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1 Copyright © 2102 by ASME
Proceedings of the ASME 2012 International Design Engineering Technical Conferences &
Computers and Information in Engineering Conference
IDETC/CIE 2012
August 12-15, 2012, Chicago, IL, USA
DETC2012-71168
DRAFT: MANAGING DILEMMAS EMBODIED IN 21ST CENTURY ENGINEERING
Salman Ahmed1, Minting Xiao
1, Jitesh H. Panchal
2, Janet K. Allen
1 and Farrokh Mistree
1
1The Systems Realization Laboratory @ OU
2The Collective Systems Laboratory
University of Oklahoma Washington State University Norman, Oklahoma 73019 Pullman, Washington 99164 ABSTRACT
In this session we describe in four parts the pedagogy and
outcomes of a course Designing for Open Innovation designed to
empower 21st century engineering students to develop competencies
associated with innovating in an inter-connected technologically flat
world:
1. Competencies for Innovating in the 21st Century, [1].
2. Developing Competencies In The 21st Century Engineer, [2]
3. Identifying Dilemmas Embodied in 21st Century Engineering,
[3]
4. Managing Dilemmas Embodied in 21st Century Engineering -
this paper.
In the first paper we describe the core characteristics of the
engineering in an interconnected world and identify the key
competencies and meta-competencies that 21st century engineers will
need to innovate and negotiate solutions to issues associated with the
realization of systems.
In the second paper, we describe our approach to fostering
learning and the development of competencies by an individual in a
group setting. We focus on empowering the students to learn how to
learn as individuals in a geographically distanced, collaborative
group setting.
We assert that two of the core competencies required for success
in the dynamically changing workplace are the competencies to first
identify and then to manage dilemmas. In the third paper, we
illustrate how students have gone about identifying dilemmas and in
the fourth paper how they have attempted to manage dilemmas. In
papers three and four students have briefly described the challenges
that they faced and their take-aways in the form of team learning and
individual learning.
In this the last of four papers in this session, we focus on how
students learned to manage dilemmas associated with the realization
of complex, sustainable, socio-techno-eco systems, namely, energy
policy design. The example involves the identification of a bridging
fuel that balances environmental, economic and socio-cultural
concerns. The principal outcome is clearly not the result attained but
a student‟s ability to learn how to learn as illustrated through the
development of personal competencies in a collaborative learning
framework and environment.
1 FRAME OF REFERENCE
1.1 Educational context This paper is heavily scaffolded from the course AME5740
Designing for Open Innovation orchestrated by Dr. Mistree and Dr.
Panchal in Fall 2011. The course was aimed for the students to
develop some meta competencies which are given in the following
list-
1. Ability to identify the competencies and meta-competencies you
need to develop to be successful at creating value in a cultur-
ally diverse, distributed engineering world.
2. Ability to identify and manage dilemmas associated with the
realization of complex, sustainable, socio-techno-eco systems.
3. Ability to continue learning through reflection and the associated
creation and articulation of knowledge.
4. Ability to account for sustainability considerations in formulating,
partitioning, and executing multidisciplinary, systems-design
problems that are characterized by the open innovation con-
struct.
5. Ability to speculate and to identify research topics worthy of
investigation.
We, the students, were asked in the course to identify some meta
competencies that are needed to be a successful designer of energy
infrastructure in the year of 2030 by posing the Question of the
Semester:
We imagine a future in which individuals are empowered
to participate in the global value network where geograph-
ically distributed people (including engineers) collabora-
tively develop, build, and test solutions to complex socio-
techno-eco problems.
Bridging fuel: What are the technology, policy and communication
dilemmas associated with utilizing natural gas as bridging fuel for
next 25 years, while minimizing the adverse impact on quality of
life?
2 Copyright © 2012 by ASME
Policies for distributed generation technologies: What are the
technology, policy and communication dilemmas associated with
implementing the Feed-In-Tariff (FIT) policy while maximizing the
adoption of distributed generation technologies?
This is the way the course had started by presenting the question
for semester as a common platform and pushing the students out of
their comfort zone by asking them to speculate the future and identify
the competencies and learning objectives that are needed to do that.
Throughout the course Dr. Mistree and Dr. Panchal have assisted the
students to reach their competencies by introducing to them many
concepts such as learning is a conscious activity, Globalization 3,
dilemmas, sustainability, learning organization, Bloom‟s Taxonomy,
Deep Reading, Attention Directing Tools and assignments which
were either scaffolded or non-scaffolded, either on individual level or
in a group stetting where the students were both geographically and
culturally diverse etc. For additional information see [2].
After giving all this building blocks to the students, in the end of
the course student were set free and asked to answer the question for
the semester by looking back and connecting the dots by the help of
the competencies and learning objectives that the students wanted to
develop in the beginning of the course. Thus the students have been
transformed from being a tool user to tool maker.
In this paper we, Salman and Minting, present our finding about
the first part of the question for the semester. It is because after taking
the course we have learned that in 21st century we seldom face prob-
lems that are remote and have win-win solution but rather we face
with complex intertwined dilemmas that have no win-win solutions.
Dilemmas arise from requirements from multiple regions. On one
hand, conflicts of the objectives exist, on the other hand, all the
requirement regions are significant for human living; poor satisfac-
tion of requirements of any region may lead to disaster. This means
dilemmas cannot be solved, the goal of managing dilemmas can only
be to minimize loss.
Thus it is important that we identify the critical dilemmas and then
manage the dilemmas in the means of looking for trade-offs between
conflicting goals and seeking for a balanced solution.
In this paper, we describe how students learned to manage
dilemmas associated with the realization of complex, sustainable,
socio-techno-eco systems. These competencies are being developed
throughout this course and have helped us to come up with the work
in this paper. As the students in this course are in a learning
organization, with different strengths from each individual, we have
different focus on different parts of the question for the semester,
which in all result in a comprehensive thinking on some important
issues for current world. Bertus and co-authors presented an approach
to identify the dilemmas, in the context of designing FIT policies [3],
by developing the objectives and the requirements of stakeholders
and policy makers, and analyzing their interactions with Feed-In-
tariff policies.
In this paper we present findings for the first part of question for
semester which is about the bridging fuel. So as a summary, the
motivational question in this paper is „What are the dilemmas associ-
ated in eco-socio-eco system that needs to be considered? What is
the approach of finding a bridging fuel for 2030 and how does it
manages dilemmas?’
It is because after taking this course we have learned that human
being needs to adopt such engineering system that will enable us to
live in harmony with nature for the sake of sustainability. As people
have become aware of negative effects that fossil fuels are bringing
to human life, people are looking for bridging fuels that can satisfy
the energy needs of human being in the near future. However, we do
not always make decisions that will lead us to sustainable engineering
system due to the dilemmas of meeting our increased life expectancy
while using our limited resources. We need to understand that in
order to sustain we have to manage dilemmas rather than solving
specific problems. We assert that a sustainable engineering system
can be achieved if we can identify the dilemmas in the aspects of eco-
socio-eco and manage it by the help of technology.
FIGURE1 TECHNOLOGY PRISM
In Figure 1 we present a technology prism which has been taken
from the course, where the key issues in the individual aspects of
eco-socio-eco has been shown and the dilemmas between the aspects
has been identified and technology is considered as a means to
achieve sustainable engineering system. Likewise we believe that
selecting a bridging fuel which can manage the dilemmas in the
aspects of eco-socio-eco system can be a step towards sustainable
energy system. Some assumptions are made while writing the paper follow:
1. Only eco-socio-eco region has been considered as the boundary
for dilemma management and for achieving Sustainable
engineering system.
2. Our approach to manage the dilemmas is to find an appropriate
bridging fuel; the only way that the dilemmas can be managed is
that people will largely transit from dependent on current fossil
fuel system to the bridging fuel. We assume that the bridging
fuel energy system will be adopted in the next few years.
3. There are many methods for selection; each has its limitation
and advantage. The one chosen to be used in this paper has its
limitation in applying to dilemma management. However, it is
used here for demonstration process to provide some insight of
how the dilemmas can be managed.
4. Assumptions are made that the potential fuel sources used in
carrying out the selection methods are the most suitable candi-
dates.
5. The decisions regarding comparison of each attributes of each
fuel sources in preliminary selection is based on intuition.
6. Relative importance of attributes of selection process is based
on intuition.
