THE USE OF ACTIVITY-BASED COSTING, UNCERTAINTY, AND DISASSEMBLY ACTION CHARTS IN DEMANUFACTURE COST ASSESSMENTS

1995 ASME Advances in Design Automation Conference,
Boston, Massachusetts, Sept. 17-20, 1995.
THE USE OF ACTIVITY-BASED COSTING, UNCERTAINTY, AND
DISASSEMBLY ACTION CHARTS IN DEMANUFACTURE COST ASSESSMENTS
Bert Bras and Jan Emblemsvåg
The Systems Realization Laboratory
The George W. Woodruff School of Mechanical Engineering
Georgia Institute of Technology
Atlanta, Georgia 30332-0405
ABSTRACT
properties and requirements [1]. Some hurdles to developing
In this paper, the development of an Activity-based Cost
environmental impact and cost models are: a) there is a lack of
(ABC) model is presented for use in design for demanufacture
both hard test data and past experience, b) new and different
under the presence of uncertainty. Demanufacture is defined as
technologies are integrated with unknown effects, and c) designs
the process opposite to manufacturing involved in recycling
are incomplete and evolving at the stage where the largest
materials and product components after a product has been taken
reduction in environmental impact and cost can be made. In
back by a company. The crux in developing an ABC model is to
addition, the world’s environmental processing capabilities are
identify the activities that will be present in the demanufacturing
largely uncertain. Hence, the following two questions still remain
process of a product, and afterwards assign reliable cost drivers
largely unanswered:
and associated consumption intensities to the activities.
• What is the cost associated with pursuing environmentally
Uncertainty distributions are assigned to the numbers used in the
benign products and processes?
calculations, representing the inherent uncertainty in the model.
• Which aspects of both the product and process design have
The effect of the uncertainty on the cost and model behavior are
the largest influence on these costs?
found by employing a numerical simulation technique - the
In this paper, we present a method for developing cost models
Monte Carlo simulation technique. The additional use of
which aid designers in answering these and similar questions in
disassembly action charts allows the influence of the uncertainty
the context of designing for the life-cycle. The core of our method
to be traced through the cost model to specific demanufacture
is the combined use of Activity-Based Costing and uncertainty.
process and product design parameters.
Several costing approaches have appeared in the literature in the
context of designing environmentally benign products and
OUR FRAME OF REFERENCE
processes. However, when it comes to assessing costs to life-
The growing importance of including environmental issues in
cycle and ecological issues, Activity-Based Costing (ABC) is
design has amplified the impetus for companies to more formally
gaining ground rapidly on conventional costing systems [2-5] .
consider the entire life-cycle of a product, from cradle to grave or
Based on our review of relevant life-cycle costing approaches, we
even to reincarnation through recycling and reuse. A crucial
believe that emerging Activity-Based Costing approach has the
issue is the assessment of costs (or profit) related to pursuing
best potential for efficient and effective cost assessments in the
environmentally benign products and processes. We believe that
context of designing for the life-cycle [6] .
in order to provide efficient and effective decision support in
In this paper, we extend the work presented in [6] by including
life-cycle design, costing methods should: 1) Assess and trace
the following issues:
costs and revenues; 2) Handle both overhead and direct costs;
• The uncertainty associated with the information used in
3) Handle uncertainty; 4) Provide decision support for the
product cost assessments. In particular, we highlight the
process of designing.
modeling and propagation of these uncertainties through cost
Attempts to generate formal and systematic design approaches
models using commercially available software.
which include environmental considerations, as well as
• The capability to identify those process and product design
economical, mechanical and other design considerations run
aspects that contribute most to the cost using so-called action
aground when confronted with the need to quantify environmental
charts. This enables a design group to quickly spot the most
285

