Author: Euisuk Sung (Page 1 of 2)

What is Engineering Design Process? Why are there so many design process models?

The research trend on the engineering design process has changed depending on the perspective of engineering. In the middle of the 20th century, research on engineering design process conducted in terms of applied science. Since the 1980s, some researchers viewed engineering as a problem-solving process. In recent years, many researchers agreed that engineering design processes are complex and amorphous; as a result, some researchers adopted an ethnographic approach to describe details of the engineering design process within the specific engineering contexts. In order to understand the engineering design process, we will review the discussions and arguments in the development of design theories.

1        Engineering Design as Applied Science

In the 1950s and 1960s, U.S. engineering education was science-oriented in its approach (Bousbaci, 2008). Since the Second World War, a number of theory-oriented European engineers—nuclear engineers and space engineers, in particular—moved to the United States (Seely, 1999). The science-oriented engineering research of the time influenced the U.S. engineering education curriculum, which primarily focused on theory-based science learning (Grinter, 1955). Moreover, the U.S. military supported this trend by providing science-oriented research funding (Bix, 2002). This context coincided with an engineering perspective called applied science (Howell, 2002; Pahl & Beitz, 2013; Simon, 1975). Fletcher and Shoup (1978) viewed engineering as

“an applied science which deals with the planning, design, construction, testing, management or operation of facilities, machine, structures, and other devices used by all segments of society” (Flether & Shoup, 1978, p. 2).

The applied science approach attempted to define the design process based on logical, systematic, and rationalist views. Herbart Simon (1973) argued that a design problem can be defined as a well-defined problem. He stated that a well-defined problem has the following properties:

1. a definite criterion
2. at least one problem space
3. definable state changes, and
4. representable states.

According to this approach, all problems are solvable if the problem solver decomposes the problem. On the other hand, if a problem is not solvable, its proponents believed, it is because the problem solver were not able to define the problem. Design science theorists believed that design processes could also be illustrated via step-by-step models that divided design processes into distinct phases, including problem definition, analysis, ideation, and evaluation (Simon, 1973). One representative model of this approach is Hubka’s systematic design process model (1983). Hubka presented the design process in comparison with the technical process, which depicted the design process as a wire drawing. For example, a design project is a technical process where space and time variables apply. Once the design project is initiated, the effects of human actions and technical systems lead the design process, which in turn influences the project output. The model attempted to define the basic elements of the design process and identify a unified design process model applicable to a variety of design tasks.

A Design Model through Technical Process Model (Hubka, 1983, p. 9). The model can be accessed through https://www.daaam.info/Downloads/Pdfs/proceedings/proceedings_2014/074.pdf

However, the applied science approach has failed to represent the dynamic characteristics of design processes (Sheppard, Macatangay, Colby, & Sullivan, 2008). Rittel and Weber (1973) argued that design problems cannot be defined by definite rules and operations. He labeled this characteristic of design problems as wicked problems that lack definitive formulation, stopping roles, operations, and definitive solutions. Accordingly, Dorst (2004) argued that most design problems have the following three characteristics: 1) design problems are partly determined by explicit needs and constraints; 2) a major part of design problems is underdetermined; and 3) most parts of design problems can be considered undetermined. The applied science approach has contributed to the foundation of design process research, but is limited in its capacity to represent complex, intertwined design processes.

2        Engineering Design as Problem-Solving

An alternative approach to study the design process focused on problem-solving activities (Clarkson & Eckert, 2004; Cross, 2000; Lawson & Dorst, 2013). This approach emphasized engineers’ problem-solving activities: generating ideas, exploring the consequences, and evaluating the results. The underlying idea of this approach is that problem-solving plays as a fundamental operation in human activities. Similar to the applied science approach, this idea views the full design process as smaller sub-processes, such as conceptual design, prototyping, and product manufacturing (Ball, Evans, Dennis, & Ormerod, 1997). The problem-solving approach considers problem-solving as a sub-process of the design process. This approach led to the development of design process phase models that solved engineering problems step by step (Lawson & Dorst, 2013). The phase models allow engineers to easily generate a comparable solution by treating the engineering design task as problem-solving.

Many researchers have investigated how engineers generate the best solution via problem-solving approach. Lawson (1979) compared the problem-solving styles of architectural engineers and scientists and concluded that architectural engineers tended to use solution-oriented strategies, while scientists preferred to use problem-focused strategies. Lu (2015) studied the relationship between problem-solving types and design quality. Lu compared four problem-solving style types: problem-driven, information-driven, solution-driven, and knowledge-driven. Lu’s study concluded that the solution-driven strategies yielded more creative design outcomes than the other types. Dorst and Cross (2001) examined the design process in terms of creativity and confirmed that iterations between problem-space and solution-space are key to the generation of creative ideas.

