ESE 499 Final Report: Capstone Design Project
submitted to
Professor Dennis Mell
Department of Systems Science and Engineering
Washington University
by
Jake Lyonfields
Senior in Systems Science and Engineering
at
6021 Pershing Avenue
St. Louis, MO 63112
(636)-484-4282
on
April 28th, 2014
for the project entitled,
“A System Dynamics Approach to Determining Restaurant Waste Management Costs”
under the direction of
Professor Peter Hovmand
Professor of Practice and Director of the Social System Design Lab at Washington University
at
(314)-935-7968
phovmand@wustl.edu
during
March 2013 – April 2014
previously under the direction of
Mr. Joe Edwards of Blueberry Hill and the Loop Special Business District
at
6504 Delmar
St. Louis, MO 63130
(314)-727-4444
during
October 2013 – March 2014
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Abstract
This Senior Design Project began as an attempt to utilize operations research techniques in order to assess the
economic feasibility of implementing composting efforts at restaurants in The Delmar Loop. The student
coordinated with Mr. Joe Edwards, owner of Blueberry Hill, to design a survey that was used to solicit waste
management data from the aforementioned businesses. This data would have been used to construct the
constraints and objective function of the operations research problem, however, since very few businesses
ultimately chose to complete the survey, finishing this particular Senior Design Project with any meaningful
results was not possible (references to this original project attempt will be made using the phrase “initial
project.”). The student then sought guidance from Professor Hovmand and thereafter decided to use Vensim
software and system dynamics methodology in order to outline how modifying different parts of a business’
waste management process impacts the waste-related expenses (this secondary project effort will be referenced
with the phrase “second project.”). Results include the design of a concept model of business waste
management efforts, as well as a larger, more involved model of business waste management practices. Results
also include a Weebly website that documents the work completed as part of this Senior Design Project.
Employed Resources
The student utilized a number of resources to complete this project. With respect to the initial project, the
student sought informal consultation from the WUSTL Office of Sustainability’s Director of Sustainability
regarding how best to approach encountered obstacles. A survey meant to gather information from restaurants’
waste management practices was designed in collaboration with Mr. Joe Edwards and was disseminated
electronically by email (the survey was delivered through The Loop Special Business District email listserv to
the restaurants in The Loop). The survey for the initial project was typed up in Microsoft Word, and the few
survey responses that were actually received were documented and organized in Microsoft Excel. Additionally,
the student checked in regularly with Mr. Joe Edwards, the initial project’s client, by phone in order to update
him about the initial project’s progress. Copies of the survey were also distributed at least twice in envelopes to
representatives of each of the restaurants in The Loop as part of a continuous follow-up effort during the Fall
and Spring semesters of the 2013-2014 school year (there are over 3 dozen restaurants whose feedback was
solicited, and some of these restaurants received printed surveys more than twice). Numerous calls were made
and emails sent to these restaurants as part of this same continuous follow-up effort.
When it became apparent that an overwhelming majority of restaurants were choosing not to complete the
survey, Professor Hovmand acted as a resource for the student, suggesting multiple ways in which the student’s
approach could be modified so that he could still complete a Senior Design Project. Thereafter, the second
project began by investigating federal and state-level online educational and informational resources in order to
fill in pertinent knowledge gaps. Sterman’s Business Dynamics textbook was consulted when uncertainty arose
regarding how to construct the Vensim models of the second project. Of course, the student also used Vensim
software to build the models for his second project. Notes from ESE408: A System Dynamics Approach to
Designing Sustainable Policies and Programs, a class in which the student was enrolled this past semester, were
also considered when further guidance was needed. The website Weebly was used in order to put together the
accompanying project website. Finally, the student occasionally talked aloud to his dogs or to his roommates
when he needed a sounding board for his ideas.