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cost inefficient parts of the design which allows the group to
are still largely unaddressed. Especially the uncertainty cannot
concentrate the redesign effort and improves design efficiency.
be ignored and should be included when one seeks to assess
The approach will be shown in the context of a subset of life-
costs associated with aspects of a multi-year product life-cycle
cycle design, i.e., design for demanufacture1 of telephones.
without much historical data.
ACTIVITY-BASED COSTING
INCLUDING UNCERTAINTY IN COST MODELS
Activity-Based Costing (ABC) has received its name because
Although a number of researchers outline methods for
of the focus on the activities performed in the realization of a
assessing and reducing environmental impact (e.g., [10] ), hardly
product. Costs are traced from activities to products, based on
any discussion is given to the accuracy of the data used and the
each product's consumption of such activities. Activity-Based
sensitivity of the outcome to variations in the inputs. Especially
Costing differs from conventional costing systems in two distinct
when dealing with ecological issues uncertainty must be
ways:
included due to a predominant lack of hard data.
1) In conventional costing systems, the assumption is made that
Uncertainty can be modeled in a variety of ways depending on
each unit of a given product consumes resources (e.g., energy,
what kind of uncertainty is to be modeled. Generally speaking,
material and direct labor), while in ABC the assumption is
we have the following possibilities:
made that products or services do not directly use up resources,
• We can model uncertainty based on historical data. This will
but consume activities. Hence, in ABC, the cost of a product
typically involve statistical analysis along the line of
equals the sum of the costs of all activities that must be
Gaussian Statistics.
performed in the realization of the product [4] .
• We can model uncertainty based on experience, qualified
2) Conventional cost systems are based on unit-level cost
guessing, etc. One way of doing this is by modeling the
drivers (these unit-level cost drivers are often referred to as
uncertainty analogous to fuzzy numbers, but solving the
allocation bases in conventional cost systems) of the product
model numerically rather than using fuzzy theory.
that are directly proportional to the number of units produced.
In design, and especially in original design, good historical data
Direct labor hours, machine hours and pounds of material are
are often impossible or difficult to get, thus methods based on
examples of such “unit-level allocation bases”. An ABC
Gaussian statistics will soon become inappropriate and even
system, on the other hand, uses cost drivers that can be at the
impossible to apply. Our method should therefore be designed
unit-level, batch-level, and/or product-level. Examples of
to deal with ‘fuzziness’. This means that we guess, for example
batch-level cost drivers are setup hours and number of setups.
based on experience, the type of distribution to use as well as the
Examples of product-level cost drivers are number of parts,
mean, the left deviation and the right deviation. The uncertainty
number of times ordered, and number of engineering charge
is simply modeled by assigning distributions to every number in
orders [7] .
the model for which there exists uncertainty.
Because of the assumption that a product uses activities and the
Given that the uncertainty is modeled in a cost model, we
allowance for batch and product level cost-drivers, it is generally
must determine the effect of these uncertainties on the cost. We
agreed that ABC systems are superior in modeling and tracking
have found it useful to use the Monte Carlo simulation technique
costs (see, e.g., [4, 7] ). Mostly noted is ABC’s capability to
to find the cost uncertainties resulting from our assumptions.
separate direct from indirect costs. In [4] it is noted that
Assumption cells
Forecast cells
“traditional cost systems systematically undercost small, low-
Statistical distribution
Chosen statistical
volume products and overcost large high-volume products”.
of a forecast cell
distribution for an
This is due to the inability to trace overhead costs correctly,
assumption cell
Trials
which in turn results from the use of only unit-level cost drivers
£ 4
and the focus on resource consumption. In depth discussions of
£ 12
£ 20
Results
ABC can be found in, e.g., [4, 5, 7-9] .
etc.
£ 10
£ 20
Propagation
We have chosen to use ABC because of the noted superiority
£ 35
through model
Direct Labor
etc.
+
in cost-tracing, separation of direct and indirect costs, higher
accuracy, and its capability to blend into the Activity-Based
£ 6
Product Cost = Direct Labor + Material
£ 8

Management (ABM) systems that more and more companies are
£ 15
etc.
employing (see, for example, [7] ). A motivating example for its
The forecast cell is shown here
as a histogram for simplicity
use in an environmental context can be found in [3] where it is
Material
described how Activity-Based Costing and environmental
aspects can be combined to give companies the ability to identify
FIGURE 1 – MONTE CARLO SIMULATION EXAMPLE
more accurately those plants and products which are driving up
This technique is a very simple, but powerful numerical
their environmental expenditures. However, it should be noted
approximation method that is simply based on performing a
that, although many have focused on ABC, the issues of
controlled and virtual experiment within a model. Although
a) how to provide efficient and effective decision support in
numerous different simulation methods exist, we have found it
design, and
b) how to best include the uncertainty involved
advantageous to employ a software called Crystal Ball® for this
purpose. It allows the definition of ‘assumption’ and ‘forecast’

cells in a spreadsheet computer model. The Crystal Ball
1
software adds into Microsoft Excel spreadsheet software, hence
Demanufacture: the process opposite to manufacturing involved in recycling
we talk about ‘cells’. A forecast cell can be looked upon as a
materials and product components after a product has been taken back by a
company.
response variable, while an assumption cell can be viewed as a
286

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source variable. Consider the example in Figure 1 where
product cost is modeled as a simple linear function of material
Distinguish:
Step 1 – Create an Activity

