Engineering 1000
Chapter 3: Problem Formulation
Outline
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Teams and personalities
Mental models
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Metaphors for creative problem solving
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personalities
Mental blocks to creative thinking
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Herrmann Brain Dominance Model
Whole Brain Model
Knowledge Creation Model
lessons from exercises
Heuristics for problem formulation
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statement re-statement
present-state desired-state
Kepner-Tregoe analysis
R. Hornsey
Problem 2
Camels
Somewhere in the Middle East, a man owned 17 camels – his entire wealth. He had three
children who helped him in his transportation business. While on one of their trips, the father
fell ill at an oasis. He called his children to his side and told them his last will: the oldest child
was to have half of the camels, the middle child one third of the camels, and the youngest
child one ninth of the camels (which represented a fair share of the time each had helped the
father in his business). Then the man died.
After the burial, the children were faced with the problem of how to divide the camels
according to their father’s wishes. The discussion soon centred, rather heatedly on how to kill
and cut up some of the camels to come up with the specified shares.
At this moment an old man arrived at camp, hungry and thirsty, and with a camel in the same
condition. The old man listened to the argument for a while and then offered to solve the
dilemma by giving them his camel, if they would provide shelter and food for him for the night.
The children agreed.
During the night, the oldest child decided he better leave with his share of the camels before
the old man – or his siblings – had a change of heart. Later, the middle child awoke, noticed
nine camels gone, and hastened to depart with six. In the morning, the youngest child, noting
that the others had helped themselves to their inheritance, took the allowed two camels, and
bid farewell to the old man with thanks.
The old man then resumed his journey with his well-fed and rested camel.
Creative Problem Solving and Engineering Design, Lumsdaine et al., McGraw Hill 1999
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What is the real problem here?
How do we identify and formulate problems?
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Problem 3
Problems, Teams, and Personalities
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Much of engineering (and other business) is now performed in
teams
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Along with the team management is a personal emphasis
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so it is not surprising that a lot of research has been performed into
what makes teams successful
including the development and management of the team, the roles and
skills of the members, the personalities of the members, conflict
resolution
how do I learn to be a better team member?
and hence to do well at my job
To do this, we need to understand basic aspects of our
personality
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so simple and reliable have been developed to indicate basic
personality types
the most famous is the Meyers Briggs test
e.g. http://www.humanmetrics.com/cgi-win/JTypes1.htm
R. Hornsey
Problem 4
Advantages and Disadvantages of Teams
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Advantages
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wider knowledge and experience is available
interaction of people leads to synergy
better chance of finding optimal solution
team members accept the solution and work better to implement it
team members learn from each other
encourages development of leadership skills
Disadvantages
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more time and personnel needed to build team
team process has low efficiency – lots of ideas but few practical ones
team conflict
“group think”
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Problem 5
A Good Creative Team
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What makes a good creative team?
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Problem 6
Mental Models
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Mental models are tools for aiding problem solving
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and for understanding why individuals tackle problems in different ways
We will look briefly at three concepts
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the Herrmann brain dominance model
knowledge creation
creative problem solving
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Problem 7
Herrmann Brain Dominance Model
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Loosely based on the
anatomy of the brain,
this technique uses a
questionnaire to
determine a person’s
relative strengths in
four ‘quadrants’
D
A
cerebral
rational factual
quantitative academic
mathematical
authoritarian analytical
critical realistic logical
financial technical
left
dominant organised
tactical risk-avoiding
conservative
administrative
scheduled procedural
sequential reliable
detailed
B
spatial risk-taking
holistic play strategic
simultaneous
imaginative artistic
visual conceptual
change-oriented bigpicture
right
intuitive symbolic
teaching expressive
reaching-out
interpersonal sensitive
supportive spiritual
feeling musical
limbic
C
http://www.hbdi.com/
R. Hornsey
Problem 8
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The profile for engineers is typically
very strong in quadrant A
less strong in B and D
weak in C
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None of the categories is ‘bad’
the idea is to identify your natural strengths and to concentrate on
developing your less strong areas
with the aim of being equally strong in all areas, i.e. multi-dominant or
‘whole brain’
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Engineers with strengths in each category are important
e.g. for a bridge construction
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A
technical specs, financing, project logistics
B
low-risk, efficient work flow, how to build it
C
connecting people, effect on communities and environment,
politics
D
traffic projections, different possibilities, aesthetics
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Problem 9
“Creative Problem Solving and Engineering Design” Lumsdaine et al. McGraw Hill 1999
Whole-Brain
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Problem 10
In Which Quadrant Are You?
