two methods for product design selectiondbd.eng.buffalo.edu/12th_meet/sapanel.pdf · two methods...
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TWO METHODS FORTWO METHODS FORPRODUCT DESIGN SELECTIONPRODUCT DESIGN SELECTION
Shapour Azarm
Department of Mechanical EngineeringUniversity of MarylandCollege Park, MD 20742
Acknowledgements: Hui Li and Cliff Whitcomb
Issues in Product Design Selection
� People involved take on their own �view� of the problem, (e.g., design, marketing)
� Engineer designs a product consisting of multiple subsystems with multiple, conflicting, non-commensurate �performance� objectives
� Customers with different preferences:
� Few customers (e.g., market segments)� Many customers
� Company usually uses profit for measuring benefit
Typically involves multiple aspects, many in conflict:
SELECTION WITH FEW CUSTOMERS*SELECTION WITH FEW CUSTOMERS*
*Whitcomb, C.A., N. Palli, and S. Azarm, �A Prescriptive Production-Distribution Approach for Decision Making in New Product Design,� IEEE Transactions on Systems, Man, and Cybernetics, 29 (3), pp. 336-348, 1999.
Selection Model with Few CustomersSelection Model with Few Customers
Product Development Strategy Management
Production-Distribution Trade Off
iDistribution Model
Production-DistributionCoordination
Product Performance
Sub-submodel
Product CostSub-submodel
Production Model
Market SubmodelCustomer
Distribution Submodel
Company SubmodelCompany
Distribution Submodel
Company Effectiveness
Sub-submodel
Customer Cost
Sub-submodel
Customer Effectiveness
Sub-submodel
Product Model
Production Submodel
Production Model
Design Product
Alternatives MOP(z)
Determine Product
Cost
MOP
From Production-Distribution Coordination
To Customer and CompanyDecision Making Process
To/From Market MOE Information
MOP
Production Model
Production is the optimization of the product performance.
Determine Product Design Attributes
(MOP) Needed for Design
Determine Customer �j�
Product Effectiveness
UP j(X)
Determine Customer �j� Product Life
CostUC j(X)
Determine Customer �j�
Product Effectiveness
UP j(X)
Determine Customer �j� Product Life
CostUC j(X)
Distribution Model
Determine Company
Business Goals (MOE)
Determine Company Profit(NPV of Profit)
To Production-Distribution Coordination
To/From Product MOP Definition
From Production-Distribution Coordination
From Product Design Ouput
From Product Cost Ouput
Determine Customer �i� Effectiveness
(MOE)
Determine Customer �i�
Life Cost (MOE)
NPV(Profit) Benefit (UC i) Benefit (UP i)
Determine Customer Market Information (Market Size, MOE)
BEGIN
Distribution Model
Distribution is the consideration of individuals in the group decision.
Production-Distribution Overview
Production: Multi-Objective Optimization
f1
f2 Pareto Alternatives
Distribution for a customer
U1
U2
Selection Steps with Few Customers
Step 1: Obtain market information
Step 2: Define measures of performance (MOPs)
Step 3: Generate design alternatives, the �best� possible
Step 4: Determine product cost
Step 5: Determine customer and company MOEs and utilities
Step 6: Choose m-best ranked alternatives for customers and company
Step 7: Apply a business strategy to select the alternative
SELECTION WITH MANY CUSTOMERS*SELECTION WITH MANY CUSTOMERS*
*Li, H., and Azarm, S. �Product Design Selection under Uncertainty and with Competitive Advantage,� Transactions of the ASME, Journal of Mechanical Design, 122, pp. 411-418, 2000.
