AXIOMATIC DESIGNS

Bad design is, well, bad design. Six sigma, tightening tolerances, substituting one material for another and so on only treat the symptoms, not the problem. Also, they may create expensive bad designs.

Axiomatic design, a theory and methodology developed at Massachusetts Institute of Technology (MIT; Cambridge, Mass.) 20 years ago, helps designers focus on the problems in bad designs. As Suh (1990) points out, "The goal of axiomatic design is to make human designers more creative, reduce the random search process, minimize the iterative trial-and-error process, and determine the best design among those proposed." This, of course, applies to designing all sorts of things: software, business processes, manufacturing systems, work flows, etc. The technique can also be used for diagnosing and improving existing designs.

SO, WHAT IS AN AXIOMATIC DESIGN?

While "MIT" and "axiomatic" might suggest some lofty academic theory, axiomatic design is well grounded in reality. By definition an axiom is universally recognized principle. One of the earliest uses of axioms was by Euclid, who developed Euclidian geometry from a fundamental set of postulates or axioms. Sir Isaac Newton's laws of mechanics are another example of axioms. Other fields based on axioms include thermodynamics and information theory. So when we talk about axiomatic we are talking about a systematic, scientific approach to design. It guides designers through the process of first breaking up customer needs into functional requirements (FRs), then breaking up these requirements into design parameters (DPs), and then finally figuring out a process to produce those design parameters. [Does this sound familiar? Y = f(x ₁ , x ₂ ...x _n )]. In MIT language, axiomatic design is a decomposition process going from customer needs to FRs, to DPs, and then to process variables (PVs), thereby crossing the four domains of the design world: customer, functional, physical, and process.

The fun begins in decomposing the design. A designer first "explodes" higher-level FRs into lower-level FRs, proceeding through a hierarchy of levels until a design can be implemented. At the same time, the designer "zigzags" between pairs of design domains, such as between the functional and physical domains. Ultimately, zigzagging between the "what" and "how" domains reduces the design to a set of FR, DP, and PV hierarchies.

Along the way, there are these two axioms: the independence axiom and the information axiom. From these two axioms come a bunch of theorems that tell designers some very simple things, which if followed, can make enormous progress in the quality of their product design. The first axiom says that the functional requirements within a good design are independent of each other. This is the goal of the whole exercise: identifying DPs so that each FR can be satisfied without affecting the other FRs.

The second axiom says that when two or more alternative designs satisfy the first axiom, the best design is the one with the least information. That is, when a design is good, information content is zero. That is "information" as in the measure of one's freedom of choice, the measure of uncertainty, which is the basis of information theory. Designs that satisfy the independence axiom are called uncoupled or decoupled. The difference is that in an uncoupled design, the DPs are totally independent; while in a decoupled design, at least one DP affects two or more FRs. As a result, the order of adjusting the DPs in a decoupled design is important.

This order is shown in a design matrix ” Figure 11.8 ” that shows functional coupling between FRs and DPs at a given level of the design hierarchy. Ideally, these FRs and DPs are to be decoupled.

Figure 11.8: Order of design matrix showing functional coupling between FRs and DPs.

AXIOMATIC AND OTHER DESIGN METHODOLOGIES

In the axiomatic design world, zigzagging between adjacent domains, that is between the "what" domain on the left and the "how" domain on the right, will lead to independent, uncoupled (or at least decoupled) design parameters ” namely, "good" designs.

Axiomatic design is not quite the Taguchi method, which is a specific application of robust design. It is not quite quality function deployment (QFD). Nor, like many other quality methodologies, is it an after-the-fact approach that looks at results and then traces back to the source of those results.

Robust design (Taguchi) and axiomatic design are the only methods that address the design itself, ensuring that the designs are good to start with. Unfortunately, while Taguchi focuses on making a part immune to the error in variation, it focuses on only one requirement at a time. A problem might arise when a design has to satisfy two requirements simultaneously , such as designing a car door to seal completely and close easily. In short, a coupling exists between these two functional requirements.

Taguchi method alone sometimes may trap designers into optimizing the wrong function, optimizing a function they do not have ownership of, or optimizing a design parameter that is linked to many functions. Worse, by optimizing one function, designers run the probable risk of degrading other functions. Axiomatic design, on the other hand, avoids all that by breaking the coupling between functional requirements so that they no longer interact with one another.

QFD is similar to axiomatic design in that customer requirements are listed along the left side of a matrix and engineering requirements are lined up along the top. From this matrix, designer teams can see conflicts that need to be resolved. However, QFD is very subjective . Nor does QFD show a mathematical relationship between a functional requirement and a design parameter, which axiomatic design does.

APPLYING AXIOMATIC DESIGN TO CARS

The automotive industry is fraught with couplings between design parameters, such as in styling versus aero-dynamic/cooling requirements, in styling versus crashworthiness, and in highly complex automatic transmissions designs. At one carmaker, the axiomatic methodology helps design teams optimize elements of a conceptual design before engineering creates the detailed designs. The described benefit is that it helps avoid unintended consequences in design, with the axiomatic method indicating where interactions exist between the various elements and what the optimum sequence is. The point is that axiomatic design is said to be a step beyond Taguchi and worthwhile in a DFSS endeavor.

As we already mentioned, an axiomatic design helps designers with both new and existing designs. In both cases, designers are more creative and develop better designs in less time.