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Table of Contents
1. Introduction……………………………………………………………………………… 4
2. Problem Statement and Employed Technical Methods...………………………………...5
3. Found Solutions and Conclusions…….…….……………………………………………8
4. Website…………………………………………………………………………………..12
5. Accompanying Materials………………………………………………………………...12
6. Reflections……………………………………………………………………………….12
7. Appendix A………………………………………………………………………………14
8. Appendix B………………………………………………………………………………15
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Introduction
Composting is a form of waste management that permits organic waste to break down as it might in the natural
environment. Consequently, this decomposition is less environmentally impactful than the kind of decay that
occurs in regular landfills. Commercial-scale compost collection is not practiced widely in the St. Louis
Metropolitan area, with a few notable exceptions (for example, Washington University in St. Louis regularly
composts kitchen scraps and other materials produced in its dining locations). However, as customers are
increasingly concerned about the environmental impact of their purchasing decisions and as different forms of
waste management offer the opportunity for both increased efficiency in waste disposal and a competitive
business edge, it is worthwhile to explore the economic feasibility of alternative forms of waste management.
The initial project sought to conduct an economic analysis of different waste management strategies for
restaurants in The Delmar Loop in an effort to determine if waste management strategies existed that were more
economically efficient or environmentally sustainable than currently employed practices. Specifically, the
analysis for this effort would have been grounded in the use of linear programming, supplemented by robust
data collection, appropriate data management, scenario analyses, and sensitivity analyses.
The aim for the second project was the construction of a “concept model” of the situation. A concept model is a
relatively small system dynamics model within the domain of the problem that illustrates all of the key concepts
that someone unfamiliar with system dynamics would need to understand to assess the value of the project.
Thus, Vensim and system dynamics methodology each were employed to construct such a model for a
restaurant that might hypothetically be reviewing their waste management practices. However, in order to build
on the potential opportunity to explain to stakeholders the value both of considering alternative waste
management options and of employing a system dynamics approach to evaluating waste management options, a
more involved model was built that would require some basic inputs but that would allow a relatively robust
analysis of waste management alternatives.
The student had several responsibilities during this project. To begin with, during the initial project the student
was responsible for keeping Mr. Joe Edwards and The Loop Special Business District up to date regarding
project happenings, including survey dissemination and the collection of survey results. Accordingly, survey
design, dissemination, and the collection of results were also student responsibilities. Had the collection of
survey results been generally successful, then the student would also have been responsible for formulating a
reasonable mathematical model to represent the problem and for using linear programming to derive solutions
to the problem. It was always the responsibility of the student to be available for Mr. Edwards for review and
consultation. When the second project became the focus of the student’s Senior Design Project, the student was
responsible for consulting with Professors Mell and Hovmand when needed and for following the directions
laid out by Professor Hovmand regarding the development of the concept model and accompanying material.
Finally, the student also needed to create a website that documented the work put forward during the course of
the project.
There were several results and accompanying benefits that came from the students’ efforts. First, it is
worthwhile to note that, as a result of the student’s work during the initial project, a well-developed survey, a
copy of which can be found in the Appendix, was produced that could be used in order to analyze a restaurant’s
waste management practices. Secondly, in tackling the second project, a concept model was developed that
could hypothetically be used to explain to stakeholders what the potential value is of assessing different waste
management strategies for their restaurants. Additionally, however, a more robust model was built, into which
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collected data can be inputted for the purpose of running a simulation that can describe annual costs associated
with a particular waste management strategy (in other words, this model can be used as a tool for stakeholders
interested in evaluating their own waste management practices).
Problem Statement and Employed Technical Methods
This section contains two subsections. The first, titled “Initial Project: Proposed and Employed Technical
Methods,” describes the technical methods that were proposed for the initial project, as well as those technical
approaches previously proposed that were actually carried out. The second, titled “Second Project: Employed
Technical Methods,” delineates the technical methods used to carry out the second project.
Initial Project: Proposed and Employed Technical Methods
As stated, the goal of this project was, from October 2013 to March 2013, to analyze the extent to which
different levels of composting collection are feasible for pertinent businesses on the Loop. “Economic
feasibility” is a term that can have many different meanings. In the initial project, the most economically
feasible waste management strategy was intended to be the one that minimizes the cost of waste management
operations for food service businesses. Scenario analyses were going to explore how the feasibility of certain
waste management operations changed from the base case scenario with modifications in the availability of
certain resources.