7. Attribute ratings of selection process are based on intuition after
reflecting from hard information.
8. The principal outcome is clearly not the result attained but
a student‟s ability to learn how to learn as illustrated
through the development of personal competencies in a
collaborative learning framework and environment.
Our approach for managing dilemmas is illustrated in Figure 2.
The inner triangle represents the dilemmas from three regions of the
3 Copyright © 2012 by ASME
most important issues that human are facing with. In order to
minimize the damage, we come up with the approaches to deal with
the dilemmas, by using different domains of knowledge in Bloom‟s
Taxonomy introduced in this course. The earlier steps of managing
the dilemmas are included in the outer triangle, which involves
Knowledge, Analysis and Evaluation. The later steps of managing the
dilemma, which is the process of carrying out the numerical models,
is the synthesis of the previous steps and the dilemma prism, is in the
center of the picture.
The road map of this paper is explained in terms of the steps of
the approach to deal with dilemmas.
1. List the dilemmas. The approach to identify the dilemmas is
introduced by Bertus and co-authors [3]. In this paper the dilem-
mas are listed in Section 1.1
2. Analyze and break down each dilemma to find the conflicting
goals within the dilemma. The requirements we come up with
are in Section 2.1
3. Categorize the dilemmas into different regions of eco-socio-
eco.*
4. Prioritize and rank the dilemmas according to their importance.*
The relative importance of different requirements are presented
in the tables of Selection Process in Section 2.3.
5. List the alternatives/methods that can possibly solve the conflict-
ing goals. This is in Section 2.1.
6. Evaluate the strength and weakness of the alternatives against
meeting the goals. The evaluation against the general require-
ments of each region is presented in Preliminary Selection phase
in Table 1.4, and the evaluation with more information against
more specific requirements are presented in the Selection Pro-
cess.
7. Come up with a number of most-likely-to-succeed alternatives
based on the strength and weakness with regard to the general of
each alternative, and the prioritizing of the conflicting goals.
This is the Preliminary Selection Process, and the numerical
model is explained in Section 2.2.
8. Select the fuel that is best in reaching a balance that is desired
because of our relative priority of the goals. This is the Selection
Process, and the numerical model is explained in Section 2.3.
FIGURE 2 STRUCTURE OF THE PAPER ON AN APPROACH FOR MANAGING DILEMMAS
* The dilemmas are categorized and prioritized based on
technology prism concept.
1.2 Dilemmas in an economic, socio-cultural,
ecological system
Before identifying the dilemmas, first it is necessary to
understand the concept of dilemma. As it has been defined in
Wikipedia „A dilemma is a problem offering two possibilities,
neither of which is practically acceptable. One in this position
has been traditionally described as "being on the horns of a
dilemma", neither horn being comfortable. This is sometimes
more colorfully described as "Finding oneself impaled upon
the horns of a dilemma", referring to the sharp points of a
bull's horns, equally uncomfortable (and dangerous)‟. So, we
understand that there is no win-win solution in a dilemma
because it cannot be solved. We have to find balances between
the conflicting objectives in order to reduce the harmful ef-
fects.
A seven step method is described for identifying
dilemmas in context of FIT; see [3]. We have followed those
seven steps in a general way and used it in context of
sustainability to identify dilemmas. Based on the Technology
Prism in Figure 1, we have identified that the stakeholders for
sustainable system are three regions consisting of economical,
socio-cultural and ecological. We have analyzed the demand
and wishes of those three regions and synthesized the
dilemmas by merging the conflicting demands and wishes
from each region. The dilemmas are given as follows-
Ecology - Economic
1 The fuel should be such that it is environmental friendly
and has low lifecycle cost.
2 The need to reduce the toxic waste of the fuel over the
need to decrease lifecycle cost.
Ecologic - Socio-Cultural
3 The need of the fuel to be renewable and also to be capa-
ble of meeting huge public demand.
4 The need of the fuel to be environmentally friendly
(Renewable energy, like wind energy) over the need of
the fuel to meet the demand of geographically distributed
customers.
Economic – Socio-Cultural
5 The need to consume less in order to preserve ecological
system over the need to improve the quality of life
6 The need of the fuel to meet the demand of public over
the need to reduce dependence on foreign oil.
7 The need to transit to new energy infrastructure based on
domestic/reliable fuel source (considering national secu-
rity) over the cost of transition.
It is seen that the issues from different regions are not iso-
lated but rather they are interconnected and create dilemmas
which must be managed. In Section 2.22 we have presented
the requirement criteria that a bridging fuel must have to man-
age the dilemmas mentioned above.
As it has been stated in the abstract that our focus is about
presenting an approach to manage the dilemmas with the help of
selection tools . So in the next section we have shown literature
review of selection methods. The result of selecting a
bridging fuel is discussed in Section 3. And how the
process of selection a bridging fuel helps managing the
dilemma is explained in Section 4.
4 Copyright © 2012 by ASME
2 LITERATURE REVIEW ON SELECTION METHODS
Engineers often face situations where decisions need to be
made between conflicting objectives and they rely on Multi
Criteria Decision Making (MCDM) to support their decision
making. There are over 70 MCDM methods in existence
however all of them have fundamental short comings and
majority of them are nothing more them attention directing
tools, [4]. According to George Hazelgigg
regarding the
verification and validation of selection methods, there is only
one true MCDM methods and the rest of them completely or
partly fail to meet the criteria, [5]-
1. The method should provide a rank ordering of candidate
designs.
2. The method should not impose preferences on the
designer, that is, the alternatives should be ranked in
accordance with the preferences of the designer.
3. The method should permit the comparison of design
alternatives under conditions of uncertainty and with risky
outcomes, including variability in manufacture, materials,
etc., which pervade all of engineering design.
4. The method should be independent of the discipline of
engineering and manufacture for the product or system in
question.
5. If the method recommends design alternative A when
compared to the set of alternatives S¼{B, C, D, . . . },
then it should also recommend A when compared to any
reduced set SR, such as {C, D, . . . } or {B, D, . . . } or
{D, . . . }, etc.
6. The method should make the same recommendation
regardless of the order in which the design alternatives are
considered.
7. The method itself should not impose constraints on the
design or the design process.
8. The method should be such that the addition of a new
design alternative should not make existing alternatives
appear less favorable.
9. The method should be such that obtaining clairvoyance on
any uncertainty with respect to any alternative must not
make the decision situation less attractive (information is
always beneficial).
10. The method should be self-consistent and logical, that is, it
should not contradict itself and it should make maximum
use of available information for design alternative selec-
tion.
In addition to fail to meet the criteria, different MCDM
methods provide different result for the same problem and
hence it is extremely important that the Decision Makers
(DM) are aware of the problem in hand, limitations of MCDM
methods and interpretation of results.
In this paper, attention directing tool is used because of the
quality and quantity of available information. An attention
directing tools acts as a guide, a result is produced, with the
DM making the final selection, considering the area of
applicability the tool, the limitations and assumptions associ-
ated with it, and an analysis of the consistency and sensitivity
of the results. When using a selection method the DM
assumes that complete information is available; hence the data
input is a perfect reflection of the physical situation. The use
of an attention directing tool does not require the DM to make
this assumption, and allows for the DM to attempt to compen-
sate and investigate the effects of this imperfect and incom-
plete representation.
2.1 An Approach to Selection Methods
The approach for selection of the bridging fuel is based on
the Preliminary Selection DSP and Selection DSP methods
proposed by Mistree and co-authors [10].. They proposed two
methods for selection namely preliminary selection and
selection process. The preliminary selection Decision support
problem is to be formulated and solved when a decision is to
be based on experience based soft information. A selection
decision support problem is to be formulated and solved when
meaningful hard information is available.
Preliminary selection involves the selection of the most-
likely to succeed concepts for further development into feasi-
ble alternatives. A flow chart of preliminary selection is
shown in Figure 3.
Figure 3 FLOW CHART OF PRELIMINARY SELECTION
The selection DSP facilitates the ranking of alternatives
based on multiple attributes of varying importance. The order
indicates not only the rank but also by how much one alterna-
tive is preferred to another. Both science based objective
information and experience based subjective information can
be used. A flow chart of selection is shown in Figure 4.
Figure 4 FLOW CHART OF SELECTION
2.2 Preliminary Selection
Each of the following section is based on the Steps shown
in Figure 3.
