 2015, Boston, Massachusetts, USA
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extract design principles, effective techniques and areas for
improvement and development of greater rigor can be identified
toward a more formalized design principles research methodology.
3 RESEARCH METHODOLOGY
This paper is both a literature review and original critical analysis of
the state-of-the-art with the goal of advancing and formalizing the field
of design principles research. To gain an understanding of the types
and prevalence of each type of methodologies for exploring, deriving
and validating design principles, the authors reviewed 66 sources,
including monographs, books, anthologies, journal publications, and
conference publications. References were chosen based on either their
seminal nature to the foundation of the field (noted by their longevity
and/or high citation rate) or their publication in leading design
engineering journals or conference proceedings. Figures 1, 2, and 3
show the proportional breakdown of types of references, the field that
the references come from, and the distribution of references by year of
publication.
As each reference was reviewed, the authors tabulated the following
information from each source where applicable: keywords/key topics,
main contribution/brief synopsis, methods to find principles, methods
to validate principles, principles discovered, and any articulated formal
nomenclature definitions. This tabulation was analyzed in several
different ways, as reviewed in the following sections.
4 DISCUSSION OF NOMENCLATURE
In the pursuit of standardization, formalization and added rigor to any
scientific methodological undertaking, the articulation of clear and
well-reasoned definitions for key concepts is imperative. Formal
definitions ensure a common understanding and universal language,
not only between the authors and reader, but hopefully spreading
throughout the research community over time. In the following Sub-
Sections (4.1-4.5), the authors present articulated formal definitions of
design principles from the literature reviewed. A formal definition for
each term is then posed based on an amalgamation and aggregate
assessment of the literature findings and the expertise of the authors.
These definitions are within the context of the design research field,
and, therefore have an implied “design” before each term reviewed
(i.e. design principle).
4.1 Principle
Design principles are the focus of this research, though the
methodologies surrounding their conceptual kin (i.e. heuristics, etc.)
can be and often are similar, relevant, and applicable to those for
design principles. Several definitions and characteristics have been
gathered and juxtaposed below in their original form. Researchers use
a large variety of terms when defining “principle,” including:
technique, methodology, data, experience, example, recommendation,
suggestion, assertion, and proposition. Factors considered when
classifying and describing principles include: level of detail in which
they impact the design, point of application in the design process, level
of abstraction, specificity or granularity of the principle itself, the
manner in which principle is applied, the level of refinement or
success of the principle, among others. As expected, terms like
“guideline” are used to define principles, and are often used
interchangeably in informal settings. To summarize the literature
review in Table 1, the common threads that can be observed
throughout most of the definitions are:
• Principles are not universally applicable, effective, or true but
instead are generally applicable, effective, and true in a given
context.
• Principles are typically based on experiences, examples, or
empirical evidence.
• The application of principles may be context and/or problem
dependent, but should be more generalizable than a few isolated
instances
• Principles are used as foundations for understanding and for the
development of supporting methods, techniques, and tools.
Based on the literature review and analysis of the definitions, the
following is a proposed formalized definition for principle.
Proposed Formal Definition:
Principle: A fundamental rule or law, derived inductively from
extensive experience and/or empirical evidence, which provides
design process guidance to increase the chance of reaching a
successful solution.
Source
Definition/Characteristics
[5] Merriam-Webster
Dictionary
“A moral rule or belief that helps you know what is right and wrong and that influences your actions; a basic truth or theory: an
idea that forms the basis of something; a law or fact of nature that explains how something works or why something happens”
[6] Moe et al., 2004
[7] Weaver et al., 2008
[8] Singh et al., 2009
“A (transformation) principle is a generalized directive to bring about a certain type of mechanical transformation. A
(transformation) principle is a guideline that, when embodied, singly creates a transformation.”
[9] Glegg, 1969
“Principles of engineering design can be divided into three distinct types:
1. Specialized techniques: particular data and manufacturing techniques that have been amassed over a long period of
time with respect to a very specific technology that you cannot hope to design that product without - i.e. camshaft for a
TABLE 1. LITERATURE REVIEW OF DEFINITIONS AND CHARACTERISTICS FOR “PRINCIPLE”
Books%
Journal%
Papers%
Conference
Papers
Reference%
Texts%
FIGURE 1.
PROPORTION OF
REFERENCE TYPES
0
10
20
30
40
50
60
70
Number of References
FIGURE 2. FIELD OF
REFERENCES
0
1
2
3
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5
6
7
1969
1972
1973
1980
1981
1984
1985
1988
1989
1990
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2014
2015
Number of References
Year of Publication
FIGURE 3. REFERENCE YEAR OF PUBLICATION
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petrol engine.
