Design Exploration

Christopher A. MattsonDepartment of Mechanical EngineeringBrigham Young University

MeEn 579 – Global Product DevelopmentMeEn 576 – Product DesignMeEn 497 – Innovation & Entrepreneurship (interdisc) MeEn 476 – Product and Process Development 2MeEn 475 – Product and Process Development 1MeEn 373 – Engineering ComputingMeEn 372 – Machine Design

PAIN: Museums need data about customer habits of their strategic decisions

are based on hypotheses. Optimization in Early Design

Design Exploration

Part 1 Design SpacePart 2 Problem FormulationPart 3 Pareto Traversing

Design SpacePART 1

Mattson and Sorensen, Fundamentals of Product Development, 2013.

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

Desirable & Transferable

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

What’s happening in the design space?

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

What’s happening in the design space?

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

What’s happening in the design space?

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

What’s happening in the design space?

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

What’s happening in the design space?

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

Concept SetQuantityVarietyNoveltyQuality

J.J.Shah, S.M. Smith, and N. Vargas-Hernandez. Metrics for Measuring Ideation Effectiveness. Design Studies, 2003.

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

Quantity in the Concept Set

Low Quantity High Quantity

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

Variety in the Concept Set

Low Variety High Variety

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

Novelty of the Concept Set

Low Novelty High Novelty

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

Problem FormulationPART 2

multidisciplinarymonodisciplinaryinterdisciplinary

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

Multiple Objectives

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

Interconnected Objectives

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

Concept SetQuantityVarietyNoveltyQuality

J.J.Shah, S.M. Smith, and N. Vargas-Hernandez. Metrics for Measuring Ideation Effectiveness. Design Studies, 2003.

subject to

Generic Formulation

1. Formulate an aggregate objective function that captures preference• Weighted Sum (WS) method• Compromise Programming (CP)• Goal Programming (GP)• Physical Programming (PP)

2. Converge on a single Pareto solution

Strategy 1

Strategy 2

1. Diverge: Obtain many Pareto solutions• WS, CP, PP methods• e-inequality Constraint method• Normal Boundary Intersection• Normal Constraint method

2. Converge: Choose the most attractive solution

NC Method Steps

1. Obtain anchor points2. Construct Utopia Line (blue)3. Generate points on utopia line4. Construct Normal Line (orange)

through point on utopia line5. Reduce feasible space6. Minimize m2

7. Repeat Steps 4-6 for all points on utopia line

Messac, Ismail-Yahaya, and Mattson, The Normalized Normal Constraint Method… Structural and Multidisciplinary Opt., 2003.

Curtis, Hancock, and Mattson, Design Space Exploration with a Dynamic Opt. Formulation, Research in Eng. Design, 2013

Image Source: hitachipowertools.com

Concept 2 Concept 3 Concept 5Concept 1 Concept 4

= Impact mechanism= Bevel gears= Trigger= Motor= Counter weight= Spur gears

IGTMWS

• Location: Impact, motor• Type: Motor, gear set• Size: Shafts, gear set

• Center of Mass• Total Weight• Total Cost• Torque supplied to impact • Speed supplied to impact • Maximum Stress

Model Inputs

Model Outputs

• Location: Impact, motor• Type: Motor, gear set• Size: Shafts, gear set

• Center of Mass• Total Weight• Total Cost• Torque supplied to impact • Speed supplied to impact • Maximum Stress

Model Inputs

Model Outputs

• Location: Impact, motor• Type: Motor, gear set• Size: Shafts, gear set

• Center of Mass• Total Weight• Total Cost• Torque supplied to impact • Speed supplied to impact • Maximum Stress

Model Inputs

Model Outputs

• Location: Impact, motor• Type: Motor, gear set• Size: Shafts, gear set

• Center of Mass• Total Weight• Total Cost• Torque supplied to impact • Speed supplied to impact • Maximum Stress

Model Inputs

Model Outputs

• Location: Impact, motor• Type: Motor, gear set• Size: Shafts, gear set

• Center of Mass• Total Weight• Total Cost• Torque supplied to impact • Speed supplied to impact • Maximum Stress

Model Inputs

Model Outputs

subject to subject to

where

subject to

where

Novelty Preferred Variety Quality

Curtis, Mattson, Lewis, and Hancock, Divergent Exploration in Design … Structural and Multidisciplinary Opt., 2013.

Novelty

where

Novelty

where

Novelty

where

Preferred Variety

Quality

where

is the aggregate objective function value

Novelty

Preferred VarietyQuality

Curtis, Mattson, Lewis, and Hancock, Divergent Exploration in Design … Structural and Multidisciplinary Opt., 2013.

Pareto TraversingACT 3

Micro Finance

Pareto Traversing

Pareto Traversing

Micro Finance

Pareto Traversing

Self Finance

PAIN: Museums need data about customer habits of their strategic decisions

are based on hypotheses. Grower Pump

Low cost More affordable than competition More flow rate than competition Simple off-the-shelf parts Reconfigurable

PAIN: Museums need data about customer habits of their strategic decisions

are based on hypotheses. World Cart

Low cost Low packing volume Platform design cut from 1 sheet No metal (except axle, hub hardware) No glue Failed at ¾ ton load

Pareto Traversing

A few future directions

Clever Design

Monetizable Need

Face-to-Face Discussion

Observational Studies

Experiential Studies

Map Drawing

Cultural Familiarity

Location Familiarity

Language Proficiency

Existing Relationships

Methods

Attributes

$2.86 trillion (58%): food

$433 billion (9%): energy

$332 billion (7%): housing

$179 billion (4%): trans.

$158 billion (3%): health

$51 billion (1%) ICT

The Next 4 Billion – 2007 – International Finance Corporation – World Bank

6 billion mobile phone subscriptions worldwide

Developing countries: 29% to 77% from 2000 to 2010

Non-voice services have also dramatically increased

Smart phones will cost the same as non-smart phones by 2018

Mobile Phone Access Reaches Three Quarters of Planet’s Population – 2012 – World Bank

Design Exploration

PAIN: Museums need data about customer habits because most of their strategic decisions

are based on hypotheses.

Novelty

Preferred VarietyQuality

Curtis, Mattson, Lewis, and Hancock, Divergent Exploration in Design … Structural and Multidisciplinary Opt., 2013.

Design Exploration:The divergent/convergent process of discovering, expanding, evolving, and navigating the design space – often in a computationally assisted way – in order to arrive at an optimal design.

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