2.2.1 Step I- Potential Candidates of Fuel Sources We have identified the following nine alternatives for bridging
fuels. They are presented in no specific order. Each is listed with an
acronym, a small summary, and a basic list of advantages and disad-
vantages relating to that particular alternative.
Nuclear (old and new plants) - NF
5 Copyright © 2012 by ASME
Encompassing fission and fusion, nuclear power focuses on
reactions between particles on the atomic and subatomic levels which
produce high amounts of energy. Nuclear fission involves the split-
ting of Uranium atoms to create heat. That heat is contained and
routed to power steam turbines which, in turn, power generators that
create electricity. Nuclear fusion could nearly be considered com-
pletely opposite of fission as it joins, rather than separates, multiple
atoms together. This process requires a significant amount of heat to
begin the reaction but the results are explosive. Unlike fission,
nuclear fusion is not well controlled to where the energy can be easily
harvested
Petroleum - OIL
One of the fossil fuels in this list, petroleum in a very strict sense
refers solely to crude oil. More commonly it refers to the different
possible states of hydrocarbons. In general, fossil fuels are used in
power plants similar to nuclear fission in that they mainly provide
heat to turn a turbine, in turn turning a generator, and produce
electricity. The main difference is that a fossil fuel power plant
requires combustion of the fuel. The heat from combustion converts
water into steam which is then used to turn the turbines.
Coal (old plants and plants with carbon-capture technology) - CL
Another of the fossil fuels listed here, coal is made up of carbon
and various other elements including hydrogen. As with petroleum,
coal is burned to heat steam to power turbines which turn generators
and produce electricity. One main difference between coal and petro-
leum is that coal must be crushed into a fine dust to be burned. Coal
currently provides roughly a quarter of our energy.
Natural Gas - NG
Natural gas is a naturally occurring gas mixture consisting
primarily of methane, typically with 0–20% higher hydrocarbons
(primarily ethane). It is found associated with other hydrocarbon fuel,
in coal beds, as methane clathrates, and is an important fuel source
and a major feedstock for fertilizers.
Most natural gas is created by two mechanisms: biogenic and
thermo genic. Biogenic gas is created by methanogen organisms in
marshes, bogs, landfills, and shallow sediments. Deeper in the earth,
at greater temperature and pressure, thermo genic gas is created from
buried organic material.
Before natural gas can be used as a fuel, it must undergo pro-
cessing to remove almost all materials other than methane. The by-
products of that processing include ethane, propane, butanes, pen-
tanes, and higher molecular weight hydrocarbons, elemental sulfur,
carbon dioxide, water vapor, and sometimes helium and nitrogen.
Natural gas is often informally referred to as simply gas, especially
when compared to other energy sources such as oil or coal.
Solar (photovoltaic, concentrated solar, solar heating, solar energy
chemical storage [like hydrogen generation]) - SL
Solar energy, radiant light and heat from the sun, has been har-
nessed by humans since ancient times using a range of ever-evolving
technologies. Solar radiation, along with secondary solar-powered
resources (such as wind and wave power, hydroelectricity and bio-
mass) account for most of the available renewable energy on earth.
Only a minuscule fraction of the available solar energy is used.
Solar powered electrical generation relies on heat engines and
photovoltaic. Solar energy's uses are limited only by human ingenu-
ity. A partial list of solar applications includes space heating and
cooling through solar architecture, potable water via distillation and
disinfection, day lighting, solar hot water, solar cooking, and high
temperature process heat for industrial purposes. To harvest the solar
energy, the most common way is to use solar panels.
Solar technologies are broadly characterized as either passive
solar or active solar depending on the way they capture, convert and
distribute solar energy. Active solar techniques include the use of
photovoltaic panels and solar thermal collectors to harness the
energy. Passive solar techniques include orienting a building to the
Sun, selecting materials with favorable thermal mass or light dispers-
ing properties, and designing spaces that naturally circulate air.
6 Copyright © 2012 by ASME
Wind (on-shore, off-shore) –WD
Wind power is the conversion of wind energy into a useful form
of energy, such as using wind turbines to make electricity, windmills
for mechanical power, wind pumps for water pumping or drainage, or
sails to propel ships.
Biomass – BM
Biomass, as a renewable energy source, is biological material
from living, or recently living organisms. As an energy source, bio-
mass can either be used directly, or converted into other energy prod-
ucts such as biofuel.
In the first sense, biomass is plant matter used to generate
electricity with steam turbines & gasifies or produce heat, usually by
direct combustion. Examples include forest residues (such as dead
trees, branches and tree stumps), yard clippings, wood chips and even
municipal solid waste. In the second sense, biomass includes plant or
animal matter that can be converted into fibers or other industrial
chemicals, including biofuels. Industrial biomass can be grown from
numerous types of plants, including miscanthus, switch grass, hemp,
corn, poplar, willow, sorghum, sugarcane, and a variety of tree spe-
cies, ranging from eucalyptus to oil palm (palm oil).
Geothermal (heating and electricity) – GT
Geothermal energy is thermal energy generated and stored in the
Earth. Thermal energy is the energy that determines the temperature
of matter. Earth's geothermal energy originates from the original
formation of the planet (20%) and from radioactive decay of minerals
(80%)4
Hydropower (dams, miniature dams, river hydropower, wave power,
tidal power, rain power) – HP1,2
Hydropower is power that is derived from the force or energy of
falling water, which may be harnessed for useful purposes. Since
ancient times, hydropower has been used for irrigation and the opera-
tion of various mechanical devices, such as watermills, saw mills,
textile mills, dock cranes, and domestic lifts. In modern times it is
used to produce electricity by building dams.
Hydro is one of the largest producers of electricity in the United
States. Water power supplies about 10 percent of the entire electricity
that we use
2.2.2 Step II-Requirement criteria of Bridging Fuel The dilemmas associated in using fuels is presented in Section
1.1 the requirement criteria of bridging fuel under the region of ecol-
ogy, social and economic of the bridging fuel is identified.
Environmental
• Effects on environmental elements (soil, water, air, etc.) [EEE]
- It covers the side effects that are incurred on earth, water, air
etc. due to its usage.
• Renewability/Recyclability [RW] - It tries to classify whether
the fuel is renewable and also whether it can be recycled or not
• Reduction of toxic wastes. [RTW] - It means that the fuel
which is less toxic is the better one.
Economic
• Lifecycle cost [LCC] - It is the sum of all recurring and one-
time (non-recurring) costs over the full life span or a specified
period of a good, service, structure, or system. In includes pur-
chase price, installation cost, operating costs, maintenance and
upgrade costs, and remaining (residual or salvage) value at the
end of ownership or its useful life.(From Business dictionary)
• Cost per kilowatt hour to produce [CPP] - It is the price to pro-
duce energy.
• Reduce dependence on foreign oil [RDFO] - It is implying that
domestic fuel source should be preferred over foreign fuel
source so that it can make a secured energy sector.
• Meet the demand of geographically distributed customers
[DGDC] - It means that the fuel can delivered wherever there
is demand i.e. the availability of fuel is high and it can reach its
customers easily.
Socio-Cultural
• Maintains or improves the quality of life [QL] - This relates
basically to the overall health of the population. The bridging
fuel should not cause or contribute to any negative effects on
individual health.
• Available to all that desire to use the fuel [ADF] - Relating in
part to its versatility, the bridging fuel must be in ample supply
to be purchased for personal and commercial use.
7 Copyright © 2012 by ASME
• Available on demand, reliable [DR] - The general population
has become accustomed to on-demand electricity and energy.
The standard of living is not expected to decline because of the
selection of the bridging fuel.
• Empowers customers [EC] - In this wired and interconnected
world that is continually being flattened, individuals are able to
partake in activities that could not be done previously. A
bridging fuel that supports more individuals' efforts to compete
in the G3 world is vital.
Engineering
• Secure [SC] - In basic terms, this refers to how safe the bridg-
ing fuel is with respect to personal, national, and source secu-
rity. Personal security consists mainly of safety through per-
sonal use. National security refers to the safety of our nation
at all times. Source safety includes supply amount,
accessibility, and reliability.
• Ability to scale with demand [SD] - Energy demand is varia-
ble, dependent on far too many factors to list. Scaling down
when demand is low and scaling up when demand peaks is
extremely important since energy or electricity cannot be
easily stored.