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Based on the data from the previous page give yourself a
score out of 10 for each quadrant
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note: this is not how the real test is done!
When in a team, do you find yourself behaving according to
your dominant quadrant?
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do you see others displaying other quadrants?
do you see their contributions as valuable to the team?
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Problem 11
Knowledge Creation Model
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How can the whole-brain model be extended to give an
understanding of the innovation process?
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The idea is that knowledge is created as we move from one
quadrant of the Herrmann diagram to the next
It is important here to identify two types of knowledge
Explicit knowledge
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in “Creative Problem Solving and Engineering Design” Lumsdaine et al.
combine the whole-brain approach with lessons for innovation drawn
from Japanese companies
“hard” knowledge that can be expressed in formulae, descriptions,
instructions, diagrams
it can be transmitted readily by manuals, documents etc.
Tacit knowledge
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‘know-how’, experience, intuition, craft, skill
tacit knowledge must be transmitted by interaction and personal
instruction
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Problem 12
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The combined knowledge creation diagram identifies four
stages
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“Creative Problem Solving and Engineering
Design” Lumsdaine et al. McGraw Hill 1999
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socialization: shared vision, corporate culture
externalization: discussions and brainstorming
combination: analysis and evaluation of concepts
internalization: learning and integrating the new knowledge
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Problem 13
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You can see similarities/connections with
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the design process itself
the levels of failure from Ch.2
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Problem 14
Example – Oakland Bay Bridge
Early
History
Bridge
Authority
Bridge
Design
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Soc.
Public discussion and increasing traffic needs after WW1.
Extern.
38 proposals and design concepts by 1928.
Comb.
Board of 3 distinguished engineers recommends analysis of preferred site for more detailed
design and cost estimates. benefits of bridge versus tunnel.
Intern.
Focus on bridge failures with large cantilever designs.
Soc.
Political efforts underway
Extern.
Creating a publicly-owned facility
Comb.
Financing, appointment of state highway engineer, boring and analysis of potential sites
Intern.
Detailed traffic studies, best route, California Toll Bridge Authority
Soc.
Many engineers and consultants work together, port expansion wishes accommodated
Extern.
Intensive design work on many designs, scenic beauty a factor
Comb.
Engineering experience and judgement play key roles in narrowing down design
possibilities. Switch from cantilever to suspension bridge on San Francisco section for
economic, safety and aesthetic reasons.
Intern.
Model testing carried out because multiple-span suspension bridge was a new concept
Completed in 1936 ahead of schedule and within budget
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Problem 15
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Problem 16
http://www.lib.berkeley.edu/Exhibits/Bridge/bb_ce006.html
Metaphors for Creative Problem Solving
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So far, we have considered the thought processes and
dynamics of knowledge creation
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These mind-sets can be conveniently though of in terms of
fictitious personalities
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is needed to seek out new ideas and to see the opportunities presented
by the big picture
‘Detective’
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these are the roles required during the different phases of the
knowledge creation process
‘Explorer’
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now we consider the ‘mind-sets’ required at each stage of the process
performs a more detailed analysis of the situation
problem formulation typically ends after these two roles
‘Artist’
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generates creative and imaginative ideas
but may not analyse them critically
R. Hornsey
Problem 17
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‘Engineer’
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‘Judge’
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identifies flaws in the solutions proposed and works with the ‘artist’ and
‘engineer’ to overcome them
‘Producer’
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shapes the creative ideas into something more practical, examine the
technical issues, optimisation
puts it all together to come out with a good product, i.e. solves the
problems of implementation
may be the project sponsor higher up in the organisation
Without any one of these personalities, a critical element of the
problem-solving team is absent
These personalities fit with the Herrmann diagram and the
knowledge creation cycle as shown on the next page
R. Hornsey
Problem 18
“Creative Problem Solving and Engineering Design” Lumsdaine et al. McGraw Hill 1999
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Problem 19
Mental Blocks to Creative Thinking
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There are three common barriers to creative thinking
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From the following list, choose who you think is the most
creative group of people
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NASA engineers, high school teachers, homemakers, college students,
first graders, journalists, movie producers, abstract painters, auto
mechanics
Creativity is more a matter of environment than profession
Creativity (%)
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false assumptions
habitual thinking
attitude barriers
100
80
60
40
20
0
0
10
20
30
40
Age (years)
R. Hornsey
Problem 20
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“An intelligent mind is a good thinker” … ?