Intended Linear Programming Approach for Initial Project
In particular, linear programming techniques were going to be utilized, with the following decision variables:
xi = pounds of landfill waste coming from landfill tote “i”. It was to be assumed that current landfill
operations will be utilized for all waste sent to the landfill by businesses. As such, it was not going to be
necessary to designate a landfill drop location in the landfill waste decision variables.
yj = pounds of recycling waste coming from recycling tote “j”. It was to be assumed that current
recycling operations will be utilized for all waste sent to recycling plants by businesses. As such, it was
not going to be necessary to designate a recycling drop location in the recycling waste decision
variables.
zm,n = pounds of compost waste coming from composting tote “m” to composting drop location “n”.
“n” > 1 only if more than one composting drop location s had been determined to be available for use (it
was unknown at the beginning of the initial project whether composting sites with significant capacities
existed that were going to be available for use)
These decision variables were going to be used when formulating the objective function, which was to
enumerate the overall cost of a business’ waste management strategy. The student was going to attempt to
minimize this cost, and reflected in the solution to the objective would have been values for each decision
variable that indicated how many pounds of each type of waste should be sent to respective waste drop
locations. These values would then have served as an indication of the different waste management strategies
that ought to be employed at a particular business if a business is seeking to minimize cost (e.g., if all zm,n = 0
then it is understood that the business ought not enact any composting collection methods).
These decision variables would also have been used as the basis for formulating constraints for the linear
programming problem. While not all constraints were initially known (e.g., the student was initially unaware of
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the current capacities of available composting drop locations), the general form of certain constraints could have
been outlined.
For example, the list of constraints would have included the minimum expected amount of waste generated in a
typical week for a particular business location, which would have taken the form of
xi + yj + zm,n ≥ bp, where “bp” is equal to the minimum expected amount of waste generated for a
particular business location “p” in a typical week
Other constraints might have included restrictions such as the amount of compost waste that could be sent to a
composting drop location per week from a particular business, the maximum amount of material that a
particular business could appropriately compost based on their waste profile, etc. Not all previously known
constraints are listed here for the purposes of brevity.
Moreover, it would have been assumed that all constraints exist as linear relationships in order to accommodate
the linear programming approach being utilized in this project. Linear approximations were to be made for any
constraints not inherently linear in nature as the need arose.
Finally, the objective function was to be built using those cost relationships ascertained through the data
collection phase of this project, with the ultimate goal, as stated, being the minimization of the cost of waste
management operations. Again, appropriate linear approximations were to be made as necessary.
Data Collection for Initial Project
The costs of waste management operations are dependent on the amount of each type of waste that is sent to
respective waste drop locations (that is, both how many pounds of compostable, recyclable, and landfill material
are produced each week by a business and how the business chooses to dispose of such waste). Understanding
the amount of waste a location generates is important because such information provides the basis for the
creation of linear constraints regarding the selection of particularly sized waste receptacles. Knowing the
maximum percentage of compostable, recyclable, and landfill material is important because these percentages
will set limitations on the total amount of each type of material that can be sent to different waste drop
locations, something that further limits container options for businesses.
The initial project’s survey was created in order to ascertain the aforementioned cost-related data from a
substantial number of restaurants in The Delmar Loop (e.g., those fees, in dollars/ton of waste, assessed to each
restaurant based on the amount of waste hauled from their dumpsters each day). The survey was also intended
to help the student understand what waste-related infrastructure was employed by each restaurant (e.g., whether
restaurants owned or rented waste dumpsters, how big these dumpsters are, etc). Waste audits, which can
typically be performed for little to no cost for businesses that utilize large landfill or recycling haulers, could
have been used to profile each restaurant’s waste stream.