• Versatile [V] - Many current technologies require the same
fuel source for operation. Choosing an appropriate bridging
fuel for the future means it may be utilized in varying fields
for various purposes. Its ability to meet the requirements for
each of these fields is of considerable importance.
• Easily transported [ET] - Energy in the form of electricity is
easily transported from place to place by means of the mil-
lions of miles of power lines. Since electricity is not har-
vested directly, it is important that the bridging fuel can be set
up for converting immediately to electricity after extraction or
can be transported quickly and easily to a power plant to do
the same.
• Efficient [EFF] - The generic definition of thermal efficiency
is simply stated as the ratio of what comes out of the system
to what goes in. A greater efficiency is desired as a given
process with higher efficiency will yield more products or re-
quire less input to yield a constant amount of product
2.2.3 Step III- Viewpoints of Attributes In order to work efficiently in the selection process, general
viewpoints are given here as guidelines to creating the Comparison of
Concepts tables with respect to the datum. A table of comparison of
some fuels with nuclear power (NF) is given in 2.24 as an example,
see Table 1. The justification of viewpoints for that comparison with
NF as datum is included below.
[EEE] - Does the bridging fuel alternative cause or have the
potential to cause more or more severe environmental effects than the
datum? If so, -1. If it will produce similar effects on the
environment, 0. If it will produce less harsh effects on the
environment so that it will be better than the datum, 1. With regard to
this attribute, all other fuels are better than nuclear power,
considering the risk of accidents which will bring disaster to
environment from nuclear power.
[RW] - Is the bridging fuel alternative renewable or recyclable?
If yes and the datum is not, 1. If not and the datum is not OR if so
and the datum is also, 0. If not and the datum is, -1. Among all the
fuels here in Table 1, only biomass (BM) is renewable, and others are
not, thus BM gets „1‟ and others get „0‟.
[RTW] - Does the bridging fuel alternative produce toxic waste
or utilize toxic materials? If yes and the datum does not, -1. If not
and the does not OR if so and the datum does as well, 0. If not and
the datum does, 1. Since the possible leaking or waste from nuclear
power station is much more toxic than other fuels in Table 1, all other
fuels get „1‟ with regard to this attribute.
[LCC] - The lifecycle cost refers to all costs involved with the
harvesting (time, labor, and technology), any safety costs, the support
costs, transporting costs, etc., all the way to disposal costs. Will the
bridging fuel alternative cost less than the datum over their lifecy-
cles? If so, 1. If not, -1. If they will be about the same, 0. Consider-
ing the significant cost of money and strict requirement of technology
and time it takes to build qualified nuclear power station to generate
power, and relatively lower cost for other bridging fuels, all other
bridging fuels get „1‟ with regard to this attribute.
[CPP] - This focuses solely on the cost to produce a kilowatt
hour of electricity. If this price is greater than the datum, -1. If this
price is the same as the datum, 0. If this price is less than the datum,
1. As clarified for LCC, the high lifecycle cost of nuclear makes the
cost per kilowatt hour of electricity from nuclear also higher than
other fuels compared here. Thus other fuels get „1‟ here.
[RDFO] - Does the bridging fuel alternative utilize or have the
potential to utilize only domestic product? If the bridging fuel
alternative does and the datum does not, 1. If the bridging fuel does
not and the datum does, -1. Else, 0.
[DGDC] - Is the bridging fuel alternative of a form that it can be
transported before being converted to electricity? If the bridging fuel
alternative is and the datum is not, 1. If the bridging fuel is not and
the datum is, -1. Else, 0. Among the fuels in Table 1, only oil and
natural gas can be easily transported, thus these two alternatives get
„1‟ while others get „0‟.
[QL] - Will the bridging fuel alternative contribute to or create
poor health in individuals of the population? If the bridging fuel will
and the datum does not, -1. If the bridging fuel will not and the
datum will, 1. Else, 0. Nuclear power is related to possible negative
effect on living environment thus threatening the health of
individuals, while other fuels in the table only result in extra carbon
dioxide, which is not a threat to human health, thus all other
alternatives get „1‟.
[ADF] - Is the bridging fuel alternative available for personal
and commercial use? Alternatively, does it provide fuel or energy to
the consumer? If the bridging fuel is available for personal or
commercial use and the datum is not, 1. If the bridging fuel is not
available for personal or commercial use and the datum is, -1. Else,
0.
[DR] - Does the bridging fuel alternative once converted to
energy/electricity have a delay in delivery or is it practically available
at all times? If it is always available and the datum is not, 1. If it is
not always available and the datum is, -1. Else, 0.
[EC] - Will the bridging fuel alternative allow the consumer to
participate and compete in the G3 world? If the bridging fuel will
and the datum will not, 1. If the bridging fuel will not and the datum
will, -1. Else, 0. It requires large cost and high technology for
extracting energy for utility from oil, natural gas, coal and nuclear
power, thus these alternatives hardly allow individuals to participate
in energy generation. Biomass especially requires specific technology
that is not broadly developed, which even is more difficult for
individuals to participate in. Thus alternatives all get „0‟ and BM get
„-1‟.
[SC] - How reliably can the bridging fuel alternative be sourced
or are there issues with personal safety or national security? If there
are these issues with the bridging fuel alternative and none with the
datum, -1. If these issues do not exist with the bridging fuel but do
with the datum, 1. Else, 0. Considering the national security
regarding sourcing, alternatives that can be supplied sufficiently
within the nation is considered good. Dependent of oil sourcing is
related to oil monopoly and potential risk of shortage, thus it gets -1.
[SD] - Is the bridging fuel alternative able to be scaled
appropriately to meet demands at peak and downtimes? If so, and the
8 Copyright © 2012 by ASME
datum is not, 1. If not and that datum can, -1. Else, 0. All other
alternatives in the table are better in the ability to immediate scaling
than nuclear power, due to the nature and technology limitation that
nuclear power is generated.
[V] - Does the bridging fuel alternative have the ability to meet
the requirements of various fields? If so and the datum does not, 1.
If not and the datum does, -1. Else, 0. The infrastructure and facility
makes oil and natural gas can be adapted to more diverse fields than
the other three alternatives.
[ET] - Is the bridging fuel alternative in its unconverted form
(i.e., not yet converted to electricity) easily transportable or set up in
such a way that it does not need to be transportable? If so and the
datum is not, 1. If not and the datum is, -1. Else, 0.
[EFF] - When compared to the datum, does the bridging fuel
alternative produce more or less energy per a constant given amount
of fuel? If more, 1. If less, -1. If the same, 0. Regarding the
efficiency of power generating, nuclear power has a significant
disadvantage considering the consuming of substance in the process
of power generating, thus others get 1.
2.2.4 STEP IV-Preliminary Selection Process In Scenario 1, the datum is nuclear power (NF), meaning the
remainder of the alternatives are compared directly to and only to it.
The same carries through for the later scenarios for their respective
datum. The lower the value of the rank, the "better" is the choice.
As an example of preliminary selection process, one table is shown
below.