and direct labor cost. Based upon our “assumptions” w.r.t.
Hierarchy and Network
• Design Dependent Cost
material and direct labor, we want to “forecast” the associated
Drivers
• Design Independent Cost
product cost. In each assumption cell, an uncertainty
Drivers
Step 2 - Identify and Order all
distribution is defined as is appropriate for the particular value
Necessary Cost Drivers and
Distinguish:
in that cell. In our example (see Figure 1), the ‘Direct Labor’
Consumption Intensities
• Selection of best design
• no explicit relationships needed
assumption cell is distributed as a triangular distribution while
• Modification of a design:
the ‘Material’ assumption cell is distributed elliptically.
Step 6 – Iterate,
• mathematical functions, or
Step 3 - Identify the
if necessary
• action charts
The Monte Carlo simulation provides random samples of
Relationships between Cost
Drivers and Design Changes
numbers in the assumption cells (material and direct labor). The
Use commercially
available MS Excel and
random numbers propagate through relationships/equations in
Crystal Ball® software
the model and the value of the associated forecast cells (product
Step 4 - Find and Minimize the Cost
of the Consumption of Activities
cost, in our example) is calculated by means of the appropriated
relationships/equation. In our example, the value of the forecast
Use profitability
Step 5 – Evaluate
distributions,
Product Cost is a simple summation of the random numbers for
the Solution
sensitivity analyses,
Material and Direct Labor. When all the trials have been
and trend charts.
performed, the calculated values of a forecast cell will form a
new statistical distribution (see the Product Cost distribution in
FIGURE 2 – FLOW-CHART FOR DEVELOPING ABC
Figure 1). Due to the randomness, the numbers that have
MODELS
propagated through the model can be used in ordinary statistical
Step 1 - Create an Activity Hierarchy and Network.
analysis as if we were running a real experiment, e.g., to
The purpose of this step is to break down that part of the life
construct confidence intervals, perform T-tests, etc.
cycle which forms the design focus into a hierarchy of activities.
A demanufacture process can be broken down into
DEVELOPING AN ABC MODEL INCORPORATING
(sub)activities as in Table 1. This is not the only possible
UNCERTAINTY FOR DESIGN SUPPORT
hierarchy of demanufacture activities. As depicted in Table 1,
Our method for developing ABC cost models that includes
three different levels of activities are present. For example,
uncertainty for decision support in design uses consists of six
activity A1 (‘Collect’) consists of the level 2 activities ‘Buy-
steps. A flow chart of our method is given in Figure 2. We
back’, ‘Transport’, and ‘Store’ (A11, A12, and A13,
illustrate our method by developing an ABC model for assessing
respectively). Of those activities, only ‘Transport’ has lower
and tracing the cost of demanufacturing a telephone and show
level activities, namely, ‘Load’ and ‘Move’ (A121 and A122).
how to guide detailed design changes based on the assessments
The purpose of an activity hierarchy is to ensure that all the
provided by the model.
activities in the part of the life cycle to be studied are
Before discussing the details, we point out that our method
considered. If an objective is to identify the effect of changes in
has the following core components (see Figure 2):
design parameters on cost, then it is essential to form activities
• Formulation (steps 1 through 3) – These steps deal with the
detailed enough that cost drivers can be assigned and that the
actual formulation of the model.
lowest level of the activity hierarchy can be assigned directly to
• Solution (step 4) – The formulated model is solved, i.e., a
the design parameters through the cost drivers.
cost assessment is obtained.
After identifying all the activities, a network indicating the
• Validation (steps 5 and 6) – The results from the solution
relationships between the activities is constructed. In Figure 3,
process are used to assess and verify the model and reiterate
the activity network is shown for a demanufacture process
the process if necessary. Step 6 will not be addressed in the
corresponding to the activity hierarchy in Table 1. In the
paper. More information can be found in [6] .
demanufacture case study we are interested in two different
process scenarios:
• Dismantling; this scenario includes only activities related to
the process of dismantling a product as much as
possible/feasible in order to recover reusable components.
• Shredding; this scenario includes only activities associated
with shredding a product. There is no dismantling.
Both process scenarios are included the network. Another
approach could have been to develop separate models. It is
important to note that, in general, an ABC activity network does
not have a one-to-one corresponds with a process network. In
an activity network, connections and relationships between
process activities are given. A single activity may, however,
consist of several process actions. Consider activity A311
‘manual dismantling’. This activity contains all manual
dismantling actions, no matter where or in what sequence they
occurred in the demanufacturing process. We use the network to
identify:
287

