Chapter 7-Chapter Decision Making and Concept Selection

judgement

integration of a persons basic mental processes and ethical standards good judgement is clearly understanding the realities of the situation

Ratio Scale

interval scale in which 0 is used as anchor needed to establish meaningful weighting factors all operations allowed

Ordinal Scale

items are placed in rank order comparisons made whether two items are equal, greater than, or less than no addition or subtraction does not say how far apart can determine mode

what phase is evaluating and selecting a concept?

last step in conceptual design phase

utility

measure of preference order for a particular user

utility

measure of satisfaction (or preference order) that is associated with each outcome

weighted decision matrix

method of evaluating competing concepts by ranking the decision criteria with weighting factors and scoring the degree to which each design concept meets the criterion

analog models

models based on an analogy or similarity between different physical phenomenon EX. ordinary graph, process flow charts

control volume

models boundaries 1. finite 2. differential

maximax decision rule

should select the alternative that maximizes the maximum value of the outcomes; one with the smallest possible loss look at best outcome OPTIMISTIC approach

continuous media

solids or fluids assume that their medium transmitting a stress or flow does not contain holes

preference

statement of relative value in the eyes of the decision maker Subjective

objective

statement of which decision maker wants to achieve

Decision Under Conflict

states of nature are replaced by courses of action determined by an opponent who is trying to maximize his or her objective function

direct assignment

team decides how to assign 100 points between the different criterion only recommended for teams where there are many years of experience designing the same product line

evaluation

type of process in which alternatives are first appraised according to some standard 1. absolute criteria 2. go/no-go scenario 3. relative criteria, pugh decision matrix, analytic hierarchy 4. best concept

marginal utility

understanding what is gained from adding one more unit to what is already possessed Law of Diminishing Marginal Utility

Complete Criteria Comparison Matrix [C]

use 1-9 ratings 1/# if B is greater than A A=row B=column total each column

point scale

used with decision matrix simplest way to convert the values of different design criteria into a consistent set of values

pugh chart

useful method for identifying the most promising design concepts among alternatives generated relative comparison compares each concept relative to a reference (datum) concept and determines whether the concept in question is the same (S), less than (-), or greater than (+) the datum

Utility Theory

value preference utility marginal utility

objective tree

weighting factors determined by using a hierarchial objective tree some experience needed multiply (Q1)(Q11)(Q111)=Q111

Normalize Matrix [C] to give [NormC]

normalize matrix by dividing each box by the column total

decision point

on decision tree, square

transient (dynamic)

parameters change with time

defensive avoidance

procrastinate, shift responsibility, remain inattentive to corrective information

vigilance

search for relevant information, appraise carefully and unbiasedly before making a decision

hypervigilance

search frantically for immediate solution

similitude

the condition of physical response is similar 1. geometric 2. kinematic 3. dynamic

unconflicted change

uncritically adopt whichever courses of action is most strongly recommended

decision tree

a graphical and mathematical model for decision making under uncertainty probabilities of outcomes are known!!

Nominal Scale

a named category or identifer can only compare if they are the same or not EX. "thick or thin"

iconic model

a physical model that looks like the real thing but is scaled representation aka geometric representations

greater variability in decision variables is associated with

greater risk

Question: Using expected values only, which contract would the decision maker choose?

A: (100,000)(0.6)+(5,000)(0.1)-(40,000)(0.3)=$62,700 B: (60,000)(0.5)+(30,000)(0.3)-(10,000)(0.2)=$37,000 would choose A b/c maximizes utility

Analytic Hierarchy Process

AHP least arbitrary a problem solving methodology for making a choice among a set of alternatives when the selection criteria represent multiple objections, have a natural hierarchical structure, or consist of qualitative and quantitate measurements

Decision Theory

based on utility theory and probability theory 1. alternative courses of action 2. states of nature 3. outcome 4. objective 5. utility 6. states of knowledge

scale models

can be made cheaper and quicker similitude

model validation

checking to see that the model gives an accurate representation of the real world

model verification

checking to see that the model works as intended

Decision Under Certainty

-Has all necessary information to evaluate the outcome of their choices -Each action results in a known outcome which will occur with a probability of 1 -Just choose lowest values on loss table

Perform Consistency Check on [C]

1. Calculate weighted sum vector {Ws}=[C][W] in excel 2. Calculate consistency vector {Cons}={Ws}/{W} 3. Find λ as average values in {Cons} 4. Find Consistency Index (CI)=(λ-n)/(n-1) 5. Calculate Consistency Ratio (CR)=CI/RI -RI is Random Index value found on table 6. If CR<0.1, the {W} is valid

Steps to Make a Pugh Chart

1. Choose Criteria 2. Formulate Decision Matrix -Columns: concepts - Rows: criteria 3. Clarify the Design Concepts 4. Choose Datum 5. Complex the Matrix (+,-,S) 6. Evaluate Ratings 7. Establish new datum (highest rated) and rerun 8. Examine Selected Concept for Improvement Opportunities