Table 1.1 PRELIMINARY SELECTION, SCENARIO 1
Table 1.2 PRELIMINARY SELECTION, SCENARIO 2
Table 1.3 PRELIMINARY SELECTION, SCENARIO 3
OIL NG COAL NF BM
ENVIRONMENTAL
EEE 1 1 1 0 1
RW 0 0 0 0 1
RTW 1 1 1 0 1
Score 2 2 2 0 3
Normalized score 2/3 2/3 2/3 0 1
ECONOMICAL
LCC 1 1 1 0 1
CPP 1 1 1 0 1
DGDC 1 1 0 0 0
Score 3 3 2 0 2
Normalized score 1 1 2/3 0 2/3
SOCIAL
QL 1 1 1 0 1
EC 0 0 0 0 -1
Score 1 1 1 0 0
Normalized score 1 1 1 0 0
ENGINEERING
SC -1 1 0 0 1
SD 1 1 1 0 1
V 1 1 0 0 0
EFF 1 1 1 0 1
Score 2 4 2 0 3
Normalized score 1/2 1 1/2 0 3/4
OVERALL SCORES AND RANKS
Sum of normalized scores 3.167 3.667 2.833 0.000 2.417
Ranks 2 1 3 5 4
ATTRIBUTESALTERNATIVES
SCENARIO 1 DATUM: NF
OIL NG COAL NF BM
ENVIRONMENTAL
EEE -1 -1 -1 -1 0
RW -1 -1 -1 -1 0
RTW -1 -1 -1 -1 0
Score -3 -3 -3 -3 0
Normalized score 0 0 0 0 1
ECONOMICAL
LCC 1 1 1 -1 0
CPP 1 1 1 0 0
DGDC 1 1 1 0 0
Score 3 3 3 -1 0
Normalized score 1 1 1 0 1/4
SOCIAL
QL -1 -1 -1 -1 0
EC 1 1 1 -1 0
Score 0 0 0 -2 0
Normalized score 1 1 1 0 1
ENGINEERING
SC -1 1 1 0 0
SD 0 0 0 -1 0
V 1 1 1 0 0
EFF -1 -1 0 -1 0
Score -1 1 2 -2 0
Normalized score 1/4 3/4 1 0 1/2
OVERALL SCORES AND RANKS
Sum of normalized scores 2.250 2.750 3 0 2.750
Ranks 4 2 1 5 2
SCENARIO 2 DATUM: BM
ATTRIBUTES ALTERNATIVES
OIL NG COAL NF BM
ENVIRONMENTAL
EEE 1 1 0 -1 1
RW 0 0 0 0 1
RTW 1 1 0 -1 1
Score 2 2 0 -2 3
Normalized score 4/5 4/5 2/5 0 1
ECONOMICAL
LCC 1 1 0 -1 -1
CPP -1 -1 0 -1 -1
DGDC 1 1 0 0 0
Score 1 1 0 -2 -2
Normalized score 1 1 2/3 0 0
SOCIAL
QL 1 1 0 -1 1
EC 0 0 0 0 -1
Score 1 1 0 -1 0
Normalized score 1 1 1/2 0 1/2
ENGINEERING
SC -1 0 0 -1 1
SD 1 1 0 0 0
V 1 1 0 -1 -1
EFF 1 1 0 -1 0
Score 2 3 0 -3 0
Normalized score 5/6 1 1/2 0 1/2
OVERALL SCORES AND RANKS
Sum of normalized scores 3.633 3.800 2.067 0 2
Ranks 2 1 3 5 4
SCENARIO 3 DATUM: COAL
ATTRIBUTES ALTERNATIVES
9 Copyright © 2012 by ASME
Table 1.4 PRELIMINARY SELECTION, SCENARIO 4
Table 1.5 PRELIMINARY SELECTION, SCENARIO 5
2.2.5 STEP V-Assigning Weights and Normalizing
A table is created where, for a particular scenario, one of the
generalized criteria is considered more important than the others. In
scenario one, that is Environmental; in scenario two it is Economical,
and so on. In Scenario 5, a staggered weighting is given rather than a
single, overriding criteria.
Table 2 WEIGHT OF THE ATTRIBUTES
In the second table we have determined the total normalized
score for each alternative and, further, for each scenario. The chart is
aligned so as to act as an extension of the above chart. That is, the
column just to the right of the alternatives is for Scenario 1 and the
final column below is for Scenario 5. The equation to determine the
different scores is given in a general form in the table as well.
TABLE 3 TOTAL SCORE
2.3 Selection DSP
After preliminary selection, the most-likely-to-succeed alterna-
tives have been identified by using soft information. Then a selection
Decision Support Problem to identify the best concept is to be solved.
At this stage, both soft and hard information is involved, and the
preference for alternatives is considered with regard to different
emphasis on attributes for each alternative respectively.
The selection process is divided in several steps as shown in
Figure 4 for ease of carrying out the process.
2.3.1 Different Steps of Selection DSP STEP I
Table 4 is produced to introduce the candidates of fuel sources
Table 4 CANDIDATES OF FUEL SOURCES
STEP II
OIL NG COAL NF BM
ENVIRONMENTAL
EEE -1 0 -1 -1 1
RW 0 0 0 0 1
RTW -1 0 -1 0 1
Score -2 0 -2 -1 3
Normalized score 0 0.4 0 0.2 1
ECONOMICAL
LCC -1 0 -1 -1 -1
CPP -1 0 1 -1 -1
DGDC 0 0 -1 -1 -1
Score -2 0 -1 -3 -3
Normalized score 1/3 1 2/3 0 0
SOCIAL
QL -1 0 -1 -1 1
EC 0 0 0 0 -1
Score -1 0 -1 -1 0
Normalized score 0 1 0 0 1
ENGINEERING
SC -1 0 0 -1 0
SD 0 0 0 -1 -1
V 0 0 -1 -1 -1
EFF 0 0 1 -1 -1
Score -1 0 0 -4 -3
Normalized score 3/4 1 1 0 1/4
OVERALL SCORES AND RANKS
Sum of normalized scores 1.083 3.400 1.667 0.200 2.250
Ranks 4 1 3 5 2
SCENARIO 4 DATUM: NG
ATTRIBUTES ALTERNATIVES
OIL NG COAL NF BM
ENVIRONMENTAL
EEE 0 1 -1 -1 1
RW 0 0 0 0 1
RTW 0 1 -1 -1 1
Score 0 2 -2 -2 3
Normalized score 2/5 4/5 0 0 1
ECONOMICAL
LCC 0 1 -1 -1 -1
CPP 0 1 1 -1 -1
DGDC 0 0 1 -1 -1
Score 0 2 1 -3 -3
Normalized score 3/5 1 4/5 0 0
SOCIAL
QL 0 1 -1 -1 1
EC 0 0 0 0 -1
Score 0 1 -1 -1 0
Normalized score 1/2 1 0 0 1/2
ENGINEERING
SC 0 1 1 -1 1
SD 0 1 0 -1 -1
V 0 0 -1 -1 -1
EFF 0 -1 1 -1 -1
Score 0 1 1 -4 -2
Normalized score 4/5 1 1 0 2/5
OVERALL SCORES AND RANKS
Sum of normalized scores 2.300 3.800 1.800 0 1.900
Ranks 2 1 4 5 3
SCENARIO 5 DATUM: OIL
ATTRIBUTES ALTERNATIVES
One Two Three Four Five
Environmental 0.4 0.2 0.2 0.2 0.2
Economical 0.2 0.4 0.2 0.2 0.3
Social 0.2 0.2 0.4 0.2 0.2
Engineering 0.2 0.2 0.2 0.4 0.3
Generalized
Criteria
Scenario Number
Alternative
Oil 0.767 0.650 0.927 0.367 0.600
NG 0.867 0.750 0.960 0.880 0.960
Coal 0.700 0.800 0.513 0.533 0.540
Nuclear 0.000 0.000 0.000 0.040 0.000
Biomass 0.683 0.600 0.500 0.475 0.420
Σ[(Scorenormalized)x(Weight)]
Name Acronym Description
Alternative
1Nuclear NF Splitting Uranium Atom
Alternative
2Petroleum OIL Crude Oil and Hydrocarbons
Alternative
3Coal COAL Mostly Carbon
Alternative
4Natural Gas NG Mostly Methane
Alternative
5Biomass BM Biological Matter
10 Copyright © 2012 by ASME
In Table 5, the relative importance of the attributes is shown
based on giving more weights in each of the regions of socio,
economics and ecology. For example, to show more weight on socio-
cultural we have given highest priority on Attributes 11 and 12.
Similarly when economy or ecology is most important then highest
priority is given to Attributes 4, 5 or Attributes 1, 3 respectively. The
cumulative sum of the relative importance is equal to 1.
Table 5 ASSIGNING RELATIVE IMPORTANCE TO THE ATTRIBUTES
Table 6 SCALES
STEP III
The scale in Table 6 is used for all attributes except for AT#5
and AT#12. The scales for those two attributes are given below,
respectively.
Table 7 SCALES FOR AT#5
Table 8 SCALES FOR AT#12
Table 9 ATTRIBUTE RATINGS
STEP IV
Table 10 NORMALIZED ATTRIBUTE RATINGS
STEP V
The data for relative importance of the attributes are taken from the
column weighted ecology Table 5.
Attribute
(AT)Description
Acro
nym
Relative
Importance
Weigted
Socio
Relative
Importance
Weigted
Economy
Relative
Importance
Weigted
Ecology
#1
Effects on environmental elements
(soil, water, air, etc.) Ordinal
converted to interval scale. Range of
rating values: 0-5. Larger number
preference.