2. General rules: broader theoretical considerations which are not confined to a single engineering mechanism - wide
though their scope may be, they are not of universal application.
3. Universal principles: underlying laws which cross the frontiers of most engineering design. They are the rules behind
the rules; they are not tied to any particular type of design, they concern the design of design.”
[10] Bell et al., 2004
Design principles are “…an intermediate step between scientific findings, which must be generalized and replicable, and local
experiences or examples that come up in practice. Because of the need to interpret design principles, they are not as readily
falsifiable as scientific laws. The principles are generated inductively from prior examples of success and are subject to
refinement over time as others try to adapt them to their own experiences. In this sense, they are falsifiable; if they do not yield
purchase in the design process, they will be debated, altered, and eventually dropped.”
[11] Kali, 2008
“Specific Principles describe the rationale behind the design of a single feature or single research investigation. Due to their
direct relation to one feature, specific principles in the database are embedded within the features.
Pragmatic Principles connect several Specific Principles (or several features), …
Meta-Principles capture abstract ideas represented in a cluster of Pragmatic Principles.”
[12] Anastas and
Zimmerman, 2003
“The principles are not simply a listing of goals, but rather a set of methodologies to accomplish the goals…The breadth of the
principles’ applicability is important. When dealing with design architecture, …the same…principles must be applicable,
effective, and appropriate. Otherwise, these would not be principles but simply a list of useful techniques that have been
successfully demonstrated under specific conditions. Just as every parameter in a system cannot be optimized at any one time,
especially when they are interdependent, the same is true of these principles. There are cases of synergy in which the successful
application of one principle advances one or more of the others.”
[13] Mattson and Wood,
2014
“A principle…[is] a fundamental proposition used to guide the design process. The principles in this paper are not suggestions
or activities the designer should complete, they are assertions that can guide the designer to a more effective outcome. The
principles do not explicitly say what should be done; they simply guide the engineer as decisions are made...Although
principles are not guaranteed, and at times they should not be followed, they should always be considered”
[14] McAdams, 2003
A design principle is “‘a recommendation or suggestion for a course of action to help solve a design issue’. This definition is
adapted from the definition for a design guideline according to Nowack (1997). Off-line principles are applied at the design
stage. On-line principles are applied anytime after this stage, including manufacturing and during use. Another characteristic
that distinguishes between the principles is the level of detail that they change the design.”
[15] Perez et al., 2011
“A set of principles can make this process more efficient as well as improve on the design of the original product. The
principles provide a means of processing the information gathered in the reverse engineering step in order to derive ideas
based on specific details encompassed by the example products.”
[16] Sobek et al., 1999
“…Principles…are not steps, prescriptions, or recipes. Rather, (Toyota chief) engineers apply the principles to each design
project differently. Design engineers use the principles to develop and evaluate a design process. The key to success is the
implementation of ideas as much as the principles themselves.”
[17] Altshuller, 1994
“Technical evolution has its own characteristics and laws. This is why different inventors in different countries, working on the
same technical problems independently, come up with the same answer. This means that certain regularities exist. If we can
find these regularities, then we can use them to solve technical problems – by rules, with formulae, without wasting time on
sorting out variants.” – in describing the 40 inventive principles of TRIZ
[1] Pahl and Beitz, 1988
“Only the combination of the physical effect with the geometric and material characteristics (working surfaces, working motions
and materials) allows the principle of the solution to emerge. This interrelationship is called the working principle …and it is the
first concrete step in the implementation of the solution.”
4.2 Guideline
As discovered in the literature addressing the definitions and
characteristics of principles, we find similar content for that of
guidelines. Key terms found throughout the literature quoted in Table
2 include: prescriptive, imperative, advice, instruction, opinion,
recommendation, assistance, prediction, and general. Descriptions
address factors such as when to use guidelines during the design
process, how they must be changed and revised, and how they must be
presented and described to their user. There are two key differences
that stand out between the definitions of principles and guidelines:
• Guidelines seem to be presented as more context dependent and
changeable than principles – perhaps even less “universal” or
“fundamental.”
• The literature on guidelines places strong emphasis on their
modality, organization, and level of detail of presentation for
maximum effectiveness and usability, though this could be an
artifact of the choice of references.
• Guidelines are described as more prescriptive than heuristics,
presented in the next section, which tend to be descriptive or
prescriptive.
Based on the literature review and analysis of the definitions, the
following is a proposed formalized definition for guideline.
Proposed Formal Definition:
Guideline: A context-dependent directive, based on extensive
experience and/or empirical evidence, which provides design
process direction to increase the chance of reaching a
successful solution.