Not necessarily; untrained intelligent people may be poor
thinkers for a number of reasons
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they can create a good justification for any point of view and do not see
the need to explore alternatives
they confuse verbal fluency for good thinking
their mental quickness leads them to jump to conclusions
they think that quick thinking is good understanding
they use intelligence to criticise rather than construct
Other valuable attributes
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play
humour
what if …?
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Problem 21
Exercises
1a. Which of these figures is different from the rest? Why?
�
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Reason:
1b. An army must move some soldiers to a different location. If a
maximum of 39 soldiers and their gear fit into a bus, how
many buses are needed to move 1261 soldiers?
(a) 31
(b) 32 (c) 32.33 (d) 33 (e) 34
Answer:
2. How many squares are there?
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Problem 22
3a. Join all the dots with 4 straight lines with no more than one
line through any dot
3b. Sketch a path from A to B
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Problem 23
4. What do you see below?
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Problem 24
5a. What do you see?
5b. Can you find all 9 people?
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http://www.grand-illusions.com/
Problem 25
Bad Habits
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Exercise 1a & 1b
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Corollary to exercise 1
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in order to know the best answer of those we have, we must look at the
context
Block 2: do not look at the problem in isolation
Exercise 2
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it is possible to make a good case for any shape being the odd one out
hence the question is too vague
Block 1:there is more than one correct answer
the simple answer is that there are 17 squares
but this is limited thinking, e.g. it assumes that the picture is 2-D; what
happens if this is looking at the top of a column of blocks?
Exercises 3a & 3b
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‘thinking outside the box’
Block 3: following the “rules”
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Problem 26
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Exercise 4 – to check progress
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Exercise 5a & 5b
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chances are you answered “a black dot”
possibly “a rectangle containing a black dot”
in fact ~ 95% of the rectangle is white space!
shows ambiguous images; can you see both images interchangeably?
Block 4: discomfort with ambiguity
very little in life is 100% clear – including ENG1000 assignments
Attitudinal blocks
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Block 5: risk avoidance/fear of failure
“if you never fail, you’re not reaching far enough”
Block 6: negative thinking
“it’ll never work …”
R. Hornsey
Problem 27
Problem Formulation
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Following our knowledge creation cycle, the ‘explorer’ and
then the ‘detective’ personalities are appropriate for problem
formulation
Problem formulation (or problem definition) is needed to
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ensure everyone realises that there is a problem
and to specify the real problem
On the following page, we see how the two personalities
approach the same issues
R. Hornsey
Problem 28
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Problem 29
“Creative Problem Solving and Engineering Design” Lumsdaine et al. McGraw Hill 1999
The Explorer
The ‘explorer’ personality is used for divergent thinking
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quadrant D thinking
taking the far view
spotting trends
predicting the future
How you become a trend spotter?
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be selective about information you take in
read articles that contain ideas
talk to people
have broad-ranging interests
synthesise ideas (i.e. think!)
observe what is around you
ask questions
identify how things change over time
find opportunities
R. Hornsey
http://www.angelfire.com/me/jakub/indy/
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Problem 30
The Detective
In contrast to the ‘explorer’, the ‘detective’ specialises in
convergent thinking
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quadrant B personality
looks for root causes
accumulates information, surveys, data
who, what, when, where, why, how much?
Kepner-Tregoe approach (see later)
explicit and tacit knowledge
persistent
R. Hornsey
http://www.sherlock-holmes.org.uk
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Problem 31
Heuristics
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A heuristic technique is essentially a trial and error approach
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We will look at several heuristic approaches to problem
definition
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a number of options are generated and the best is selected
a try-it-and-see experimental approach
a rule of thumb
statement re-statement
source and cause
revision method
present state and desired state
Kepner-Tregoe situation analysis
Remember that these (and the methods we have already
discussed) are merely aids for thinking
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not guaranteed to produce good results
R. Hornsey
Problem 32
Statement Re-statement Technique
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This approach aims to promote a better understanding of a
problem by stating and re-stating the problem in different ways
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The statement re-statement technique consists of four parts
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for which we assume there is a problem statement of some sort already
in existence
1. Determine the real problem
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hence focusing in on the problem
this can be done by rewriting the problem statement to see what
solutions are triggered
see next page
2. Determine actual constraints and boundaries
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sometimes the perceived constraints are tougher than the real ones
in the problem statement, relax the constraints to see if it has changed
in a significant way; if not the original constraints were too tough
e.g. car >500km/h replaced by car > 200km/h
e.g. “lowest price” replaced by “affordable”
R. Hornsey
Problem 33
Restatement
Description
Increase the number of commuters
who use the TTC
Vary the emphasis
Has the focus of the problem itself
changed? How? Is it a better
statement?