Some critics have claimed that problem-solving process models do not explain all aspects of the design process. Bucciarelli (2003) argued that design process models depicted by shapes and arrows can only reflect a narrow view of the design process. Engineers often experience frustration when they try to solve a certain engineering problem according to a design process model because the model does not work as described.

3        Engineering Design as Ethnography

The multifaceted nature of engineering has led many researchers to adopt an ethnographical approach as a research methodology (Bucciarelli, 2003; Latour & Woolgar, 1986; Vinck, 2009). This ethnographical research method provides a realistic description of engineering tasks within the specific engineering contexts. Vinck (2009) used this approach to illustrate engineers’ day-to-day lives. Vinck visited engineers’ plants, design offices, and laboratories to observe what real engineers do. Using the ethnographical approach, Vinck presented the natural characteristics of engineering as: socio-technical complexity, negotiation and optimization, and comprehensive job practices (from designing to presenting the design solution). One advantage of this approach is that it does not simply claim that engineering is complex; it also identifies how the complexity occurred and was managed. The ethnographical approach can describe the engineering design process with realistic and authentic illustrations.

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These K-12 engineering and technology education design process models have similar structures and procedures (Katehi, Pearson, & Feder, 2009). The table below compared the design process models developed for K-12 engineering and technology education. Some models explicitly note that the design process can vary depending on the grade and the subject. Design processes for young students are oftentimes simpler with fewer steps than upper grades. For example, TeachEngineering explained that the fourth-grade’s Introduction to Engineering unit has a partial design process of six steps, while the 9^th to 12^th graders’ Creative Engineering Design unit consists of the eight steps of full design process model.

Table. A comparison of Design Process Models in K-12 Engineering and Technology Education Programs.

In practice, the instructional flows of K-12 engineering and technology lessons are closely aligned with their design process model. For instance, an EiE unit Engineering Go Fish: Engineering Prosthetic Tails (EiE, 2016) consists of six lessons, and each lesson is addressed by one or two engineering design stages. The TeachEngineering curriculum also features a similar unit flow. Each unit begins with a design problem, and the units proceed through the corresponding design cycle.

In terms of student learning, the design process models used in K-12 education have the similar structure to the instruction design models. Gagné’s Nine Events of Instruction articulated the specific teaching instructions of different classroom event stages (Gagne, Briggs, & Wager, 1992). The juxtaposition of Gagné’s Nine Events of Instruction in Figure 1 and 2 shows the models’ similar flows.

Gagné’s instruction model is rooted in the cognitive learning theory (Piaget, 1969) and the information processing theory (Driscoll, 2000). The information processing theory explains the mechanism of learning is similar to the process of information by saying that learning is a cognitive process of information handling between external stimulus and human memory storage. The information processing theory claims that human memory consists of two parts: short-term and long-term storage. This cognitive instruction model suggests that a learning activity involves several internal information processing stages. For example, per the instruction model, the third stage is stimulating recall of prior learning, which is a cognitive strategy to retrieve memory from long-term storage. The design process model in Figure 2 begins with clarifying the problem, which uses a set of cognitive strategies, including problem analysis, memory retrieval, association, and transformation. These cognitive elements produce the design operations of question, declare, suppose, or explain. These design operations help memory retrieval and storage by providing cognitive reinforcement. Once both models provide learners with the appropriate learning environment via cognitive attention, they guide learners to explore and practice their learning. After the learning or problem-solving is accomplished, the models lead learners to assess and their performance.

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Various engineering education programs have been developed for K-12 students, and most of the programs have adopted engineering design as the primary teaching and learning method. The Infinity Project (http://www.infinity-project.org) was started in 1999 by Southern Methodist University’s Lyle School of Engineering and Texas Instruments. The project partnered with the U.S. Department of Education, the National Science Foundation, and a team of university faculty, teachers, engineers, and researchers. The project targeted grades 6-12 and provides curriculum, instructional materials, and hands-on design projects (Brophy, Klein, Portsmore, & Rogers, 2008). The Infinity Project features a design process of eight steps: 1) Identify the problem, 2) Define the goals and identify the constraints, 3) Research and gather information, 4) Create a potential design solution, 5) Analyze the viability of the solution, 6) Choose the most appropriate solution, 7) Build and implement the design, and 8) Test and evaluate the design (The Infinity Project, n. d.)