EEE 0.0769 0.0128 0.1538
#2
Renewability or Recyclability. Ordinal
converted to interval scale. Range of
rating values: 0-5. Larger number
preference.
RW 0.0513 0.0256 0.0769
#3
Reduction of toxic waste. Ordinal
converted to interval scale. Range of
rating values: 0-5. Large number
preference.
RTW 0.0385 0.0385 0.1410
#4
Lifecycle costs. Ordinal converted to
interval scale. Range of rating values:
0-5. Large number preference.
LCC 0.0641 0.1538 0.1282
#5
Cost per kilowatt hour to produce.
Ordinal converted to interval scale.
Range of rating values: 0-3. Large
number preference.
CPP 0.0128 0.1410 0.0513
#6
Meet the demand of geographically
distributed customers. Ordinal
converted interval scale. Range of
rating values: 0-5. Large number
preference.
DGDC 0.0897 0.0897 0.0897
#7
Maintains or improves the quality of
life. Ordinal converted interval scale.
Range of rating values: 0-5. Large
number preference.
QL 0.1026 0.1026 0.1026
#8
Empowers customers. Ordinal
converted interval scale. Range of
rating values: 0-5. Large number
preference.
EC 0.1282 0.1282 0.0128
#9
Secure energy source with respect to
supply, reduce long-term price
volatility, and the capacityto promote a
more resilient electricity system.
Ordinal converted interval scale.
Range of rating values: 0-5. Large
number preference.
SC 0.0256 0.1154 0.1154
#10
Ability to scale with demand. Ordinal
converted interval scale. Range of
rating values: 0-5. Large number
preference.
SD 0.1538 0.0641 0.0641
#11
Versatile. Ordinal converted interval
scale. Range of rating values: 0-5.
Large number preference.
V 0.1410 0.0769 0.0256
#12
Produce energy efficiently. Ordinal
converted to interval. Range of rating
values: 0-2. Large number preference
EFF 0.1154 0.0513 0.0385
Interval Ordinal
0 Unacceptable 0-20% chance of success in meeting the attribute; major revisions required for improvements
3 Very Good 60-80% probability of meeting a fair amount of the attribute
40-60% probability of meeting the attribute
1 Below Average 20-40% probability of meeting the attribute
2 Average
RatingsDescription
5, 4 Excellent Over 80% probability of meeting or exceeding the attribute
Ratings
Ratio
3 Very Economical (< $0.09/kWh)
2 Affordable to majority ( $0.09 ≤ C ≤ $0.16/kWh)
1 Affordable to few ( $0.17 ≤ C ≤ $0.23/kWh)
0 Costly (> $0.23/kWh)
Description
Ratings
Ratio
2 Highly Efficient (>40% efficient)
1 Moderately Efficient (20-40% efficient)
0 Poor Efficiency (<20% efficient)
Description
Alternatives AT#1 AT#2 AT#3 AT#4 AT#5 AT#6 AT#7 AT#8 AT#9 AT#10 AT#11 AT#12
NF 0 0 0 0 0 1 0 0 3 2 1 0
OIL 2 0 2 2 1 3 3 3 1 5 5 3
COAL 1 0 1 5 3 3 2 3 3 3 3 3
NG 3 0 3 2 2 3 4 2 3 2 3 3
BM 3 3 2 2 0 1 2 2 3 1 1 1
Scale O-I O-I O-I O-I O-I O-I O-I O-I O-I O-I O-I O-I
Range 0-5 0-5 0-5 0-5 0-3 0-5 0-5 0-5 0-5 0-5 0-5 0-2
Units None None None None None None None None None None None None
AlternativesAT#1 AT#2 AT#3 AT#4 AT#5 AT#6 AT#7 AT#8 AT#9 AT#10AT#11AT#12
NF 0 0 0 0 0 0 0 0 1.000 0.25 0 0
OIL 0.667 0 0.667 0.400 0.333 1.000 0.750 1 0 1.000 1 1.000
COAL 0.333 0 0.333 1 1.000 1.000 0.500 1.000 1.000 0.500 0.500 1.000
NG 1 0 1 0.4 0.67 1 1 0.667 1 0.25 0.500 1.000
BM 1 1 0.67 0.400 0.000 0 0.5 0.667 1.000 0.000 0.000 0.333
11 Copyright © 2012 by ASME
Table 11 MERIT FUNCTION VALUES SYNTHESIS
STEP VI
Table 12 MERIT FUNCTION VALUES AND FINAL RANKING (WITH HIGHER NUMBER PREFERENCE)
2.4 Sensitivity Analysis Table 13 is produced by changing the weights from one region
to another and it can be observed that changing the weight drastically
change the result. In Table 13a, oil comes out to be the bridging fuel
when the weight is on Socio- cultural and the runner up is natural gas
which is closely followed by coal. Thus a sensitivity analysis is done
by increasing and decreasing the relative importances of the attributes
but still oil come out to be the winner when the weight is on socio-
cultural. Similarly in Table 13 b and c, coal comes as winner when
weight is on economy and natural gas comes out to be the winner
when ecology is given more weight. Even after sensitivity analysis
each winner stands on their positions firmly.
Table 13 SENSITIVITY ANALYSIS a) Weight on Socio-cultural
b) Weight on Economy
c) Weight on Ecology
3 RESULTS
The result of Preliminary Selection DSP and Selection DSP is
given in the following sections
3.1 Preliminary Selection The graph below is produced based on the two Tables 2 and 3.
Table 2 is a weight table where, for a particular scenario, one of the
generalized criteria is considered more important than the others. In
scenario one, that is Environmental; in scenario two it is Economical,
and so on. In Scenario 5, a staggered weighting is given rather than a
single, overriding criteria.
Figure 5 GRAPHICAL REPRESENTATIONS OF PRELIMI-NARY SELECTION SCORE
In Table 3, we determined the total normalized score for each
alternative and, further, for each scenario. The equation to determine
the different scores is given in a general form in the table as well.
From the synthesis of the five preliminary scenarios, natural gas
was determined to be the bridging fuel with the most potential to
succeed. From Figure 5, it can be seen that natural gas is at the top of
the rankings in four of the five scenarios. The runner-up is coal
which remained fairly consistent through each scenario and is the top
choice in Scenario 2 when natural gas came in second.
An interesting result is illustrated in Figure 5, nuclear power is
deemed the most likely to fail as a bridging fuel. We realize that this
is not a section-ending selection method and that a true selection
process is required to determine the best option for a bridging fuel.