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• what effect a change in the design parameters will have on
Landfill
Non-haz. landfill
A1e51
the consumption of activities, and
Haz. landfill
A1e52
Incinerate
Non-haz. incinerate
A1e61
• what effect a change in consumption of an activity will have
Haz. incinerate
A1e62
on the other activities.
The network also provides the designer a graphical view on
Step 2 - Identify and Order all the Necessary Cost
how different decisions will affect the activities required.
Drivers and Consumption Intensities
The purpose of this step is to identify the cost drivers and
TABLE 1 – DEMANUFACTURING ACTIVITIES2.
corresponding consumption intensities that are necessary to find
Level 1 activity
Level 2 activity
Level 3 activity
Notation
the cost of the consumption of activities with the desired
Collect
Buy back
-
A11
accuracy. The cost of the consumption of a specific activity is
(A1)
Transport
Load
A121
the cost driver(s) multiplied with the consumption intensity.
Move
A122
Store
-
A13
The total costs is found as the sum of the costs of all the
Pre-Clean
-
-
A2
activities that the design solution would impose. The properties
Dismantling
Non-hazardous
Manual dismantling
A311
of ABC depend on the cost drivers chosen. Bad cost drivers may
(A3)
dismantling
Dismantling using handtools
A312
(destructive/
Dismantling using
A313
give bad cost estimates. An example of a bad choice would be if
non-destructive)
light equipment
a unit level cost driver (e.g., mass per unit) was chosen to keep
Dismantling using
A314
special equipment
track of a batch level activity (e.g., inspection).
Hazardous
Manual dismantling
A321
Having identified the cost drivers, the consumption intensities
dismantling
of haz. comp.
for each cost driver should be determined next. Furthermore,
(destructive/
Dismantling of haz.
A322
non-destructive)
comp. using handtools
uncertainties in cost drivers and consumption intensities should
Dismantling of haz.
A323
be modeled at this stage. It would be beyond the scope of this
comp. using light equipment
Dismantling of haz comp
A324
paper to list all cost drivers and associated consumption
using special equipment
intensities with the uncertainty distributions used in the
Sort
Non-hazardous sort
Sort non-haz. reusable comp.
A411
demanufacture cost model. Illustrative examples are listed in
(A4)
Sort non-haz. recyclable mat.
A412
Hazardous sort
Sort haz. reusable comp.
A421
Tables 3 and 4. From Table 1 we see that activities A411 and
Sort haz. recyclable mat.
A422
A412 are sorting of non-hazardous reusable components and
Clean reusable
Clean non-haz. reusable
-
A51
comp.
comp.
recyclable material, respectively. As can be seen in Tables 3
(A5)
Clean haz. reusable comp.
-
A52
and 4, normal and triangular uncertainty distributions are
Inspect reusable
Inspect non-hazardous
Inspect visually non-haz
A611
assigned, respectively, to both the cost drivers and consumption
comp.
reusable comp.
reusable comp.
(A6)
intensities in terms of a mean and left and right deviation. The
Test non-haz. reusable comp.
A612
Crystal Ball software allows twelve different distribution types.
Inspect hazardous
Inspect visually haz. reusable
A621
reusable comp.
comp.
Among them the triangular and normal distributions as used in
Test haz. reusable comp.
A622
Table 3 and 4, but also other types such as the uniform, Weibull,
Shredding
-
-
A7
exponential, and user-defined custom distributions.
Collect reusable
Collect non-haz.reusable
-
A81
comp.
comp.
(A8)
Collect haz.reusable
-
A82
Step 3 - Identify the Relationships between Cost
comp.
Collect
Collect non-haz.
-
A91
Drivers and Design Changes.
recyclable mat.
recyclable mat.
The next step in our method is to identify the relationships
(A9)
Collect haz.recyclable
-
A92
mat.
between cost drivers and design changes. The relationships
Store
Keep records
-
A1a1
between cost drivers and design parameters are the crux of a
reusable comp.
Keep storage
-
A1a2
design decision support model, because they capture how much a
(A1a)
Keep max. storage
-
A1a3
Store
Keep records
-
A1b1
change in one or more design parameters will affect the
recyclable mat.
Keep storage
-
A1b2
consumption of the activities, i.e., the cost.
(A1b)
Keep max. storage
-
A1b3
Transport
Non-haz. transport
Non-haz. loading
A1c11
TABLE 3 – COST DRIVER EXAMPLES.
reusable comp.
of reusable comp.
Non-haz. moving
A1c12
(A1c)
Haz. transport
Haz. loading
A1c21
Activity
Cost driver
of reusable comp.
Haz. moving
A1c22
Distribution
Mean
Left dev.
Right dev.
Transport
Non-haz. transport
Non-haz. loading
A1d11
A411
Direct labor
Normal [h/batch]
20.0
10.0
30.0
recyclable
of recyclable material
Non-haz. moving
A1d12
A412
Direct labor
Normal [h/batch]
15.0
10.0
20.0
material
Haz. transport
Haz. loading
A1d21
(A1d)
of recyclable material
Haz. moving
A1d22
TABLE 4 – CONSUMPTION INTENSITY EXAMPLES.
Manage waste
Collect waste from
Collect non-haz. waste
A1e11
(A1e)
disassembly stations
Collect haz. waste
A1e12
Activity
Cost driver
Consumption intensity
Store waste for
Keep records
A1e21
Distribution
Mean
Left dev.
Right dev.
landfilling
Keep storage
A1e22
A411
Direct labor
Triangular [$/h]
20.0
18.0
23.0
Keep max. storage
A1e23
A412
Direct labor
Triangular [$/h]
20.0
18.0
23.0
Store waste for
Keep records
A1e31
incineration
Keep storage
A1e32
A key objective for using an Activity-Based Cost model in
Keep max. storage
A1e33
design is to identify how changes in different design parameters
Transport waste to
-
A1e4
final destination
affect the cost and consumption of the activities. The level of
detail and sophistication needed in modeling the relationships

between cost drivers and design parameters depends on the
2
Gray cells represent lowest level activities. The notation refers to the shaded cells.
purpose and usage of the cost model. In Figure 4, different uses
haz. = hazardous, comp. = components, mat. = materials
288