Selection with Many Customers
UNCERTAINTYFEASIBILITY/SUPERIORITY
BUSINESS GOALS
DM�S PREFERENCES
MARKETCUSTOMERS COMPETITION
SINGLE PRODUCT PRODUCT LINE
Overall FlowchartOverall Flowchart
Design Alternative Generation
multi-objective optimization
permutation
levels of attributes permutedPareto solution
Design Alternative Evaluation
designer's expected utility
Monte Carlo simulation:
deterministic business goalsdesigner's utility
sampling of random variablesrepeat
preferences of sample customerscost
competitive productsmarket size,discount rate,cost,life
uncertain/other information:
Approach with Many Customers
Design alternatives:
Di ,i= 1, ..., I
Exogenous variables
Y
Utility
U(NPV, MS)
Choose Di to maximize U
Design alternative attributes:
Ai
DemandRevenue
Cost
Market share:MS
NPV
Start
End
Selection Steps with Many Customers
Step 1: Define the market, attributes, assume distributions
Step 2: Sample customer preferences
Step 3: Generate design alternatives
Step 4: Assume a choice model, obtain demand
Step 5: Estimate NPV and market share of each alternative
Step 6: Construct designer's expected utility function
Step 7: Select alternative with maximum designer utility
Follow ups!
Multiobjective Optimization: Definition
K}1,...,=k 0, = )(h J,1,...,j 0,)(g :{D D : subject to
)}(f..., ),(f),...,({f)( Minimize
kj
mi1
xxxx
xxxxf
=≤=∈
=
f1 (e.g. time/op)
� Pareto/non-dominated frontier
� Preferred optimum solution Preferredsolution
f2(e.g. weight)
•
Feasible domain
Pareto frontier
pg
Market Share and Demand Estimation
Choice model: customer will choose a design alternative with highest utility.
Start
market share for designs
market size
demand for design
alternatives
calculate a customer�s utility for all
design alternatives
compare utilities of all designs and
customer�s current choice to estimate
the customer�s final choice
calculate customer�s utility for all competitive
products
compare utilities to obtain a customer�s
current choice among competitive
products
aggregate customers'
choices
sample size
End
Start
repeat for each customer
1) Compromise: Satisfy all customer markets with a single product.2) Market Capture: Identify most influential customer market and
select their best alternative.3) Market Share: Identify common customer markets and select their
best alternative.
4) Customize Product: Develop the best product for each customer market.
5) Modularize Product: Develop products by varying their characteristics, divided into baseline and optional attributes, to create a line of products that are best for each different customer market.
Business Strategies with Few CustomersBusiness Strategies with Few Customers
Determine Customer �j�
Product Effectiveness
UP j(X)
Determine Customer �j� Product Life
CostUC j(X)
Determine Customer �j�
Product Effectiveness
UP j(X)
Determine Customer �j� Product Life
CostUC j(X)
Determine Customer �i�
Product Effectiveness
(MOE)
Rank Alternatives andIdentify Common Best Ranked Alternatives, Ai
*
SelectBusiness Strategy
Distribution Model Production Model
Determine Customer �i� Product Life
Cost(MOE)
Determine Company Product
DevolpmentBusiness Goals
(MOE)
Determine Customer Market
Information (Market Size, MOE)
Determine Company
Profit(NPV of Profit)
NPV of Profit Outcome
Acceptable?
Select Alternative(s)
Determine Product Design
Attributes (MOP) Needed
for Design
Design Product
Alternatives MOP(z)(MDO)
Determine Product
Cost
Re-adjust Cost for EOS?
Y
NN
Y
END
Compute Distance-to-Ideal
Change Alternative Designs or
Adjust Business Goals or STOP
KeyModeling Information FlowDesign Process Flow
MOP
NPV(Profit) UC i UP i∆∆∆∆z
Ai*
BEGIN
MOP
Approach with Few Customers
Concluding Remarks
Assumptions: Approach with Few Customers
� Segmentation feasibility
� Generation of design (preferably �best�) alternatives
� Stable customer preferences
� No uncertainty
� Known cost, demand, price
Assumptions: Approach with Many Customers
� Generation of design (preferably �best�) alternatives
� Same attributes for generation and evaluation
� New or improved product for an existing market
� Same time-to-market for all alternatives
� First choice model
� Stable customer preferences
� Static market competition
Conclusion
� Selection methods with few/many customers:� Engineering design with marketing aspects� Few or large variety of customer preferences� Competition in market� Implicit demand� Uncertainty
� Directions for future research:� Some of the assumptions need to be relaxed, e.g.,
� Other choice models
� Dynamic market competition