Increase: decrease fares? Make more
convenient
Commuters: advertise benefits of TTC
to commuters
TTC: bus lanes, subway to York
Substitute explicit
definitions
Is the problem statement clearer
and more precise? In what way?
Why?
Commuter  ‘people travelling to work
each day’: encourage employers to
reward TTC users.
TTC  trains/buses: make working
easier on trains/buses
Change positives to
negatives and vice
versa
Reverse the statement. Instead of
how to make the car faster, ask
what slows the car down.
Reduce the number of commuters:why
don’t more people use TTC? Fix
reasons.
Replace persuasive
and/or implied
words
Where ‘obviously’ or ‘clearly’ occur,
examine the reasoning. If reasoning
is flawed, what effect will this have?
Underlying reasoning is that by
increasing TTC ridership, we reduce
number of private cars, pollution etc. i.e.
number of commuters is constant.
Promote telecommuting instead.
R. Hornsey
Problem 34
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3. Prioritise goals
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as we saw in Ch.2, not all objectives are equally important
satisficing
4. Link outputs to inputs
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determine what transforms inputs (raw materials, people, money) into
outputs (the desired benefits of the design)
are any stages of the transformation process missing?
are any stages unpredictable? What would you do about them?
re-state problem statement to reflect what is known, unknown, desired,
and unpredictable
R. Hornsey
Problem 35
Present State and Desired State
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An alternative heuristic approach to problem definition is to
focus on the present and desired states
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by manipulating statements of the present state (PS) and the desired
state (DS) we aim to make a clear correlation between the two
PS: too many commuters use private cars
DS: less traffic
PS: too many commuters use private cars because there is no viable alternative
DS: less traffic
PS: too many people use private cars because they must commute and they don’t take public
transport
DS: we need to reduce commuting by private car
PS: too many people use private cars because they must commute and they don’t take public
transport
DS: people should be encouraged to reduce their commute or take public transport
PS: too many people use private cars because they must commute and they don’t take public
transport
DS: people allowed to work closer to/at home or public transport should be made attractive
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Problem 36
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How would this
sequence have been
different if the DS had
been “reduced
pollution”?
The PS/DS approach
can be expressed
diagrammatically
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in the so-called
Duncker diagram
“Engineering by Design” G. Voland, Addison Wesley, 1999
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Problem 37
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This is very similar to the objectives and functions trees we
saw in Ch.2
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except that the aim is to start from the PS and DS and work from both
ends
it enables both more complex and multiple statements to be included
simultaneously
R. Hornsey
Problem 38
Kepner–Tregoe Analysis
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In their 1981 book “The New Rational Manager” Kepner and
Tregoe developed a four-step problem solving approach
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SA and PA are relevant here
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DA and PPA are used later in the design process
Kepner-Tregoe is now a large management consulting and
strategy company
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Situation Analysis (SA): critical aspects first
Problem Analysis (PA): what past event may have caused problem?
Decision Analysis (DA): what actions are needed to correct problem?
Potential Problem Analysis (PPA): how to prevent further problems?
http://www.kepner-tregoe.com
This analysis is primarily intended for engineering problems in
progress
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but can aid in structuring the search for the real problem in any design
process
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Problem 39
Situation Analysis (SA)
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The current situation is analysed according to three criteria
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timing: which is the most urgent problem?
trend: is the problem getting better or worse? how quickly?
impact: what are the consequences of the problem being left
unsolved?
For each problem and sub-problem, each criterion is given a
high, medium, or low ranking of importance
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see example from p.90 of Engineering by Design (reproduced here for
convenience)
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Problem 40
Example – The Water Tank Disaster
The following news story is based on the Nassau edition of Newsday, the Long Island,
N.Y., newspaper (April 24, 1981 ) and OPLOW, American Water Works Association, vol.7,
no.6,June 1981, p.3.