3.2 Selection Process
In selection process we considered all of the possible scenarios
by shifting weight from one region to another and came to the
understanding that shifting weights changes the outcome also. In
Table 13a it is seen that oil comes as winner when weight is more on
the socio-cultural. Similarly in Table 13b and Table 13c, coal comes
as winner when weight is more on economy and natural gas comes as
Alternatives AT#1 AT#2 AT#3 AT#4AT#5AT#6AT#7 AT#8 AT#9 AT#10AT#11AT#12
Relative
Importance:0.15385 0.07692 0.141026 0.13 0.05 0.09 0.1 0.01 0.12 0.06 0.03 0.04
NF 0 0 0 0 0 0 0 0 0.12 0.02 0 0
OIL 0.10256 0 0.094017 0.05 0.02 0.09 0.08 0.01 0 0.06 0.03 0.04
COAL 0.05128 0 0.047009 0.13 0.05 0.09 0.05 0.01 0.12 0.03 0.01 0.04
NG 0.15385 0 0.141026 0.05 0.03 0.09 0.1 0.01 0.12 0.02 0.01 0.04
BM 0.15385 0.07692 0.094017 0.05 0 0 0.05 0.01 0.12 0 0 0.01
NF 0.1314 0.1380 0.1248
OIL 0.5726 0.6013 0.5440
COAL 0.6303 0.6619 0.5988
NG 0.7639 0.8021 0.7257
BM 0.5641 0.5923 0.5359
Merit
Function
Value
AlternativesIncrease
5%
Decrease
5%
Alternatives
Merit
Function
Value
AT1 -5%
AT8 +5%
AT3 -5%
AT12 +5%
AT4 -5%
AT5 +5%
AT9 -5%
AT10 +5%
AT7 -5%
AT2 +5%
NF 0.0641 0.0641 0.0641 0.0641 0.0647 0.0641
OIL 0.8120 0.8158 0.8165 0.8109 0.8197 0.8081
COAL 0.6731 0.6782 0.6782 0.6705 0.6756 0.6705
NG 0.6774 0.6778 0.6812 0.6765 0.6780 0.6722
BM 0.3803 0.3808 0.3810 0.3791 0.3791 0.3803
Alternatives
Merit
Function
Value
AT1 -5%
AT8 +5%
AT3 -5%
AT12 +5%
AT4 -5%
AT5 +5%
AT9 -5%
AT10 +5%
AT7 -5%
AT2 +5%
NF 0.1314 0.1314 0.1314 0.1314 0.1264 0.1314
OIL 0.6299 0.6359 0.6312 0.6292 0.6331 0.6261
COAL 0.8184 0.8246 0.8203 0.8177 0.8142 0.8158
NG 0.7058 0.7094 0.7064 0.7074 0.7008 0.7006
BM 0.3949 0.3985 0.3944 0.3918 0.3891 0.3936
Alternatives
Merit
Function
Value
AT1 -5%
AT8 +5%
AT3 -5%
AT12 +5%
AT4 -5%
AT5 +5%
AT9 -5%
AT10 +5%
AT7 -5%
AT2 +5%
NF 0.1314 0.1314 0.1314 0.1314 0.1264 0.1314
OIL 0.5726 0.5682 0.5699 0.5709 0.5759 0.5688
COAL 0.6303 0.6284 0.6299 0.6265 0.6262 0.6278
NG 0.7639 0.7566 0.7588 0.7630 0.7589 0.7588
BM 0.5641 0.5568 0.5600 0.5615 0.5583 0.5654
12 Copyright © 2012 by ASME
winner when weight is more on ecology respectively. So it can be
inferred form Table 13 that which fuel is to be selected based on
which region we want to prioritize.
4 DILEMMA MANAGEMENT In the last sections, the dilemmas associated to critical regions to be
managed are presented, and a numerical approach for selecting a
bridging fuel is shown. In this section, we explain and discuss how
the approach for selecting the bridging fuel effectively manages the
dilemmas we are faced with.
4.1 Effectiveness of the Approach In this subsection, it is explained how our approach for selecting
a bridging fuel effectively result in a balanced satisfaction of our
different goals with different relative importance.
The objective of the dilemma management problem is: To
find the alternative that is satisficing to our conflicting objectives
with our different emphasis. The alternative should be selected
according to the relative importance of the requirements as well
as the ability of the alternatives to satisfy the requirements. The
approach should be one such that alternative that has more
strength against the requirement that we put more emphasis on
has more likelihood to win. In Section 1.1, we described the
concept of dilemma and used the method shown in Ref. [3] to
identify dilemmas.
In Section 2, we find by preliminary selection DSP that natural
gas is the bridging fuel In preliminary selection, the general
performance of the alternative bridging fuels in each region is
considered. The way that the scores for each fuel are calculated is
shown on the top of Table 2. The nature of this calculating method
accounts for both the relative importance of the requirements in
sustainability prism and the performance of the alternative fuels in
each region.
In Table 2 the weights are shifted from one region to the other
and based on that total normalized score is shown in Table 3. From
Table 2 and 3, it can be seen that when the weight is on
environmental then the total score of natural gas is 0.867 and it is the
highest among other all other alternatives. Similarly in other
scenarios except economy, natural gas is the highest scorer 0.96, 0.88
and 0.96 when the weights are in social, engineering, economy and
engineering combined respectively. Only when the weight is on
economy, coal comes up as the bridging fuel by scoring 0.8 and
natural gas as runner up by scoring 0.75 which is slightly below than
that of coal.
In selection DSP different attributes are preferred over other ac-
cording to the weight put on the regions of socio-cultural, economy
and ecology. At this stage, by calculating the merit function it is
similar that alternative with more strength on requirement of more
emphasis are likely to have higher merit function value, and have
higher likelihood to win.
For example from Table 10 and Table 11 we see that NG has the
highest merit function value, this attributes to the fact that NG is
rated one of the highest among all the alternatives for attribute #1, #3
and #7, and these three attributes are the ones that have highest rela-
tive importance. At the same time, Oil has quite high score for attrib-
ute #11, but it doesn‟t get high merit function value, because attribute
#11 does not have high relative importance compared to others.
Now we change the relative importance of the requirements
which is to change weightages, When the weight is on socio-cultural
then Attribute 10 and Attribute 11 in Table 5 get the highest relative
importance 0.1538 and 0.141 respectively and as a result from Table
13a it can be seen that oil scores 0.812 which is the highest among
all. Attribute 10 refers to how much the fuel has the potential to meet
the demand scale of society and Attribute 11 refers to how much the
fuel is versatile, i.e., how wide is the fuel‟s applicability and
acceptance to society. Similarly in Table 5 when the weight is shifted
to economy and ecology, the relative importance of the attributes is
also shifted to Attribute 4, 5 and Attribute 1, 3 respectively. And in
the Table 13b and Table 13c, it can be seen that coal scores 0.8184
which is the highest and natural gas scores 0.7639 which is also the
highest respectively. A sensitivity analysis is done by increasing or
decreasing each of the relative importance of the attributes by 5
percent in Table 13 a, b and c to confirm the result. So, it is inferred
from different results from Table 13 a, b and c that oil should be the
bridging fuel when the socio-cultural is prioritized, coal should be the
bridging fuel when economy is prioritized and natural gas should be
the bridging fuel when ecology is prioritized.
Our focus is about selecting a bridging fuel which favors
sustainability system and hence natural gas is selected as bridging
fuel as it meets the ecology demands better than that of coal and oil.
4.2 How the Selected Bridging Fuel Manages the
Dilemmas In this section, we show how the bridging fuel, i.e., natural gas man-
ages each of the dilemmas listed previously by achieving tradeoffs
between conflicting objectives.
Ecology - Economic
1 The fuel should be such that it is environmental friendly and has
low lifecycle cost.
Here we have issues of being environmentally friendly and at
the same time low life cycle cost and as we are putting more weight
on ecology so natural gas manages the dilemma better than that of oil
and coal, as natural gas is more environmental friendly
2 The need to reduce the toxic waste of the fuel over the need to
decrease lifecycle cost.
Here the issues are about reducing toxic waste and also being
low lifecycle cost, and natural gas has less toxic waste than that of
coal, oil, biomass and nuclear fuel thus natural gas is better at manag-
ing this dilemma as well than any other sources
3 The need of the fuel to be renewable and also to be capable of
meeting huge public demand.
Here the issues are about being renewable and also being capa-
ble of meeting the public demand. Biomass is the only fuel source
that is renewable but it cannot meet the huge demands as good as
natural gas, coal and oil does
4 The need of the fuel to be environmentally friendly (Renewable
energy, like wind energy) over the need of the fuel to meet the
demand of geographically distributed customers.
Here one issue is about renewability and thus biomass is the best
option but the other issue is about meeting the need of geographically
distributed customers where oil, gas and coal are better than that of
biomass.
5 The need to consume less in order to preserve ecological system
over the need to improve the quality of life
Here issues of preserving ecological system and improving the
quality of life are mentioned and natural gas is better at managing this
dilemma than other because it has less carbon foot print than oil and
coal
13 Copyright © 2012 by ASME
6 The need of the fuel to meet the demand of public over the need
to reduce dependence on foreign oil.
Here issues about meeting public demand and also security
dependency. Only natural gas and coal can manage this dilemma as
oil increases security dependency though it has capability to meet
public demand and on the other hand biomass do not increase secu-
rity dependency but it lacks the capability to meet demands
7 The need to transit to new energy infrastructure based on domes-
tic/reliable fuel source (considering national security) over the
cost of transition.
Here the issues are about transiting to a new energy infrastruc-
ture which decreases security dependency and at the same time
considering the cost of it. Oil fails to manage this dilemma as it
increases security dependency but coal, natural gas and biomass all
have a fair chance
In the end if we combine the issues of all the regions i.e.,
ecological, social and economic together then the dilemmas is about a
need of a fuel which is environment friendly, decrease security
dependency, low life cycle cost and able to meet the public demand
at the same time. Oil does not manage the dilemma as it increases
security dependency and carbon foot print. Coal does not manage this
dilemma as it is not environment friendly though it is cheap and able
to meet the demand. Similarly, Biomass does not manage the dilem-
mas in spite being renewable because it is not capable of meeting
huge demand. So, the only other option left is natural gas and it has
the capability of managing the dilemmas better than any other and is
the bridging fuel.