New Designs

By following the process, the designer designs in a systematic way, completing prerequisite tasks before continuing to the next stage. Accordingly, the designer is more creative by:

• Understanding a clearly defined problem before design begins

• Identifying innovative ways to fulfill the functional requirements

• Saving time by:

  • Avoiding frustrating dead ends

  • Drastically reducing random searches for solutions

  • Minimizing or eliminating design iterations

The designer uses current design tools more effectively, producing better designs by:

• Selecting the best design among good alternatives

• Optimizing the design properly

• Verifying the design against explicit requirements

• Having a fully documented design for troubleshooting and extensions

Diagnosis of Existing Design

For diagnosing an existing design, the use of axiomatic design highlights problems such as coupling and makes clear the relationships between the symptoms of the problem (one or more FRs not being achieved) and their causes (the specific DPs affecting those FRs). While improving the solution, the designer also enjoys the new-design benefits above.

Extensions and Engineering Changes to Existing Designs

When an existing version needs an engineering change or an upgrade, axiomatic design identifies all of the areas affected by the contemplated changes. As a result, unintended problems are avoided.

To summarize, for both new and existing designs, the designer is more creative, turning out better designs quicker.

Efficient Project Work-Flow

Axiomatic design helps to identify tasks, set a task sequence from the system architecture, and assign resources effectively. This process also allows you to check progress against explicit FRs.

Effective Change Management

When creating change, axiomatic design uses explicit criteria and allows you to select the best option, identify effects throughout the system, and document changes.

Efficient Design Function

Axiomatic design enables use of a common language and shared information between design team members , which preserves institutional learning.

The designers' benefits translate into three categories of benefits for the organization:

1. Competitive advantage: The organization gains a competitive advantage when it satisfies its customers' needs best. With axiomatic design, those needs map to explicit functional requirements and constraints, which the designers strive to meet. (If, for some reason, no design meets the initial set of FRs and Cs, the firm can explain the tradeoffs of specific alternatives to the customer.) Constraints such as cost and weight can be allocated and verified as the design progresses to ensure they are met. Time to market, another source of competitive advantage, is shortened since designers avoid time-consuming iterations and dead ends.

2. Higher profit: The organization can earn more profit by selling more units, commanding a higher price, or reducing cost. Axiomatic design helps in all three areas. With products that meet customers' needs better than competitive products, the firm gains market share, resulting in higher unit sales. In addition, meeting those needs better means more value to the customer, who is then willing to pay a higher price. Three types of cost can be lowered : research and development (R&D), cost of goods sold (COGS), and support, for the following reasons:

   1. The R&D cost is less because designers spend less time designing the product initially and making engineering changes after the product is released.

   2. COGS drops when products are not coupled and therefore are easier to assemble and test.

   3. Support costs are lower because products that are not coupled install and set up faster and typically require fewer warranty repairs .

3. Less risk: Axiomatic design reduces both technical risk and business risk. Axiom 2, the information axiom, ensures that the chosen design has minimum information content, which is defined as the most technically probable to succeed. Business risk is also reduced because:

   • Products satisfy customers' needs since FRs are derived from those needs.

   • Development schedules are shorter and more predictable.

   • Upgrades can be done quickly and effectively.

In sum, axiomatic design provides the designer with the benefit of designing better products faster, and provides the firm with a competitive advantage, higher profit, and less risk.

When you follow the axiomatic design process, you continue to use all of your current software design tools. You will find that you will be more creative, turning out better designs faster, since you will minimize iterations and trial and error. You will have complete documentation of all the design decisions and supporting analysis.

To facilitate the analysis of axiomatic designs, to our knowledge the Acclaro Software allows you to link to all of your tools and to a common database for the entire design team. It is available commercially and may be purchased by contacting Axiomatic Design Software, Inc.

There are a number of techniques used today in design such as QFD, TRIZ, and robust design. The use of these techniques and others is completely consistent with axiomatic design. In fact, axiomatic design can help the designer apply these techniques better. Figure 11.9 shows how they all fit together. Some examples of what these techniques can do are:

1. With QFD (Quality Function Deployment, "the voice of the customer"), designers gather information from customers about their requirements and the relative importance of each. This information helps the designer to choose which FRs must be present and which may be safely ignored.

2. When a designer has selected an FR and wants to identify alternative DPs to achieve it, TRIZ (the theory of inventive problem solving) can be helpful in generating alternatives.

3. After choosing a DP to satisfy an FR, the designer uses robust design to optimize the design of this particular DP, which helps to reduce the information content of the design.

4. The designer follows the axiomatic design process and uses the various techniques when appropriate. Axiomatic design helps the designer avoid mistakes such as unknowingly attempting to optimize a coupled design.

Figure 11.9: Relationship of axiomatic design framework and other tools.

Users of axiomatic designs and applicable software, such as the Acclaro, have found that the process of implementing axiomatic designs is enhanced, in the sense that the designers have more freedom to document every decision and to specify the relationships between FRs and DPs to any level of detail. It also does matrix manipulations, checks for design problems such as coupling, and communicates relevant information to members of the design team. Specifically, the Acclaro software runs on standard PCs and workstations and in addition it links to your software design tools and to your existing database through SQL. No other software is required except for the Java environment, which is available at no charge from Sun Microsystems or from Axiomatic Design Software, Inc.