Inadequate safety precautions and an accident inside an empty water tank caused the
deaths of two workmen in New Jersey on April 23. At 4 P.M., a scaffold inside the tank
collapsed and caused the two men painting the tank to fall to the bottom. Stranded
there, they were overcome by paint fumes and eventually lost consciousness. John
Bakalopoulos, 34, of Brooklyn, N.Y., and Leslie Salomon, 31, also of Brooklyn, were not
wearing oxygen masks. The Suffolk County Water Authority's contract for the painting
job specified that workmen wear "air hoods," masks connected to air compressors. The
masks were available, but Bakalopoulos and Salomon had decided not to wear them
because they were unwieldy. Instead, Bakalopoulos wore a thin gauze mask designed
4to filter out dust and paint particles. Salomon wore no mask.
Peter Koustas, the safety man who was handling the compressor and paint feed outside
the tank, asked a nearby resident to call firemen [sic] as soon as he realized the
scaffold had collapsed. Then he rushed into the tank with no oxygen mask, and he, too,
was overcome by the fumes and lost consciousness. The men lay unconscious for
hours as rescue efforts of more than 100 policemen, firemen, and volunteers were
hampered by bad weather. Intense fog, rain, and high winds made climbing the tank
difficult and restricted the use of machinery. Several men collapsed from fatigue.
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Problem 41
Inside the tank, conditions were worse. Because of the heavy fumes, rescuers used only
hand-held, battery-powered lights, fearing that sparks from electric lights might cause
an explosion. Lt. Larry Viverito, 38, a Centereach, N.Y,. volunteer fireman, was overcome
by fumes 65 ft (20 m) above the floor of the tank. Fellow rescuers had to pull him out.
Rescuer John Flynn, a veteran mountain climber, said he hoped he would never have to
go through anything like that night again. For five hours he set up block-and-tackle
pulleys, tied knots, adjusted straps on stretchers, and attached safety lines and double
safety lines. The interior of the tank was as blindingly white as an Alpine blizzard—
completely and nauseatingly disorienting. Fans that had been set up to pull fresh air into
the tank caused deafening noise.
When Flynn first reached the tank floor, he stepped into the wet paint and began to slide
toward the uncovered 4-ft (1.2 m) opening to the feeder pipe in the center of the floor.
Flynn was able to stop sliding, but John Bakalopoulos wasn't as fortunate.
As rescuers watched helplessly, Bakalopoulos, still out of reach, stirred, rolled over, and
in the slippery paint slid into the feeder pipe. He plunged 1 10 ft (34 m) to the bottom.
Bakalopoulos was dead on arrival at the University Hospital in Stony Brook, N.Y., Peter
Koustas, rescued at 1:45 A.M. and suffering from hypothermia, died the following
morning when his heart failed and he could not be revived. Only Leslie Salomon
survived.
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Problem 42
Although there may be additional concerns that
could be identified (such as rescue expenses
and the subsequent use of the water tank), let us
assume that Table 3.2 includes the major
elements of the problem. A review of the
priorities given to each subconcern indicates
that "paint fumes" received high levels of
concern in all three categories (timing, trend, and
impact) for both paint crew members and their
rescuers. Therefore, we should initially focus on
this most urgent aspect of the situation.
This first step in Kepner-Tregoe analysis further
requires that we classify each aspect of a
situation into one of three categories,
corresponding to the next step (problem
analysis, decision analysis, or potential problem
analysis) to be performed in resolving the
problem. In the case of the water tank problem,
since we already know the cause of the paint
fumes (the paint itself), Kepner-Tregoe problem
analysis is unnecessary; we would move directly
to decision analysis (see Chapter 10 of text) and
strive to eliminate the need for painting the tank.
R. Hornsey
From “Engineering by Design” G. Voland,
Addison Wesley, 1999
Problem 43
Problem Analysis (PA)
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SA aids our determination of which problem(s) to tackle first
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PA asks the following questions
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what is the problem? – and what is not?
when did the problem occur – and when did it not?
where did the problem occur? – and where did it not?
what is the extent of the problem?
[much of this seems like common sense, but it helps to have a
structure to follow in instances of duress – like drilling soldiers]
These key considerations are summarized as
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problem analysis assist our thinking for a specific sub-problem
identity, location, timing, magnitude
The aim is to determine why there is a difference between ‘is’
and ‘is not’, between positive and megative
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Problem 44
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Problem 45
“Engineering by Design” G. Voland, Addison Wesley, 1999
Example - Electronics Manufacture
An electronics manufacturing company is involved in the demanding task of producing
miniaturized printed circuitry. One day, the production quality fell off sharply and the
number of rejected circuits skyrocketed. "Why?" demanded the boss. "Why?" echoed
his subordinates. "Temperature in the leaching bath is too high," said one technician. So
temperatures were lowered.