However, the initial project’s duration and scope might have made it infeasible anyway to conduct waste audits
on each of the food service businesses in The Delmar Loop for which composting collection might have been
considered. Thus, the creation of generic “profile” food service businesses, which assume particular waste
generation activities (“waste generation activities” can be defined as those activities that generate different
quantities or types of waste) based on a smaller number of waste audits would have proven to be a more
expedient, cost effective, and relatively accurate basis for determining the economic feasibility of implementing
different levels of composting collection operations. In other words, creating profile food service businesses
would have allowed the student to assume particular types of waste generation activities for those businesses in
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The Loop that would have been considered in this analysis, thus permitting the student to assume that the results
obtained from solving the objective function in the model were appropriately applicable to the food services
businesses involved in this project.
Still, the problem was then presented of how to create the aforementioned “profile” food service businesses. An
overall “average” profile food service business might be constructed that reflects the mean amount of waste
generated by all food service businesses on the Loop as well as the average maximum percentages of
compostable, recyclable, and landfill waste for all businesses on the Loop.
However, the use of an “average” profile food service business as the basis for the model could result in
calculating recommendations for waste management operations that are actually inappropriate for individual
food service businesses. For example, the model may suggest using particularly sized recycling containers for
all food service businesses when, in fact, the expected amount of recyclable material resulting from some
business operations may exceed the size of the recommended container. In short, excessive or limited waste
management recommendations translate into unnecessary expenditures or missed opportunities, respectively.
An alternative approach was to categorize the food service businesses on the Loop into different groups based
on the amount of waste they typically produce and then create “average” profile food service businesses for
each group. Specifically, average profiles of three groups of food service businesses, classified as “small,”
“medium,” and “large” based on the amount of waste they generate, could have been used as the basis of the
base case scenario model. Although this approach might have been slightly more tedious, it also could have
been advantageous both because the model’s resulting recommendations for each of these three groups of
businesses would probably have been more appropriate for the individual businesses present within each of
these groups and because it is likely that businesses that produce similar levels of waste also have similar
existing waste management operations budgets. This latter point is especially important when considering how
such resources might be reallocated after considering the model’s results. Because of this strategy’s benefits, the
grouping approach with “small,” “medium,” and “large” categories was planned for this model. A decision
regarding the number of waste audits to pursue when building the “average” profiles was to be made after
grouping the Loop’s food service businesses into the aforementioned categories. Because this strategy was to be
employed, it was going to be necessary to acquire estimations of the amount of waste generated annually by
each of the participating food service businesses.
The data collection plans of the initial project also included soliciting information on the costs involved with
various levels of composting, recycling, and landfill waste collection and removal. Such information was to be
garnered from the waste bills of the different food service businesses, from the external landfill and recycling
businesses already involved with waste management efforts on the Loop, and from any commercial composting
businesses that could hypothetically be involved in food service waste management efforts on the Loop. This
pricing information was going to be useful in formulating the base case scenario model for this project and in
comparing existing practices to the optimal solution produced by the model.
Any additional information required to formulate the model was to be solicited throughout the course of the
project as needed.
The data collection that actually occurred during the project included the development and subsequent
dissemination of the waste management survey. The challenges surrounding the collection of data for the initial
project have already been documented (see the “Employed Resources” section) – only 7 restaurants responded
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to the waste management survey, and 3 of the 7 survey responses were incomplete, that is, they did not include
all of the information necessary for the completion of the initial project.
For the sake of brevity, the previously made data management plans for the initial project, as well as previously
made plans for conducting scenario and sensitivity analysis, will not be documented in this final report. The
initial project proposal will accompany the submission of this final report to Professor Mell and Professor
Hovmand.
Second Project: Employed Technical Methods
Employed technical methods for the second project consisted of utilizing a system dynamics approach to
develop a waste management concept model and of constructing such a model in Vensim. Additionally, more
robust model was developed after constructing the concept model.