Source
Definition/Characteristics
[18] Merriam-Webster
Dictionary
“A rule or instruction that shows or tells how something should be done”
[19] Greer et al., 2002.
“Design guidelines provide a means to store and reuse design knowledge with the potential to be effective in the early stages
TABLE 2. LITERAT URE REVIEW OF DEFINITIONS FOR “GUIDELINE”
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of design where…broad knowledge is beneficial. The format used to present the product evolution design guidelines is the
imperative form from English grammar…According to Nowack, a design guideline has at least four parts: issue(s) addressed
or impacted, links to design context, action recommendations, and rationale [20].”
[20] Nowack 1997
A design guideline is “a prescriptive recommendation for a context sensitive course of action to address a design issue.”
[21] Kim, 2010
“…Design guidelines can…be considered as an intermediary interface between the designer and …[expert] knowledge. The
purpose of design guidelines is to enable designers to make usable and consistent applications that conform to designated
conventions. To maximize the compliance of the resulting products, it is important to produce design guidelines that designers
can actually understand and apply [22]. Design guidelines address a wide range of design levels; the contents are typically
based on laboratory experiments and experts’ opinions. These guidelines are being continuously revised and updated to
meet technical and environmental changes.”
[23] Bevan and
Spinhof, 2007
“A good set of guidelines is composed of a combination of more specific guidelines for the application at hand and more
generic guidelines that refer to more general aspects...”
“And the set of guidelines should be well documented, including good or bad examples, a thorough table of contents and
glossaries [21].”
[24] Jänsch and
Birkhofer, 2006
“The generality inherent in all guidelines has been greatly increased… direction of the guidelines has changed from a personal
support for individuals…towards a general procedure for a company addressing organization and content….advice within the
guidelines [has] changed from addressing concrete thinking processes to general problem solving advice…instructions have
changed from statements that can be immediately put into action or thought to instruction on an abstract level, which need to
be adapted to the current situation of the designer… appearance of the descriptions of the guidelines have altered from a pure
one-page text-based description to comprehensive descriptions with figures, in particular flow charts and in-depth
texts….content of the descriptions has been enhanced with figures, examples and a quantity of text.”
[25] Matthews, 1998
“Guidelines can provide additional assistance by predicting likely outcomes of actions and by identifying additional issues
that should be considered. For guideline support to be effective, appropriate guidelines must be available to the designer at the
time of a design decision.”
4.3 Heuristic
The term heuristic has an understandably broader and richer base of
literature from which its definition can be derived, as it has both
connotations with computational applications as well as analogue
design process applications. Table 3 draws upon both sets of literature
in an attempt to generalize the definition among the fields of
application. Key terms used in describing and defining heuristics from
the sampled literature include: rule-of-thumb, guideline, common
sense, principle, experience, observation, knowledge, lesson, strategy,
simple, concise. Again, as in the previous two section defining
principle and guideline, we find the terms can be and often are used
interchangeably in the literature. Distinctions that emerge based on
the literature sampled that make heuristics unique include:
• Emphasis on reducing search time – not necessarily an optimal
result, but satisfactory, practical or “quick and dirty.”
• Ability to be prescriptive or descriptive, unlike guidelines, which
are mostly prescriptive.
• Value is typically defined by usefulness
• Heuristics are generally reliable, but potentially fallible depending
on context and circumstances.
• There may not be as extensive evidence or validation of heuristics,
compared to guidelines, and especially principles.
Based on the above literature review and analysis of these definitions,
the following is a proposed formalized definition for heuristic.
Proposed Formal Definition:
Heuristic: A context-dependent directive, based on intuition, tacit
knowledge, or experiential understanding, which provides design
process direction to increase the chance of reaching a
satisfactory but not necessarily optimal solution.
Source
Definition/Characteristics
[26] Merriam-Webster
Dictionary
“Using experience to learn and improve; involving or serving as an aid to learning, discovery, or problem-solving by
experimental and especially trial-and-error methods <heuristic techniques> <a heuristic assumption>; also: of or relating to
exploratory problem-solving techniques that utilize self-educating techniques (as the evaluation of feedback) to improve
performance <a heuristic computer program>”
[27] Stone and Wood,
2000
“(Module) heuristics: A method of examination in which the designer uses a set of steps, empirical in nature, yet proven
scientifically valid, to identify (modules) in a design problem. This definition requires another: the phrase ‘proven
scientifically valid’ refers to a hypothesis, formulated after systematic, objective data collection, that has successfully
passed its empirical tests. Thus, the heuristics are proven by following the scientific method.”
[28] Bolc and
Cytowshi, 1992
“Heuristics [are] explicit rules derived from human experiences and tacit knowledge.”