A week later, when rejects climbed still higher, temperatures were raised, then lowered
again, then systematically varied up and down for days. Rejects remained astronomical.
"Cleanliness is not what it should be. That's what's causing the trouble," someone
offered. So everything was scrubbed, polished, filtered, and wiped. The rejects dropped,
then rose again. Acid concentration was the next idea. Same results. Water purity was
checked out on Wednesday, Thursday, and Friday. The possibility of oil transferred from
the operator's fingertips received full scrutiny on the following Monday and Tuesday.
Rejects still were high.
They might have remained high had not one supervisor begun to ask systematic
questions. "What is wrong with the rejected pieces?" This produced the information that
the acid leaching step of the printed circuit pattern was occurring unevenly as if some
waterborne contaminant in the leaching solution was inhibiting the action.
"When does it occur?" A check of the records showed that rejects were at their highest
on Monday mornings, lower on Monday afternoons, and gone by noon on Tuesday.
R. Hornsey
Problem 46
This cast a different light on everything. Now nobody was asking "Why?" about the
cause of a general, ill-defined deviation. Instead they focused on what was distinctive
about Monday mornings compared with the rest of the week. They focused on what
might have been changed that bore a relationship to this timing. An immediate
distinction was recognized: "Monday morning is the first work period following the nonwork period of the weekend." And what changed on Monday morning? On each
Monday, as soon as the tap was turned, water that had stood in the lines over the
weekend came into the printed circuit leaching laboratories.
The water used in the process had to go through intensive purification, since purity
standards of a few parts per-billion are required. A quick search turned up the fact that
some valves had been changed several months before. These valves used a silicone
packing material. As water stood in the lines over the weekend, enough of this silicone
packing material had begun to diffuse into the water and degrade the leaching process.
The result? Many rejections on Monday morning, fewer in the afternoon, and none after
Tuesday noon. By then the contaminated water had been purged from the system.
From “The New Rational manager”, C. Kepner and B. Tregoe, Princeton Research Press, 1981.
R. Hornsey
Problem 47
Summary

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
A good problem definition is necessary for a good design or
solution
Understanding of thinking preferences and elimination of poor
thinking techniques assists the process
Using metaphors can help to adopt the necessary approaches
to the problem
Certain techniques (heuristics) can assist in the process of
formulating the problem
R. Hornsey
Problem 48
Homework
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
Read and understand Chapter 3 of the text book
Read the case studies
Do problem 3.7
R. Hornsey
Problem 49
Exercise – Leaking Oil

Apply Kepner-Tregoe analysis (SA and PA) to determine
the priorities and possible causes of the following problem
Our client is a major food processor. One of the company plants produces oil from corn
and soybeans. The five units that filter the oil are located in one building. On the day
the problem was first observed, a foreman rushed into his supervisor's office: "Number
One Filter is leaking. There's oil all over the floor of the filter house."
The foreman guessed that the leak was caused by valves loosening up from vibration.
This had happened once before. "Number One sits right next to the main feedwater
pump and gets shaken up more than the other four filters." A mechanic tried to find the
leak but couldn't tell much because the oil had already been cleaned up. The lid
fastener looked all right. After examining pipes, valves, and the walls of the filter
chamber, the mechanic concluded that the oil had spilled from another source.
The next day there was more oil. Another mechanic traced the leak to the cleanout
hatch but that didn't help much. Why should the cleanout hatch leak? It looked
perfectly all right. Just to be on the safe side, he replaced the gasket even though it
looked new. The hatch continued to leak. "Maintenance people just aren't closing it
tight enough after they clean it out," someone volunteered. "There are a couple of new
guys on maintenance here since the shifts were changed around last month. I wonder if
they're using a torque wrench like they're supposed to. This happened to us once
before because somebody didn't use a torque wrench." No one could say for sure.
R. Hornsey
Problem 50
The next day an operator slipped on the oil-slick floor and hurt his back. The
cleanup task was becoming more than irksome, according to some outspoken
comments overheard by the foreman. A few people began grumbling about
promises made at the last safety meeting about improving conditions in the filter
house. Two days later the plant manager got wind of the situation, called in the
supervisor and the foreman, and made it clear that he expected a solution to the oil
mess problem within the day.
From “The New Rational manager”, C. Kepner and B. Tregoe, Princeton Research Press, 1981.
R. Hornsey
Problem 51