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and ways of modeling the effects of design changes on the cost
Driver/Design Parameter relationships which link design
are illustrated. We identify two distinct uses of an Activity-
changes at the property/dimension level (bottom level in Figure
Based Cost model:
4) to the cost drivers. This approach allows us to modify designs
1) Evaluation of a number of discrete designs in order to
on a very detailed level and enables cost minimization directly
identify the economically best design, that is, the cost of a
by computing the set of the most cost effective design parameter
number of alternative designs is determined and a selection of a
values using, e.g., optimization algorithms. However, the usage
design is made based upon the result. Therefore, we do not
of such mathematical Cost Driver/Design Parameter
have to model the relationships between design parameters and
relationships can become extremely cumbersome in the design of
cost drivers explicitly. This approach works at the activity
complicated systems where there are a) many relationships and
level (the top level in Figure 4) and selection of the most cost
b) many changes made over time in the relationships.
effective design is the primary purpose.
In Figure 4, a solution is represented by introducing a level in
2)
Identification of “optimal” values for continuous
the middle - where we do not keep track of design properties and
design parameters, that is, a given design is modified through,
dimensions, but rather keep track of how the design properties
e.g., mathematical optimization in order to identify the ideal
and dimensions affect specific actions. The aggregated effect on
values of a number of design parameters. Rather than selection
these actions is then transformed into an aggregated effect on the
of designs, modification of an existing design is the primary
activities and the cost drivers. In the next section, this concept
purpose. This is shown in the gray area of Fig. 4.
of using “action charts” to identify the aggregated effect of
In order to improve design parameter values (usage 2), it is
design changes on activities in the ABC model is discussed in
necessary to identify the effect the design parameters have on the
detail.
cost drivers. The highest amount of detail is obtained if these
effects are quantified in detailed mathematical Cost
A
A 411
A 51
A 611
A 612
A81
A 1a2
A1c11
A1c12
311
A 312
A 11
A 412
A 91
A 1b2
A 1d11
A 1d12
C
A 313
B
A 121
Landfill A1e22
A1e4
A1e51
A 1c22
Dismantling
F
A 314
A
A1e32
A1e4
A1e61
122
Incinerate
B
A7
A 1c21
Shredding
A 13
A
Non-hazardous
A
1a1
1e11
A1a2
A 321
No
A 1a3
No
A421
A 52
A 621
A 622
A 82
A2
A
A 322
Yes
D
E
Yes
No
Hazardous
A 323
B
A422
A92
No
A 1b3
C
A 1e22
A1b1
A1b2
A 324
Dismantling
A 1d21
No
B
A7
Shredding
Yes
Yes
D
E
A1e23
A 1e4
A1e52
Decisions nodes:
A1e12
A 1d22
Hazardous or non-hazardous
Landfill
A
material or component
No
A 1e21
F
B
Type of demanufacturing
A 1e32
process
Incinerate
Store for less than
Yes
D
No
C
E
Type of disassembly tools
90/180 days?
Yes
E
A 1e33
A 1e4
A 1e62
No
Less than 100 kg/month of
D
hazardous waste?
F
Landfill or incinerate
A 1e31
FIGURE 3 – DEMANUFACTURING ACTIVITY NETWORK. THE ICONS ARE THE SAME AS USED IN [11] .
TABLE 2 – DEMANUFACTURING ACTIVITIES AND COST DRIVERS.
Activity
Cost drivers
Activity
Cost drivers
Activity
Cost drivers
A11
Buy back
A52
Direct labor; Tooling time; No. of set-ups
A1c22
No. of batches; Fuel; No. of set-ups
A121
No. of batches
A611
Direct labor
A1d11
No. of batches
289

