1Weaver Innovation Tool: Axiomatic Design (A Brief Introduction) Jonathan Weaver UDM ME Department.

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1 Weaver Innovation Tool: Axiomatic Design (A Brief Introduction) Jonathan Weaver UDM ME Department

Transcript of 1Weaver Innovation Tool: Axiomatic Design (A Brief Introduction) Jonathan Weaver UDM ME Department.

Page 1: 1Weaver Innovation Tool: Axiomatic Design (A Brief Introduction) Jonathan Weaver UDM ME Department.

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Innovation Tool: Axiomatic Design (A Brief Introduction)

Jonathan WeaverUDM ME Department

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References

• Nam P. Suh, The Principles of Design, Oxford Series on Advanced Manufacturing, 1990.

• K. Yang & B. El-Haik, Design for Six Sigma: A Roadmap for Product Development, McGraw Hill, 2003.

• Deo & Suh, Axiomatic Design of Customizable Automotive Suspension, Proceedings of ICAD2004, ICAD-2004-38.

• Lui & Soderborg, Improving an Existing Design Based on Axiomatic Design Principles, Proceedings of ICAD2000, ICAD-055.

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Axiomatic Design

• Most principally based on the work of Nam Suh at MIT• The ultimate goal of Axiomatic Design is to establish a science base

for design and to improve design activities by providing the designer with a theoretical foundation based on logical and rational thought processes and tools.

• Other goals:– To make human designers more creative– Reduce the random search process– Minimize the iterative trial-and-error process– Determine the best designs among those proposed– Endow the computer with creative power through the creation of

the science base for the design field

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Axiomatic Design (Cont.)

• Complete coverage of Axiomatic design is a very long endeavor; here we’ll just introduce it

• Axioms are general principles or self-evident truths that cannot be derived or proven to be true except that there are no counter-examples or exceptions.

• Two axioms were identified by examining the common elements that are always present in good designs, be it a product, process, or systems design. They were also identified by examining actions taken during the design stage that resulted in dramatic improvements.

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Axiomatic Design (Cont.)

• The two Axioms:

– Independence Axiom: The independence of Functional Requirements (FRs) must be always maintained, where FRs are defined as the minimum number of independent functional requirements that characterize the design goals.

– Information Axiom: Among those designs that satisfy the Independence Axiom, the design that has the smallest information content is the best design.

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Axiomatic Design (Cont.)

• Violating Axiom 1 results in a coupled design

• Violating Axiom 2 results in system complexity

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Axiomatic Design (Cont.)

• The Independence Axiom is often misunderstood. Many people confuse between the functional independence with the physical independence.

• The Independence Axiom requires that the functions of the design be independent from each other, not the physical parts.

• The second axiom would suggest that physical integration is desirable to reduce the information content, if the functional independence can be maintained.

• Both axioms can be illustrated using a faucet as an example.

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Axiomatic Design (Cont.)

• Let’s discuss the ‘classic’ faucet design problem from the perspective of axiomatic design

– What are the two principle functional requirements?

– What are the two principle design parameters?

– Is it axiomatic?

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Axiomatic Design (Cont.)

• How about now?

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Axiomatic Design (Cont.)

• Matrices can be an effective way to understand the mapping between functional parameters and design parameters

• For the faucet design examples:

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Axiomatic Design (Cont.)

• In the ideal case of total independence, the matrix mapping functional requirements to design parameters is square and diagonal, the design is called uncoupled and each design parameter can be manipulated to meet a particular functional requirement without affecting the other parameters or functions

Design Parameters

DP1 DP2 DP3 DP4

Functions

FR1 X    

FR2 X    

FR3   X  

FR4       X

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Axiomatic Design (Cont.)

• In the decoupled case, the matrix is upper/lower triangular. The design may be treated as uncoupled if the design parameters are fixed in the order dictated by the matrix

Design Parameters

DP1 DP2 DP3 DP4

Functions

FR1 X    

FR2 X X    

FR3 X X X  

FR4 X X X X

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Axiomatic Design (Cont.)

• In the coupled case (highly undesirable), the matrix is populated above and below the main diagonal (possibly completely populated). There is an innovation opportunity with such designs if they can be decoupled!

Design Parameters

DP1 DP2 DP3 DP4

Functions

FR1 X X X X

FR2 X X X X

FR3 X X X X

FR4 X X X X

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Axiomatic Design (Cont.)

• Consult Nam Suh’s work for details on the conceptualization process of mapping functional requirements to physical solutions, and ultimately to processes.

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Automotive Suspension Example (based on Deo & Suh’s paper)

• Problem: comfort/handling tradeoffs involving damping and stiffness of suspension

• Active suspensions have drawbacks: power, size weight, cost

• This paper looks at adaptive systems wherein some design parameters are changed in response to some information

• A novel adaptive suspension architecture is proposed which allows independent control of stiffness, damping and ride height

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Prior Art on Variable Stiffness and Ride Height

• A typical solution is an air spring, but as shown below, this design is coupled (the number of FR’s exceeds the number of DP’s)

DP 1: Amount of Air

FR1: Control Ride Height X

FR 2: Control Stiffness X

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Proposed Architecture

From Deo & Suh

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Mapping of Functional Requirements to Design Parameters

DP 1: Pivot Position

DP 2: Cam Position

DP 3: Orifice Control

FR 1: Stiffness X

FR 2: Ride Height X X

FR 3: Damping X

As discussed in the paper, a feedback control system can eliminate the coupling.

Consult the paper for more details.

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Automotive NVH Example

• Liu and Soderborg investigate the effect of a number of design parameters on NVH characteristics

• The effect of those parameters on NVH as a percent of the total response is measured and tabularized on the next page

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From Liu & Soderborg

Note that it is highly coupled and the best order to attach the problem is not obvious – until it is re-ordered as shown on the next page.

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From Liu & Soderborg

Now the best order – and the necessary tradeoffs along the way – are clear!