[29] Li et al., 1996
“Heuristics are rules-of-thumb that have been successful in producing ‘acceptable’, not necessarily ‘optimal’ solution to
a type of problem.”
[30] Chong et al., 2009
Heuristics “…are criteria, methods, or principles for deciding which among several alternative courses of action
promises to be the most effective in order to achieve the desired goals.”
[31] Nisbett and Ross,
1980
“Heuristics are reasoning processes that do not guarantee the best solution, but often lead to potential solutions by
providing a “short-cut” within cognitive processing.”
[32] Pearl, 1984
“The term ‘heuristic’ has commonly referred to strategies that make use of readily accessible information to guide
problem-solving.”
[33] Yilmaz and
Seifert, 2011
“The term ‘heuristic’ implies that it:
1) Does not guarantee reaching the best solution, or even a solution; and
TABLE 3. LITERA TURE R EVIEW OF DEFINITIONS FOR “HEURISTIC”
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2) Provides a ‘quick and dirty’ (easier) method that often leads to an acceptable solution.”
[34] Koen, 1985
“All engineering is heuristic.
“Synonyms of the heuristic: rule of thumb, intuition, technique, hint, aid, direction, rule of craft, engineering judgment,
working bias, random suggestions, le pif (the nose)
A heuristic is an “engineering strategy for causing desirable change in an unknown situation within the available
resources…anything that provides a plausible aid or direction in the solution of a problem but is in the final analysis
unjustified, incapable of justification, and fallible. It is used to guide, to discover, and to reveal.
“Signatures of the heuristic:
• A heuristic does not guarantee a solution
• It may contradict other heuristics
• It reduces the search time in solving a problem for a satisfactory solution
• The absolute value of a heuristic…is based on the pragmatic standard …[it] depends exclusively on its usefulness in
a specific context…a heuristic never dies. It just fades from use.
• One heuristic [replaces] another by…doing a better job in a given context.”
[35] Magee and Frey,
2006
“A heuristic is a generally reliable, but potentially fallible, simplification that enables a problem to be addressed within
resource constraints.”
[36] Clancey, 1985
“The heuristic classification model characterizes a form of knowledge and reasoning-patterns of familiar problem
situations and solutions, heuristically related. In capturing problem situations that tend to occur and solutions that tend to
work, this knowledge is essentially experiential, with an overall form that is problem-area independent.”
[37] Maier and
Rechtin, 2000
“The heuristics methodology is based on “common sense,” …comes from collective experience stated in as simple and
concise a manner as possible… Insight, or the ability to structure a complex situation in a way that greatly increases
understanding of it, is strongly guided by lessons learned from one’s own or others’ experiences and observations. But
they must be used with judgment.
“People typically use heuristics in three ways…[1] as evocative guides... evoke new thoughts…[2] as codifications of
experience…[3] as integrated into development processes.
“Two forms of heuristic[s]…[1] descriptive: it describes a situation but does not indicate directly what to do about it…[2]
prescriptive: it prescribes what might be done about the situation.
“Heuristics…are trusted, nonanalytic guidelines for treating complex, inherently unbounded, ill-structured problems….are
used as aids in decision making, value judgments, and assessments…provide the successive transitions from qualitative,
provisional needs to descriptive and prescriptive guidelines and, hence, to rational approaches and methods.
Heuristic evaluation criteria “…to eliminate unsubstantiated assertions, personal opinions, corporate dogma, anecdotal
speculation, mutually contradictory statements:
• … must make sense in its original domain or context…a strong correlation, if not a direct cause and effect, must be
apparent between the heuristic and the successes or failures of specific systems, products, or processes.
• The general sense…of the heuristic should apply beyond the original context.
• The heuristic should be easily rationalized in a few minutes or on less than a page.
• The opposite statement of the heuristic should be foolish, clearly not “common sense.”
• The heuristic’s lesson, though not necessarily its most recent formulation, should have stood the test of time and
earned a broad consensus.
• Humor (and careful choice of words) in a heuristic provide an emotional bite that enhances the mnemonic effect
• For maximum effect, try embedding both descriptive and prescriptive messages in a heuristic.
• Don’t make a heuristic so elegant that it only has meaning to its creator, thus losing general usefulness.
• Rather than adding a conditional statement to a heuristic, consider creating a separate but associated heuristic that
focuses on the insight of dealing with that conditional situation.
To synthesize the three previous Sections (4.1-4.3), the authors pose a
set of dimensions that form the definitions of heuristics, guidelines,
and principles:
• Supporting Evidence or Validation Dimension: the degree of
supporting evidence for the terms tends to be ordered as heuristics,
guidelines, and principles in increasing evidence.