TeachEngineering (teachingengineering.org) is a non-profit engineering program funded primarily by the NSF National Science Digital Library program. The project is aligned with Next Generation for Science Standards (NGSS), Standards for Technological Literacy (STL), and Common Core State Standards for Mathematics (CCSSM). The TeachEngineering project adopted an engineering design process model of seven circular steps: 1) Ask: identify the needs & constraints, 2) Research the problem, 3) Imagine: develop possible solutions, 4) Plan: select a promising solution, 5) Create: build a prototype, 6) Test and evaluate the prototype, and 7) Improve: redesign as needed. The project description emphasized the iterations of the design process. TeachEngineering’s lessons often include this seven-step design process model, but some units for lowers suggest partial design processes, such as “Ask → Imagine → Plan → Create → Improve” (omitted Research the problem and Test and evaluate the prototype) (TeachEngineering, n. d.)

The International Technology and Engineering Educators Association (ITEEA) developed various engineering and technology education curriculum based on the Standards for Technological Literacy. Advanced Design Applications (ITEA/ITEEA, 2006), ITEEA’s engineering and technology education program, adopted a technological design loop model with eight steps: 1) Clarifying the problem, 2) Brainstorming ideas, 3) Selecting a potential solution, 4) Modeling and prototyping, 5) Testing, 6) Evaluating and refining, 7) Implementing, and 8) Communicating results. This design process model was developed based on the Standards for Technological Literacy with an emphasis on technical problem-solving.

Engineering is Elementary (EiE) is one of the most well-known engineering education curricula for elementary students (Cunningham, 2009). EIE was developed by Boston’s Museum of Science. EiE developed a design process model and noted that engineers follow the procedures to solve engineering problems. The EiE presented the eight steps of the engineering design process model: 1) Identify, 2) Investigate, 3) Imagine, 4) Plan, 5) Create, 6) Test, 7) Improve, and 8) Communicate (EiE Engineering Everywhere Engineering Design Process Poster, n. d.). Additionally, EiE showed the alternative design process model that has five steps: Ask: What is the problem? 2) Imagine: What are some solutions? 3) Plan: Draw a diagram and Decide what materials need, 4) Create: Build my design and Test it out, and 5) Improve: How can I make my design better? (EiE Engineering Adventures Engineering Design Process, n. d.) EiE curricula emphasizes on the flexibility and iterative nature of the design process.

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The different goal of the design process yielded different approaches. Cross (2000) presented various design process models by its purposes, including descriptive, prescriptive, and interactive models. The descriptive models are based on the solution-focused nature of the design process. The purpose of the models is to identify the significance of generating a solution concept. These process model types usually consist of idea generation, idea analysis, and idea evaluation. One example is French’s (1999) model.

Prescriptive models, on the other hand, were built based on the analysis of engineering design processes. This design model type aimed to persuade designers to adopt improved ways of working. For example, March (1984) presented a design process model using a prescriptive approach that focused the elements of design process rather than procedural arrows and boxes. March’s model contains three reasoning strategies: inductive, deductive, and productive. The first phase of the model is productive reasoning, during which engineers meet design problems and state preliminary problem definitions. The second phase is deductive reasoning, in which engineers analyze and predict the possible consequences. The last phase is inductive reasoning, where engineers evaluate whether the developed solutions meet the clients’ needs or require further modifications.

Interactive models illustrate the iterative nature of the design process. Usually, design processes continually go back and forth. A design problem has subproblems; and solving a subproblem causes changes of the other subproblems. Therefore, design processes interact with other design problem phases, which can be symmetrical, commutative, or circular in form. Cross (2000) studied how creative ideas emerged during the design process and presented a symmetrical interactive model. This type of models begins with an overall problem but iterates through sub-problems and sub-solutions. Rather than depicting the design procedure, the interactive model highlights the iterative nature of the design process.

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Often people call engineering as one discipline, but it consists of multiple sub-majors, and the each major has distinct characteristic natures. Ethnologists Latour and Woolgar (1986) described engineering tasks as follows:

“One area of the laboratory contains various items, apparatus (section A), while the other contains only books, dictionaries, and papers (section B)” (p. 45).

Engineers in section A are in charge of cutting, sewing, mixing, shaking, screwing, and making. On the other hand, the engineers in section B wear white coats and spend long periods of time at their desks. We understand the two engineering sections as one profession; however, their “engineer” tasks are very different. Each engineer has different working styles, which might be rooted in their different educational history or job experiences. The divergent nature of engineering makes difficult to study the engineering design process in and of itself.