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A122
Number of batches; Fuel
A612
Direct labor; No. of tests
A1d12
No. of batches; Fuel
A13
Volume
A621
Direct labor; No. of set-ups
A1d21
No. of batches; No. of set-ups
A2
Direct labor; Tooling time
A622
Direct labor; No. of set-ups; Number of tests
A1d22
No. of batches; Fuel; No. of set-ups
A311
Direct labor
A71
Tooling time
A1e11
Tooling time
A312
Direct labor; Tooling time
A81
Tooling time
A1e12
Tooling time; No. of set-ups
A313
Direct labor; Tooling time
A82
Tooling time; No. of set-ups
A1e21
Direct labor
A314
Direct labor; Tooling time
A91
Tooling time
A1e22
Volume
A321
Direct labor; No. of set-ups of safety
A92
Tooling time; No. of set-ups
A1e23
Direct labor; Volume
equipment
A322
Direct labor; Tooling time; No. of set-ups
A1a1
Direct labor
A1e31
Direct labor
A323
Direct labor; Tooling time; No. of set-ups
A1a2
Volume
A1e32
Volume
A324
Direct labor; Tooling time; No. of set-ups
A1a3
Direct labor; Volume
A1e33
Direct labor; Volume
A411
Direct labor
A1b1
Direct labor
A1e4
No. of batches; Fuel
A412
Direct labor
A1b2
Volume
A1e51
Volume; Mass
A421
Direct labor; No. of set-ups
A1b3
Direct labor; Volume
A1e52
Volume; Mass
A422
Direct labor; No. of set-ups
A1c11
No. of batches
A1e61
Volume; Mass
A51
Direct labor; Tooling time
A1c12
No. of batches; Fuel
A1e62
Volume; Mass
A1c21
No. of batches; No. of set-ups
Evaluation of
Focus of interest:
the level of details, which is typical for a good action chart. The
Alternative Designs
The effect the actions
less detailed an action chart is, the less suitable it is for design
³ Activity Network
have on the activities.
Increased Level of:
modifications.
³ Detail
What purpose does the dismantling action chart serve? The
³ Model complexity
Modification of Design
action chart in Figure 6 allows the detailed documentation of a
³ Design change
The effect the design
³ Activity Network
traceability
properties, (e.g. Mass)
disassembly process. Manual disassembly can be considered as
³ Action Charts
have on the actions.
a single activity in an ABC cost model and a reduction of overall
disassembly time is clearly advantageous. But on which product
³ Activity Network
component should a designer focus? Time is not the only cost
³ Action Charts
Properties/dimensions
driver in disassembly. A different material or fluctuations in
³ Cost Driver/Design
etc. of the design.
material prices also affect overall revenue. This kind of product
Parameter Relationships
design related information is embodied in the dismantling action
FIGURE 4 – DIFFERENT LEVELS OF MODELING
chart. In essence, an action chart forms an interface between
detailed product information and a general demanufacturing
Tracing Costs to Design Using Action Charts
ABC model, in our case.
What are action charts? Activities are formed by grouping
actions that have a logic connection together [4, 5] . This is done
mainly because it is impossible to achieve credible cost
information for every step in a process. It would require an
enormous amount of cost drivers and consumption intensities,
associated with an even larger amount of possible uncertainty.
Thus, actions that occur in a process are grouped into activities.
Forming the activities in a way that roughly describes the
process is advantageous because this will make the ABC model
much easier to understand and use as it coincides with our
perception of the process.
The grouping of several process actions into a smaller number
of activities opens up the possibility of designing a model with a
generic set of low level activities which has design specific
inputs - the actions. This is a powerful approach since any
process can be described with a set of activities that will always
be present, no matter what product we are dealing with. The
definition of activities is a function of the desired degree of
generality, accuracy and traceability. Increased generality will in
general give decreased accuracy and traceability. The usage of
aggregated actions is a way of capturing how design changes
affect the costs and revenues. It is an approach in between a)
not modeling any relations at all and merely assessing cost of
designs and b) modeling the relationships in detailed
mathematical relationships and computing the most cost
effective values of design parameters. By aggregating the
actions in so-called action charts, we keep track of how the
design properties and dimensions affect the actions. The
aggregated effect on the actions is then transformed into an
aggregated effect on the activities and the cost drivers. In Figure
6, a sample from a dismantling action chart of a telephone is
shown, derived from disassembly charts outlined in [12] . Note
290

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the consumption of the demanufacture activities. To support this
step, we have implemented the entire model in Microsoft Excel
Mass
[kg]
0.0030
0.0060
0.0140
0.0580
0.0001
0.0001
4.0 spreadsheet files on a Macintosh platform. A detailed

description can be found in [13] . As stated before, we have
4
4
4
1
4
1

Mtl.
Recycl.
chosen to use software called Crystal Ball which allows the
definition of uncertainty distribution in spreadsheet cells and
ABS
Lead
Mix
set
finds resulting uncertainty distributions numerically using a
plastic
Steel
Materials
Recyclability
Material
copper,
Thermo-
Monte Carlo simulation. The results obtained in this fashion for
telehone demanufacture are discussed next.
yes
No
yes
yes
yes
yes
yes
Nondest-
structive
Step 5 – Evaluate the Solution
D
Dirt/
Corr.


There are many assumptions made in the model (135
assumption cells in 10 model files). An important assumption is
4
4
4
4
4
4
Fatigue
that the plant capacity is less than market demand. Another
=> assembly can be dismantled without totally or
assumption worth noting is that a $1 buy back price is paid per
=> assembly cannot be dismantled without totally or
4
4
4
4
4
4
Nondestructive: Yes
partially destroying any part of the (sub) assembly. No partially destroying any part of the (sub) assembly.
telephone. Once the model is implemented in spreadsheet
Abrasion
structure, several tools are available for evaluating the solution,
results, and the effects of the assumptions and design decisions
Std
Std
Std
Std
Std
Std
made. We illustrate two tools available, i.e., profitability
Reusability
(Product-Recyclability)
Stnd./
Special Pt.
And so forth

distributions and sensitivity charts.
Snap on
Snap on
Glue on
Snap on
Tool for
Assembly
Profitability Distributions. The resulting profitability
distribution for the ‘Dismantling’ scenario is presented in Figure
4
30
5
15
5
Time
[sec.]

1 => Bad, 2 => Below average, 3 => Above average, 4 => Good
7. These distributions provide a good indication of what the
4
2
3
3
4
effects of the uncertainties in the assumptions are and, in our
Force
Qualitative assessments:
Quantity, Time and Mass are assessed quantitatively.
opinion, provide more valuable information for designers than
merely a single number. The mean is estimated to be -$2.30 if
we pay, on average, $1.00 for the telephones. In other words, it is
Tool
Crowbar
Crowbar
Crowbar
not economically feasible to dismantle the present telephone
4
3
3
3
3
Disassemblability
A/C
design. The results from the ‘Shredding’ scenario are presented
CE
SP
SP
SP
SP
Type
SA
SA
SA
in Figure 8. The shredding option is also economically infeasible,

(4 is good, 1 is bad),
but we see that the revenues nearly balance the costs if we would
1
1
1
1
1
1
1
1
Quan-
tity
not have paid $1.00 for old telephones.