• Granularity or Specificity: the degree of granularity or specificity
for the terms tends to be ordered as heuristics, guidelines, and
principles in increasing formalization.
• Formalization Dimension: the degree of formalization of the terms
tends to be ordered as heuristics, guidelines, and principles in
increasing formalization.
• Prescriptive-Descriptive Dimension: the nature of the terms tends to
be ordered as heuristics, guidelines, and principles, progressing
from more prescriptive to more descriptive.
4.4 Additional Nomenclature
A number of terms fall into the same family as principles, guidelines,
and heuristics, but are not used as prevalently in the literature. A few
of these terms are reviewed here as acknowledgment of their
importance, relationship, and distinction from the three terms defined
thus far.
4.4.1 Rule/Commandment Roozenburg and Eekels
discuss design rules as dichotomous in nature, either being algorithmic
or heuristic. Algorithmic design rules are “based on knowledge where
the relationship between cause and effect is known well, as in physical
laws, and they produce predictable and reliable results.” Heuristic
design rules are much less well defined, guaranteed, or proven. They
state that “any design rule that cannot be converted into an algorithm is
heuristic” [38]. In light of the discussion thus far, were there to be a
continuum rather than a dichotomy between algorithmic and heuristic
rules, it would be expected that principles might be placed closer to the
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algorithmic end, heuristics closer to the heuristic end (naturally), and
guidelines somewhere in between.
Only one instance of the term commandment was encountered in
the work of Hamstra [39], which presented a set of seven
commandments for exhibit and experience design. The research
describes commandments as “not written in stone…[as] creative work
cannot be done from a straightjacket of design principles…[they]
combine…beliefs about…goals and planning, …methods, and content
development, and are designed to spark discussion and
inspiration…and to clarify ambitions to clients” [39]. Interestingly,
the author portrays design principles as restrictive, more so than
commandments, despite the semantic connotation of the term.
Commandments as defined come across as most similar to guidelines,
in that they are prescriptive in nature, and based on beliefs rooted in
successful design experiences.
4.4.2 Facilitator Facilitator is a term found in a series of
related works that study the design of transformers [6-8]. As stated by
the authors, “a Transformation Facilitator is a design archetype that
helps or aids in creating mechanical transformation. Transformation
Facilitators aid in the design for transformation but their
implementation does not create transformation singly” [6-8]. This
term harkens to the recommendation of Maier and Rechtin [37] to
create associated heuristics one is tempted to add a conditional
statement – in that there are corollaries and associations among them
as well, in addition to being potentially descriptive rather than
prescriptive.
4.4.3 State of the Art (SOTA) Koen inextricably links
heuristics to the term state of the art [34], which he defines simply as a
SOTA, or “a group of heuristics.” He goes on to stipulate that “each
should be labeled…and…time stamp[ed], [as]…SOTA is a function of
time. It changes as new heuristics become useful and are added to it
and as old ones become obsolete and are deleted” [34]. As stated
earlier in the heuristic section, Koen sees all of engineering as
heuristic, so naturally state of the art practice is defined by those
heuristics.
4.4.4 Ontology Gruber provides a relevant and cogent
definition of ontology, stating that “a conceptualization is an abstract,
simplified view of the world that we wish to represent for some
purpose. Every knowledge base, knowledge-based system, or
knowledge-level agent is committed to some conceptualization,
explicitly or implicitly. An ontology is an explicit specification of a
conceptualization…When the knowledge of a domain is represented in
a declarative formalism, the set of objects that can be represented is
called the universe of discourse. This set of objects, and the
describable relationships among them, are reflected in the
representational vocabulary with which a knowledge-based program
represents knowledge” [40]. Ontology, as Gruber defines it, could be
conceived of as the umbrella under which all other terms discussed
here may sit.
4.4.5 Standard Standards, as defined by Cheng [41], are
“documented agreements containing technical specifications or other
precise criteria to be used consistently as rules, guidelines or
definitions of characteristics, to ensure that materials, products,
process and services are fit for their purpose.” This definition has a
mix of softer, more subjective words like “agreements” and
“guidelines” in combination with more definitive, strong terms like
“precise criteria”, “technical specifications”, and “ensure”. One
interpretation of these mixed subtexts is that standards are often put
into place through governmental regulations, relying upon agreement
of law makers and technical experts, and the expertise of the state of
the art practices, as translated (to the extent possible) into exact
numerical specifications – no small feet to achieve, let alone define.