AHP Process for Pairwise Comparison of Selection Criteria

1. Complete Criteria Comparison Matrix [C] 2. Normalize Matrix [C] to give [NormC] 3. Average Row Values of NormC to give Criteria Weights [W] 4. Perform Consistency Check on [C]

AHP Process for Pairwise Comparison of Design Alternatives

1. Complete Criteria Comparison Matrix [C] 2. Normalize Matrix [C] to give [NormC] 3. Average Row Values of NormC to give Priority Vector {P1} 4. Perform Consistency Check on [C]

Decision Making Models

1. Decision Under Certainty 2. Decision Under Uncertainty 3. Decision Under Risk 4. Decision Under Conflict

Design Selection Based on Absolute Criteria

1. Evaluation Based on Judgement of Functional Feasibility 2. Evaluation Based on Assessment of Technology Readiness 3. Evaluation based on Go/No-Go Screening of Constraints

To Determine Best of Design Alternatives

1. Final Rating Matrix [FRating] are the values from {P1} 2. Calculate [FRating}{W}={Alternative Value} 3. Select Alternative with the Highest Rating

Models In Evaluation

1. Iconic model 2. Analog model 3. Symbolic model

Measurement Scales

1. Nominal Scale 2. Ordinal Scale 3. Interval Scale 4. Ratio Scale

Finite Element Analysis (FEA)

1. Preprocessing 2. Computation 3. Postprocessing

Steps to Build Mathematical Model

1. Problem Statement 2. Define Boundaries of Model (Control Volume) 3. Determine Pertinent Physical Laws and Available Data 4. Identify Assumptions 5. Construct the Model 6. Computation and Verification 7. Validation of Model

Patterns by Which People Cope with Challenges

1. Unconflicted Adherence 2. Unconflicted Change 3. Defensive Avoidance 4. Hypervigilance 5. Vigilance

utility function conclusions

1. can determine a preference ordering of two different amounts 2. decision makers attitude towards risk

psychological stress arises from:

1. decision makers concern about material and social losses that will result from either course of action chosen 2. reputation as competent decision maker is at risk

aids in mathematical modelling

1. dimensional analysis 2. scale models

systematic methods for determining weighting factors

1. direct assignment 2. objective tree 3. AHP

steps in good decision making:

1. establish objectives 2. classify objectives by importance 3. develop alternative actions 4. evaluate alternatives against objectives 5. alternative that hold most promise=tentative decision 6. explore tentative decision for adverse consequences 7. take action to prevent consequences

requirements for selecting a design

1. set of design selection criteria 2. set of alternatives believed to satisfy the set of criteria 3. means to evaluate the design alternatives with respect to each criterion

situation requiring action:

1. should 2. actual 3. must 4. want

Characteristics of Mathematical Models

1. steady state or transient (dynamic) 2. continuous media or discrete events 3. deterministic or probabilistic 4. Lumped or Distributed

Interval Scale

Difference etween arbitrary paris of values can be meaninglfully compared type needed to determine how much worse A is than D addition and subtraction possible no multiplication or division central tendency

data associativity

ability to share digital design data wiht other applications such as finite element analysis without each application having to translate or transmit data

symbolic models

abstractions of teh important quantifiable components of the physical system that use symbols to represent properties of the real system most important model

chance events

aka states of nature on decision tree circles

dimensional analysis

allows you to express a problem with a minimum number of design variables

value

an attribute of an alternative that is implied by choice EX. if a is chosen over b, a has more value than B money is used to express value

maximin decision rule

choose the alternative that maximizes the minimum payoff that can be obtained select alternative that minimizes the maximum loss WORST CASE SCENARIO

outcome

combination of an action and a state of nature

absolute comparison

concept directly compared with a fixed and known set of requirements (PDS)

relative comparison

concepts are compared with each other on the basis of a metric

unconflicted adherence

continue with current action and ignore information about risks of losses

discrete model

deals with individual entities

states of knowledge

degree of certainty associated with each state of nature expressed as probabilities

Decision Under Risk

each action can result in two or more outcomes, but the probabilities of outcomes are unknown (1) Maximin Rule (2) Maximax Rule (2) Combined Criterion

Decision Under Uncertainty

each state of nature has an assigned probability of occurence -using probability of occurence of each state of nature table, find expected value of each material, lowest is answer

states of nature

environment of the decision model usually out of decision makers control

simulation

exercise the model by inputting a series of values to determine the behavior of the proposed design under a stated set of conditions

minimax regret criterion

finds the maximum opportunity loss for each alternative

steady state

input variables are their properties do not change wiht time

intuition

instinctive feeling as to what is probably right (educated guess)