Forecast: Dismantling Unit-profitability

Connecting Element, Sub Assembly, Single Part, Accessibility; Standard part,
Name
Mass
Cell F415
Frequency Chart
999 Trials Shown
Remove
spring
cover

From 26;
From 26;
From 26;
Remove top
Disassemble
.033
33
Snap off base-
handset cable
from bottom
Remove mic.
cables and CB
circuit board
circuit board
Notes:
CE: SA: SP: A/C: Std: Mtl. Recycl.: Material Recyclability,
Disassembly
activity and object
No.
1
Handset Disassembly
2
3
4
27
28
29
30
.02
24.7
FIGURE 5 – A PHONE DISMANTLING ACTION CHART.
.01
16.5
In order to support the ABC model, each action must be
associated with a sufficient set of information. In our opinion, the
.00
8.25
following set of action information seems to be sufficient input for
each activity in a demanufacturing model:
.00
0
-3.50
-2.94
-2.38
-1.81
-1.25
• All actions related to the specific activity, and
[$/unit]
• For each action: the number of units, the mass and material
FIGURE 7 – ‘DISMANTLING’ PROFITABILITY
composition for each unit, the time to perform an action, the
DISTRIBUTION
tools used, the process efficiencies, the hazardousness of the
units, and the danger in performing the actions.
Forecast: Shredding Unit-profitability
Uncertainty distributions can be assigned in the action chart, e.g.,
Cell F416
Frequency Chart
998 Trials Shown
for specific disassembly times, and the effect of variations in a
.032
32
product design can be traced. In the next section, we discuss the
results obtained from using a demanufacturing action chart in our
.02
24
demanufacturing ABC model.
.01
16
Step 4 – Find and Minimize the Cost of the
.00
8
Consumption of Activities.
Having created the ABC model, defined the relationships
.00
0
between design properties and cost using action charts, and
-2.00
-1.50
-1.00
-0.50
0.00
modeled the associated uncertainty, we now proceed to step four
[$/unit]
of our method, i.e., find (and minimize) the cost associated with
FIGURE 8 – ‘SHREDDING’ PROFITABILITY
291

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DISTRIBUTION
• No. 11 Unit-revenue [$/unit], associated with reusable
Taking into account that many assumptions have been made
speakers, and
and the fact that the upper limit of the distribution is close to a
• Business days per week.
break even situation, we should not rule out the possibility of a
As can be seen, product design as well as process factors affecr
break even situation in the real world.
the cost. Most gain can be made by reducing the buy-back price,
but a handset redesign is arguably a pressing product design
Identifying Largest Cost Contributors Using
issue. Sensitivity analyses for other scenarios and using perfect
Sensitivity Charts. Assuming that we want to pursue
process information are documented in [13] . The more trials
dismantling of telephones, what changes should we make in
performed, the more useful is the sensitivity chart. The reason is
order to boost profitability? One might argue that a product
that the variability of the correlation coefficient estimates
design should be improved according to Design for Disassembly
decreases as the number of trials increases because the number
guidelines, but it may be that process aspects such as labor and
of degrees of freedom increases, and that the probability for
interest rates are far more significant than the product design.
correlation by chance decreases, see [14] .
We employ sensitivity charts to gain insight in these issues.
In Figure 9, a (shortened) sensitivity chart for the dismantling
CLOSURE AND FUTURE WORK
process model is given. Such a sensitivity chart is generated for
In this paper, we discussed how an Activity-Based Cost model
each simulation by the Crystal Ball software and is based on the
can be developed and used in design under presence of
so called Spearman Rank Correlation and measures the degree to
uncertainty. We highlighted the modeling and propagation of
which assumptions and forecasts change together. The larger
these uncertainties through a cost model using commercially
absolute value of the correlation coefficient, the stronger is the
available software. The inclusion of uncertainty and usage of
relationship. Positive coefficients indicate that an increase in
Monte Carlo simulation provides the capability to identify those
the assumption cell is associated with an increase in the forecast
process and product design aspects that contribute most to the
cell.
cost using so-called action charts. An action chart represents a
Sensitivity Chart
group of associated actions which together form an activity. We
Target Forecast: Dismantling Unit-profitability
used disassembly actions as an example. The subsequent use of
sensitivity charts facilitates identification of the most cost
Telephone 2 Pay-back Price …
-.83
inefficient parts. Profitability distributions and sensitivity charts
A612 Number of Tests [$/test]
-.46
A13 Volume [$/ft^3]
-.11
assist in identifying:
No. 2 Time [sec.]
-.09
• where we should focus our data collection efforts, e.g.,
A311 Direct Labor [$/h]
-.09
because payback prices and direct labor have such significant
No. 11 Unit-revenue [$/unit]
.09
influence (see Figure 9) we should collect more accurate data
Buisness days per week
.09
in these areas.
Motor Control House [$]
-.08
• where we should focus our design efforts, e.g., with respect
No. 20 Time [sec.]
-.07
to the telephone design, we should focus on the removal of
.....
.....
.....
the top from the base because it is the largest cost
A622 Direct Labor [$/h]
-.06
contributor.
Brass [$/kg]
-.05
It should be emphasized that especially in the early stages of
-1
-0.5
0
0.5
1
design, the identification of the largest cost contributors and
Measured by Rank Correlation
critical factors is more important than the actual cost.
FIGURE 9 – SENSITIVITY CHART FOR ‘DISMANTLING’
With respect to validity, we have attempted to make our
PROFITABILITY
demanufacturing model as realistic as possible, e.g., the EPA
regulations for storing hazardous waste have been incorporated.
As can be seen in Figure 9, the chart allows us to pin point the
The model presented in this paper seems to give reasonable
factors/assumptions for the ‘Dismantling’ scenario that
results. In fact, the same model has been applied to assess and
correlates most with the forecast cell. This facilitates studying
trace the cost of demanufacturing a car and the results were
the importance of the different assumptions in the model. It also
compatible with real world experiences [13] . We have most
indicates what cells should be updated with better, more
likely underestimated the total overhead cost for a
accurate information. The major cost and revenue triggers are:
demanufacturer, so we would expect that the true costs are
• Telephone 2 buyback price,
higher than estimated. Another aspect to take into account is
• A612 Number of tests [$/test]3, number of tests to check if
that most of the plastic revenue information, is based on [15]
components are reusable or not,
and reported to be from 1990.
• A13 Volume [$/ft^3], storage consumption intensity for units
Our focus in future work is on the following key aspects. We
in to the demanufacturing plant,
are continuing to validate, improve, and expand our method and
• No. 2 Time [sec.], time to perform action number 2 from the
models. One of our objectives is to utilize the tractability of the
phone action chart - ‘Remove top from bottom’ of the
costs and uncertainty through an activity network and identify
handset disassembly, a product aspect to be redesigned,
which life-cycle activities are truly critical in a product’s life-
• A311 Direct labor [$/h],
cycle.
In the long term, we seek to utilize the ABC method not only