4.4.6 Algorithm Suh conceived of Axiomatic Design,
from which the definition for algorithm and the following definition
for axiom are taken [42, 43]. Suh states that “in purely algorithmic
design, we try to identify or prescribe the design process, so in the end
the process will lead to a design embodiment that satisfies design
goals. Generally, the algorithmic approach is founded on the notion
that the best way of advancing the design field is to understand the
design process by following the best design practice” [42]. According
to Suh, most terms discussed thus far would fit within the category of
algorithmic design.
4.4.7 Axiom Suh goes on to define axioms as
“generalizable principles that govern the underlying behavior of the
system being investigated. The axiomatic approach is based on the
abstraction of good design decisions and processes. As stated earlier,
axioms are general principles or self-evident truths that cannot be
derived or proven to be true, but for which there are no
counterexamples or exceptions. Axioms generate new abstract
concepts, such as force, energy and entropy that are results of
Newton’s laws and thermodynamic laws” [42, 43]. While Suh uses
the term “principle” in the definition for axiom, the requirements for
the level of unshakeable truth and correctness of them makes axioms
the most stringent term discussed yet.
4.4.6 Strategy Merriam-Webster defines strategy as the
following:
“1: a careful plan or method for achieving a particular goal usually
over a long period of time
2: the skill of making or carrying out plans to achieve a goal” [44]
None of the sources reviewed here directly or explicitly defined
strategy, but rather used rule of thumb as a synonym for other terms,
such as principle or heuristic.
4.4.8 Rule of Thumb Merriam-Webster defines rule
of thumb as the following:
“1: a method of procedure based on experience and common sense
2: a general principle regarded as roughly correct but not intended to
be scientifically accurate” [45]
As with strategy, none of the sources reviewed here directly or
explicitly defined rule of thumb, but rather used rule of thumb as a
synonym for other terms, such as principle or heuristic.
5 DESIGN PRINCIPLES RESEARCH METHODS
To gauge the state of the art in research methodologies for design
principles and their kin, 66 publications were analyzed. From this
point forward in the paper, the term “principle” is used to refer to itself
and any of the other familial terms reviewed in the nomenclature
section, as the methods and sources for deriving and validating any of
the knowledge codification types reviewed previously is valuable to
this analysis. The research efforts analyzed in Section 5 include the
following references: [2, 6-9, 11-17, 19, 21, 22, 24, 25, 27, 30, 33-36,
39, 40, 46-88]. The topics addressed in the research efforts reviewed
include: transformational
design, biomimetic/bio-
inspired design, robotics,
software design, user interface
design, reconfigurable design,
green/environmental design,
TRIZ, biomechanical design,
universal design, among other
topics.
In Figure 4, the proportion of
research efforts in the
literature that used deductive
FIGURE 4. RESE ARCH
METHOD CLASSIFICATION
FOR ANALYZED LITERATURE
6
Copyright © 2015 by ASME

vs. inductive approaches
is shown, including those that used both approaches. The majority of
researchers used an inductive method, which will be discussed further
in the next two sections.
5.1 Review of Methodologies for Extraction/ Derivation/
Discovery of Design Principles
Each of the 66 references was examined to ascertain the methodology
used by the authors to derive, discover, extract, or codify design
principles. These were first tabulated as their specific detailed
methodologies, and then reduced to broader categories, including:
• Not Specified or Not Applicable: the authors did not state the
method by which the principles were derived
• Design Expert Observation: in situ observation of expert designers
at work expressly not a laboratory setting or study
• Derivation from Laboratory Base Design Practice: design study
based data was collected, from which principles were extracted
• Derivation from Design Practice: based on design performed by
the authors, from which principles are derived – can be less time
and experience than expert level, otherwise would fall into the next
category
• Experience: derived from the experience of an expert designer or
collection of expert designers, usually the author(s)
• Existing Principles: existing literature was used as the source of
principles, which were validated or tested using one of the means
discussed in Section 5.2
• Analysis of Existing Designs / Design Repositories/Empirical
Data Sets: consumer products, patents, nature, or even software are
analyzed
As shown in Figure 5, the most publications derived principles by
studying existing designs themselves, a methodology that has the
benefit of publicly accessible data sources and large accessible sample
sizes. The second most frequent methodology used principles derived
by others, a clear deductive approach to design principles research, in
which the theory is the starting point of the research confirmed by the
validation step. Design experts often write about their career’s worth
of experiences in a memoir-esque format, sharing their life long
lessons learned for designers to come. The least prevalent
methodologies are those that are highly energy and resource intensive
in terms of observation, data collection and data coding and analysis.
Very few of the papers did not specify or address where the principles
came from, or how they were derived.