Koen (2003) argued that engineering problems feature the characteristics of change, resource, best, and uncertainty. The change feature is explained by the argument that “engineers cause change” (p. 11). Engineers continually deal with various changes during their problem-solving. As noted in the definition of engineering, engineering solves problems under certain constraints and given resources. Design problems explicitly or implicitly contain criteria and constraints that limit the boundaries of problem-solving. Engineers also solve design problems to the best of their ability. There is no definitively right solution to a design problem. Engineers make decisions that influence the next phase of their problem-solving. Lastly, engineering problems are uncertain. Real-world engineering problems lack clear definitions. When solving a problem, engineers often begin by framing the boundary problem-solving in order to define the problem (Buchana, 1992).

Engineering design is a social process. Bucciarelli (2003) described its social nature as

“a process which engages different individuals, each with different ways of seeing the object of design but yet individuals who in collaboration, one with another, must work together” (p. 9).

This quote emphasizes the sociotechnical aspect of engineering design. Engineers work as a team on most design projects. Engineers work with other individuals who have different experiences, cultures, and interests. The sociotechnical aspect can be extended to the client side. Engineers communicate with their clients via design outcomes. When an engineer designs a solution to address the problem, the client may understand the intention of the design in his or her own way. The sociotechnical nature of engineering is a distinct feature of engineering design.

Henry Petrosky (1992; 2006) mentioned that the nature of the failure is imperative to engineering. He noted that the first goal of engineering is to avoid failures; necessarily, engineers experience various failures throughout the design stages. Over the course of engineering history, engineers have accumulated significant knowledge and experiences. However, one cannot deny that most of this knowledge was acquired through engineers’ failures and efforts to overcome them. Bucciarelli (2003) also noted that engineers should be tolerant of failure because engineers cannot fully control how the process of engineering actually works.

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In the field of engineering, design has a special meaning. Engineers design to solve problems using a systematic and intelligent processes. This process is called engineering design. Dym et al. (2005) noted:

“Engineering design is a systematic, intelligent process in which designers generate, evaluate, and specify concepts for devices, systems, or processes whose form and function achieve clients’ objectives or users’ needs while satisfying a specified set of constraints” (p. 104).

Accordingly, Edie, Jenison, Mashaw, and Northup (2001) defined engineering design as

“a systematic process by which solutions to the needs of humankind are obtained” (p. 79).

These definitions indicate that engineering design is neither a routine nor a trial and error process. Engineering design is a process of devising a system or product to meet clients’ needs and wants while satisfying given constraints.

Engineering design inherits features from the nature of engineering and design. Engineering design is a cognitive process that is very murky and unclear (Bucciarelli, 2003). Also, engineering design requires special cognitive abilities, including optimization, decision-making, critical thinking, and analytic ability (NRC, 2000b). Dym and Brown (2012) argued that engineering design is separable from making in terms of its required higher thinking. If a design only requires making, it does not necessarily qualify as engineering design. Engineering design requires some level of compromise to achieve its optimal approach. Accordingly, Wulf (1998) stressed the constraint feature of engineering design. He noted,

“engineering is design under constraint” (p. 29).

He compared engineering design with other creative disciplines, such as music and the arts, and claimed that only engineering operates under such strict constraints.

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Hales and Gooch (2004) noted,

“Design is something that we all do one way or another, and we all think we could have designed things better” (p. 4).

The term design is used as a verb for making or planning something and as a noun for a plan or product. ITEA/ITEEA (2000/2003/2007) used the term “designed world” to distinguish the technologically created world from the natural world. Cross (2000) also noted,

“Everything around us that is not a simple untouched piece of nature has been designed by someone” (p. 3).

These definitions of design inform a broader meaning of thinking, planning, and making something. Additionally, the term design is used in a variety of domains: artistic sketching, blueprint planning or building a structure.

A comprehensive understanding design is extremely challenging due to its multifaceted nature. Lawson and Dorst (2013) argued about the nuances of design as a fundamental human activity of creativity, analysis, problem-solving, learning, evolution, and integration. These characteristics quite resemble the nature of engineering. Design is not a simple thought process, but rather the result of creativity and analytical thinking. To solve design problems, designers need to use various creativity and analytical thinking abilities. Moreover, design is not the result of spontaneous ideation, but instead a product of continuous effort and invention. Design requires a certain level of knowledge and skills. Designers’ abilities vary greatly depending on their life experience and education. These characteristics make it difficult to define design and design methodology (Dorst, 2004; Kimbell, 2009).

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