From table 2 and table 3 we see, changing of weights of the
requirement regions lead to changing of winning bridging fuel. In
table 2 Scenario one, where the ecological requirements have the
highest weight, NG has the highest score, because NG has highest
score for the requirements related to environmental-friendliness. In
table 2 Scenario two, where economical requirements are dominant,
Coal has the highest score largely due to its high score on economical
criteria.
In Selection, after some good alternatives have stood out, we go with
more information to identify the relative importance of each require-
ment, instead of general requirements in each region in the
sustainability prism, and we identify the relative strength of each
alternative over each requirement respectively. At this stage, by
calculating the merit function it is similar that alternative with more
strength on requirement of more emphasis are likely to have higher
merit function value, and have higher likelihood to win.
5. LEARNING STATEMENTS By taking the course Designing for Open Innovation, we
Salman and Minting have learned many lessons. We have leveraged
our work from AME5740 in this paper to present an approach for
selecting a bridging fuel and an approach about how to manage
dilemmas. We have faced a lot of challenges in connecting the dots
that were presented in the course and coming up with whitespaces to
write this paper. Some challenges that we faced in writing this paper
is as follows-
We are challenged when we are facing a quite open question to
answer, and to search for an approach to answer it.
We are challenged to make connections of part of our work done
in the course Design for Open Innovation to abstract it to
another work.
We are challenged to make associated creation based on our
existing knowledge and methods
We are challenged to properly organize our knowledge in a
connected way and convey our ideas so others can understand.
is summarizing the work of the whole
The classes of the Course AME5740 continued only for one
semester but the lessons we, Salman and Minting, learned from this
course has and will continue to have effect on us for the rest of our
life. So, we present some learning statements that we find most
valuable. The course has been offered in both individual and in group
setting so the learning statements are divided into Team Learning and
Individual Learning. This section concludes our learning in the
context of this course.
Team Learning
We (Salman and Minting) learned where to go when faced of a
quite open question. We learned to speculate on the current and
future to identify holes and make evaluations with scaffolding.
In this way continue learning takes place.
We (Salman and Minting) learned how to use different domains
of knowledge in Bloom‟s Taxonomy to reflect on the existing
knowledge and on this basis make associated creation of new
knowledge.
We (Salman and Minting) learned that Learning Organization
works smoothly and becomes very powerful in achieving things
when everyone knows everyone‟s strength and weakness and
this can be done by sharing background, competencies and
learning objects
We (Salman and Minting) learned through working in a
collaborative environment that how people have different
strength and pay attention to different parts of a same thing, thus
distribution of task should be done according to the mental
model of individuals.
We (Salman and Minting) learned that Learning organization‟s
success depend on each and every one of the members through
what does not work out in our learning organization.
We (Salman and Minting) learned that A strong team contract is
important and it can be done by explicitly specifying the amount
of work each member should do, along with a hard dead line.
We (Salman and Minting) learned that While working in a
culturally diverse group with people of different backgrounds,
then ideas from different perspectives rather than a single is put
on the table and a fusion of those ideas are the one that are most
likely to succeed.
We (Salman and Minting) become aware of how to deal with
dilemmas that we are facing with, to minimize loss in the con-
text of a complex ecology-social-economy system in a G3
world.
Individual Learning
I (Salman) learned that learning is a conscious activity and it
starts when someone knows what he does not know and has a
desire to learn.
I (Salman) learned that the advent of G3 has made the world flat
because of the emergence of cheap computer and cheap internet
connection.
I (Salman) learned that the world seldom provides solution to
problems; it provides dilemmas i.e., offering two possibilities
where neither of them is feasible.
I (Salman) learned that environment, society and economy
dilemmas should be considered while designing a product for
sustainability and technology can help us to achieve it.
I (Salman) learned speculating the future and finding white
spaces is very important
I (Salman) learned self-evaluation and continuous improvement
is necessary to be successful.
14 Copyright © 2012 by ASME
I (Minting) learned how powerful a sharing-to-gain environment
can be if people work in a learning organization to achieve
things.
I (Minting) become aware of the challenges that are possible to
come when working in G3 world and have started thinking on
how to improve working in it. By working with people from
different culture and education background with different gen-
der, and even from geographically far away,
I (Minting) learned how continuous learning works. I learned to
take on responsibility of my own learning by starting from
identifying what to learn and on this bases to find out how to
learn by using different levels of cognitive learning in Bloom‟s
Taxonomy.
Through these student learning statements, the instructors
(Mistree and Panchal) able to gain confidence in their
hypothesis that using the notion of dilemmas as the core of the
graduate level design course is helpful in getting the students
to think in terms of broader system-level challenges necessary
for the 12st century rather than merely focusing on specific
methods and tools for designing technical systems.
6 CLOSURE In this paper we have drawn a boundary for finding the
dilemmas among ecological, social and economic regions
associated with fuel sources that power the current world and
have presented an approach on how to select bridging fuel. We
have also developed an approach on how to manage dilemmas
to achieve sustainability. In the dilemma management process
we have identified the crucial steps that are needed to analyze
and then synthesize a decision on how to manage dilemmas.
In the selection DSP process, we have focused on the ap-
proach of selecting a bridging fuel rather than finding the
bridging fuel itself thus the result obtained may not necessarily
reflect the best bridging fuel. The final decisions made in the
selection approaches are based on intuition after reflecting
corresponding hard information. However, we believe that
using more hard information and reflection, a bridging fuel
can be selected by using the approach presented in the paper.
The effectiveness of dilemma managing of this selection DSP
technique comes from its nature that requirements with differ-
ent preference and bridging fuels with different strength and
weakness against different criteria are considered. It is also
explained that how the result of the selection in this paper –
natural gas, with its characteristics, verifies that this approach
is effective.
This paper is part of the work done through this course in
a learning organization. The four papers in this series demon-
strates that we are in a bigger learning organization consisting
of sharing-to-gain between different inter-university that is
able to make comprehensive achievement At the same time,
each group is also a learning organization in which we learn
together and achieve things.
Our learning throughout the course as both learning
organization and individual are summarized in the end of the
paper. Here how the core competencies proposed in Refs. 1
and 2 are developed in the part of work that is associated to
this paper is explained.
Throughout the work in the Learning Organization, we
have gained the ability to identify the competencies and meta-
competencies we need to develop to be successful at creating
value in a culturally diverse, distributed engineering world.
This determines where we go in learning. By using different
domains of knowledge in the Bloom‟s Taxonomy to reflect on
an approach to manage the dilemmas, we think a lot on the
most critical issues in the current world, and seek for the prob-
lems that will be faced now and in the near future. This helps
us to develop some of the competencies we proposed. The
thinking on the nature of the dilemmas and an approach of
managing the dilemmas proves that we have developed
competency to manage the dilemmas associated with complex
sustainable systems to a large extent. In this paper we come up
with an approach for the problem that we are newly faced with
by reflecting and associated creation of knowledge, and
learned to articulate it.
Comment: We have run out of time. We recognize that this
paper needs quite a bit of editorial work. If accepted we
commit to fixing the paper to meet the expected standards for
this conference. Farrokh Mistree and Jitesh Panchal
ACKNOWLEDGEMENTS This paper evolves from the core concept of Technology
Prism which was offered in the AME5740 Designing for Open
Innovation in Fall 2011. The Preliminary Selection and
Selection DSP were originally used by Team Gamma to select
the bridging fuel in partial completion of Assignment 4 and
Assignment 6. The Team Gamma consists of Isaac Burbank,
Ryan Drobny and Vignesh Venkat from WSU and Brian
Chapman and Andrew Kooiman form OU along with the first
two authors of this paper.
REFERENCES 1. Siddique, Z., Panchal, J.H., Schaefer, D., Allen, J.K. and
Mistree, F., 2012, "Competencies for Innovating in the 21st
Century," ASME International Conference on Design
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"Developing Competencies in the 21st Century Engineer,"
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IL. Paper Number: DETC2012-71153.
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Mistree, F., 2012, "Identifying Dilemmas Embodied in 21st
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