for monetary cost assessments, but also for life-cycle
3
assessments of environmental impact in terms of matter and
From the unit, [$/test], we understand that this is the consumption intensity of
activity A612 and not the cost driver.
energy consumption. A model which provides an environmental
292

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impact assessment in terms of energy and matter consumption
14. Hines, W. W. and Montgomery, D. C., Probability and
and emission can be used for exploring the global (societal)
Statistics in Engineering and Management Science, John Wiley
environmental impact of engineering products and processes.
& Sons, Inc., (1990).
E.g., recycling products is nice, but recycling may cost more
15. Dieffenbach, J. R., Mascarin, A. E. and Fisher, M. M.,
energy than a disposal process. The use of an ABC approach
“Modeling Costs of Plastics Recycling”, Automotive Engineering,
may overcome some of the difficulties associated with
October (1993).
conventional Life-Cycle Assessment/Analysis tools, e.g., the
cumbersome amount of work involved and the lack of common
standards. In our opinion, an activity-based Life Cycle
Assessment is most easily done for energy where we have a
single unit. It will be more difficult for materials where, e.g., we
need to distinguish different grades of toxicity.
Although we have focused on demanufacturing as the area of
application, It should be noted that our method, as most ABC
based methods, is generic in that it can be applied whenever the
activities are described in sufficient detail to have cost drivers
assigned.
REFERENCES
1.
Congress, U. S., “Green Products by Design: Choices for a
Cleaner Environment”, OTA-E-541, Office of Technology
Assessment (1992), Washington, D.C.
2.
Keoleian, G. A. and Menerey, D., “Sustainable
Development by Design: Review of Life Cycle Design and
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644-668.
3.
Brooks, P. L., Davidson, L. J. and Palamides, J. H.,
“Environmental compliance: You better know your ABC’s”,
Occupational Hazards, February (1993), pp. 41-46.
4.
Cooper, R., “ABC: A Need, Not an Option”, Accountancy,
September (1990), pp. 86-88.
5.
Cooper, R., “Five Steps to ABC System Design”,
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6.
Emblemsvåg, J. and Bras, B. A., “Activity-Based Costing in
Design for Product Retirement”, Proceedings 1994 ASME
Advances in Design Automation Conference, DE-Vol. 69-2,
Minneapolis, Sept. 11-14, ASME, (1994), pp. 351-362.
7.
Turney, P. B. B., “How Activity-Based Costing Helps
Reduce Cost”, Journal of Cost Management for the
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8.
O’Guin, M., “Focus The Factory With Activity-Based
Costing”, Management Accounting, Feb. (1990), pp. 36-41.
9.
Raffish, N. and Turney, P. B. B., “Glossary of Activity-
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Environmental Recovery Analysis”, 9th International Conference
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Zurich, Switzerland, (1993), pp. 780-787.
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Framework”,
Journal of Cost Management for the
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Waschmaschine (recycling-oriented washing machine)”, Institut
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Universität, Berlin (1992).
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