Figure 6 shows the sources that researchers used from which to derive
principles. Many cited multiple sources, for example using both
consumer products and literature review. If the authors generated
principles from their own design activities, it was coded as “authors”,
rather than “design project/task.” This choice was made to illustrate
that many authors and researchers are writing about their own design
experiences, lessons, and accumulated knowledge, rather than deriving
it from an external source. The categories shown in Figure 4 are
described as the following:
• Design Project/task: designers/study subjects perform a design task
• Students: students serve as the subjects for a design study
• Not Specified/Not Applicable: the authors did not state the source
• Expert Designers from Industry: expert industrial designers were
observed, interviewed, or studied as the source
• Nature: natural phenomena, as in biologically inspired or
biomimetic design
Methods to find
Principles
Unit of Sample Size
Sample
Size
Analysis of Existing
Designs
Consumer products
10, 46, 23,
15, 10, 3
Consumer products, Patents
190, 90
Consumer products, Patents,
Nature
190, N/A
Examples
163
Nature
1
Patents
200,000,
41
Computer Programs
N/A
Reconfigurable systems
33
Analysis of Existing
Designs, Existing
Principles
Patents
90
Derivation from Design
Practice
Design project/task
2, 1, 1
Engineers
N/A
N/A (3)
N/A (3)
Derivation from
Laboratory Based Design
Practice
Design project/task
5
Designers
N/A (2),
20
Engineers
36
Students
300, 29
Teams
12
Design Expert Observation
Designs (sketches, early stage)
50
(Person) Years
0.5
N/A
N/A
Existing Principles
Literature
N/A (5),
442, 10, 3,
2
N/A (6)
N/A (6)
Existing Principles,
Experience
N/A (2)
N/A (2)
Experience
N/A (2)
N/A (2)
(Person) Years
30, 40, 40,
40, 40, 20,
1, N/A (2)
TABLE 4. SAMPLE SIZES USED IN
LITERATURE TO DERIVE PRINCIPLES
FIGURE 5. METH ODS USED IN LITERATURE TO DERIVE
DESIGN PRINCIPLES
0 5 10 15 20
Not Specified or Not Applicable
Design Expert Observation
Derivation from Laboratory
Derivation from Design Practice
Experience
Existing principles
Analysis of Existing Designs
Number of Papers
Methods to Find/Derive Principles
0 5 10 15 20
Design Project/task
Students
Not Specified or Not Applicable
Expert Industrial Designers
Nature
Designers
Authors
Patents
Engineers
Consumer products
Literature
Number of Papers
Sources of Principles
FIGURE 6. SOURCE S FROM WHIC H DESIGN
PRINCIPLES WERE EXTRACTED
7
Copyright © 2015 by ASME

• Designers: designers performed design tasks, neither novices nor
experts, nor engineers or roboticists – a middle category for design
study subjects
• Authors: the authors of the research publication served as the
source either through design activity or experiential knowledge
• Patents: patents were analyzed as the source
• Engineers: engineers were studied, observed, or interviewed as the
source
• Consumer products: consumer products were analyzed to extract
principles
• Literature: principles were taken as already articulated in pre-
existing literature
The sample sizes used for the derivation of the principles were also
tabulated, as shown in Table 4. If any information was not included,
N/A was marked. Numbers in parentheses denote the number of
papers that did not specify that particular information. The largest
sample sizes came from analysis based on student participant design
studies, patent/consumer product analyses, and individuals reporting
on their own person-years of experience.
5.2 Review of Methodologies for Validation of Design
Principles
Similar to the analysis in Section 5.1, the source literature was also
examined for the ways in which they validated the design principles
that were derived. Figure 7 shows that the majority of publications did
not address the validation of the principles, but rather focused on the
derivation of the principles, or more often the pure presentation of the
principles themselves without regard for methodology. The second
most prevalent validation methodology was a design project or task –
most often a case study of solving 1 to 3 design problems employing
the design principles. Interestingly, a niche in the publication set [8,
74, 80] is represented by those who validated principles through:
Convergence/Asymptotic Analysis: Examining a larger set of source
material (test data) until the quantity of principles converged to a
horizontal asymptote, i.e. asymptotic convergence. This numerical
technique shows promise for its computational robustness, but does
not address the validation of the utility of the principles.
As expected based on the number of publications that did not address
validation methodology, the source for validation was naturally not
addressed either for the majority of publications, as shown in Figure 8.
Most often, the authors or others performed small-scale
implementations of the design principles in practice as proof of
concept and initial validity at a case study level.
Sample sizes used for principle validation were also tabulated, as
they were for derivation. Table 5 shows the samples sizes and units of
those samples for each paper analyzed. Notice that nearly half (28) of
the papers did not report the method to validate principles nor the
source nor sample size. The largest sample sizes came from analyses
of consumer products, patent analyses, and customer review analyses.
Most papers went about validation with 1-3 design tasks implementing
the derived principles.
6 PROPOSED FUTURE DIRECTIONS FOR DESIGN
PRINCIPLES RESEARCH METHODOLOGY
The review of the design principles literature indicates some key
opportunities for future directions of design research methodology.
First, most research efforts focus on the presentation of principles
themselves, with very few offering any prescriptive application of
these principles into design practice for their validation. Author
experience should be combined with empirical derivation/discovery of
design principles so as to combine the benefits of longitudinal
expertise and reduction of bias in reporting on just one personal
perspective or experience. As is true of much of design science
research, more investment must be made into the study of expert
designers, regardless of energy/time/resource intensive requirements –
or alternatively, a solution to this problem should be developed. This
issue of sample size and access to expert or advanced level design
participants is being addressed innovatively through efforts like the
use of crowd-sourced design and other online platforms [89].
There is also an opportunity for more computational and
numerical validation of the principles, through techniques like
convergence analysis referenced earlier [8, 74, 80]. Alternative
computational validation might include other data mining techniques,
agent based modeling of design processes, modeling of human
cognition through Bayesian statistics or other philosophical
approaches, artificial intelligence models implementing methods like
neural networks, decision trees, and complex systems modeling. An
increased level of formalism in the articulation of principles, using
tools like logic operators, language structures, etc. is an additional way
to add rigor and repeatability to the research methodology.
As discussed earlier, there are dimensions of principles that
emerge from the various definitions that should be considered or even
explicitly stated, including level of supporting evidence or validation,
level of granularity or specificity, level of formalization, and position
Methods to Validate
Principles
Unit of Sample Size
Sample Size
Analysis of Existing Designs
Consumer Products
4, 17, 70, 645
Industrial Products
2
N/A (2)
N/A (2)
Convergence Analysis
Customer reviews
200
Patents
41, 50
Convergence Analysis,
design project/task
Design project/task
1
Design Expert Observation
Designs
218
Design Project/task
Design project/task
1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 2, 2,
3, 3, 3, 4, 4, 28
Students
6, 64, N/A
Team
1
Experience
N/A (4)
N/A (4)
N/A (28)
N/A (28)
N/A (28)
TABLE 5. SAMPLE SIZES USED IN LITERATURE
FOR PRINCIPLE VALIDATION
FIGURE 7. METHOD S USED IN LITERATURE TO V ALIDATE
DESIGN PRINCIPLES
0 10 20 30
Design Expert Observation
Experience
Convergence Analysis
Analysis of Existing
Design Project/task
Not Specified or Not
Number of Papers
Methods to Validate Principles
FIGURE 8. SOURCE S USED IN LITERATURE TO VALIDATE
DESIGN PRINCIPLES
0 10 20 30 40
Expert Industrial Designers
Consumer Reviews
Patents
Consumer products
Students
Designers
Examples/Case Studies/Design task
Authors
Not Specified or Not Applicable
Number of Papers
Sources of Validation
8
Copyright © 2015 by ASME

on the spectrum of prescriptive-descriptive. Other important aspects to
consider and include when articulating design principles are the time
stamp (to indicate a sense of where state-of-the-art, technological,
social and economic trends stand in relation to the principle), the
context in which the principle is usable/useful/relevant, the intended
users of the principle and any expected background or knowledge for
proper application, and any conditions or qualifiers for applicability.
7 CLOSURE
Design Science, or in general design research, has received increasing
attention of the last few decades. The future of products, services,
systems, software and architecture rely on advancing design, both in
terms of our foundation or formalized understanding and our
inspirations for practitioners. Design principles represent a key
component of description and characterization of design and
associated design processes.
In this paper, we study past contributions to the area of design
principles, developing a discourse and definitions for related
formalizations, and analyzing different research methodologies. Key
contributions of this work include working definitions for researchers
and practitioners to investigate, share, and utilize design principles.
These definitions may be used to share and describe design principles
across design communities, but also as part of disciplinary fields.
Building on these definitions, alternative research methodologies are
presented including the concepts of sources, sample size, and
approaches for validation. Researchers from disparate fields may
engage these methodologies to improve the rigor of their studies, as
well as consider the recommendations for even greater rigor and to
raise the research field. Future directions include further formalization
of methodologies for design principles research, and implementation
and validation of those methodologies with applications in the areas of
digital design for manufacturing and bio-inspired design.
ACKNOWLEDGMENTS
This work was funded by the SUTD-MIT International Design Centre
(IDC), http://idc.sutd.edu.sg.
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