The concept model informed the development of the more robust model; specifically, Professor Hovmand
recommended approaching the task in order to construct a relatively small model within the domain of the
problem that illustrates all of the key concepts that someone unfamiliar with system dynamics would need to
understand in order to assess the value of a project. Thus, a model was constructed using as few stocks, flows,
and endogenous/exogenous variables as possible so that stakeholders might easily engage the concept if it were
presented to them. However, no simulations were run with the concept model because, even if all of the data
necessary for running a simulation existed as a consequence of receiving survey responses, the results of such a
simulation, generated from a relatively elementary model, would not actually have been meaningful. Instead,
attention was given to simplifying the model so that a stakeholder might be able to use it in order to understand
how waste management processes can be analyzed for further improvement.
The more robust model was developed for the purposes of offering a tool for stakeholders to assess the costs
involved with their current waste management practices. Unlike the concept model, it permits users to evaluate
the costs of managing three different kinds of potential waste streams: landfill, recycling, and composting. It
also offers the opportunity to evaluate how changing the overall makeup of their waste (e.g., increasing the
percentage of recyclable material and decreasing the percentage of landfillable material) affects costs. Thirdly,
it takes into account a significant issue of waste streams, namely, the difficulty in ensuring the complete
accuracy of waste sorting by employees. So, the user is able to delineate what percentage of recyclable material,
for example, actually ends up in the recycling waste stream as opposed to other waste streams. Because the
purpose of this model was to enable the user to evaluate a waste management process in myriad different ways
by inputting different collected or hypothetical data, an actual simulation was not run with this model, either. In
short, this model acts as a waste management tool for users relatively familiar with system dynamics
methodology and Vensim software.
Found Solutions and Conclusions
This section offers the specifications for the aforementioned two models in greater detail. Throughout this
section, conclusions and reflections about generated content are also offered.
To begin with, the concept model is documented in Figure 1 below:
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Figure 1. Concept Model of Restaurant Waste Management Efforts
As mentioned, no simulations were run with this model, however, many details were still outlined for the model
so that intended ideas could be communicated more clearly. First, the timestep for the concept model is in
weeks, so the meaning behind the first exogenous variable, “Average tons of waste generated per week,” is
pretty evident. A constant would be inputted into this variable, though one could also imagine “Average tons of
waste generated per week” to be a function of “Money spent on waste management,” as seeing waste
management bills may very well incentivize reductions in generated waste by the restaurant. It is worth noting
that this initial variable does not permit the breakdown of the waste stream into different kinds of waste (landfill
waste, recyclable waste, and compostable waste), instead, the model simply communicates the movement of
average tons of waste generated each week into “Waste sent to receptacle (tons),” which also has the units
“Tons/Week.” This endogenous variable is, in this model, equivalent to “Average tons of waste generated per
week,” though in a more robust model this would not necessarily be the case – that is, if the average tons of
waste generated per week was broken out into the three different waste streams, then it might be that the
average tons of recyclable waste generated per week, for example, is equal to the tons of waste sent to the
recycling receptacle each week. Again, the purpose of this endogenous variable is to communicate to
stakeholders that the tons waste that are sent to the receptacles is the waste for which the restaurant will be
financially responsible.
Finally, “Waste sent to receptacle (tons),” which has the units “Tons/Week,” feeds into “Money spent on waste
management,” the units of which are “Dollars.” “Money spent on waste management” is also affected by
“Weekly dumpster rent ($),” “Daily hauling fee ($),” “Tipping fee ($/ton),” and “Capacity of dumpster (tons).”
This stock accumulates the dollars spent each week on waste management based on the aforementioned
variables, receiving the values of the endogenous variable “Waste sent to receptacle (tons),” which is updated
during each timestep. The simulation time for the model is 52 weeks, equivalent to 1 year.
“Weekly dumpster rent ($)” is pretty self-explanatory; it denotes the amount paid per week by the restaurant in
order to continue renting a waste dumpster (most restaurants do not own dumpsters and instead choose to rent
them). “Daily hauling fee ($)” denotes the amount paid each day for the hauling of waste from the dumpster
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(the vast majority of restaurants do not have waste hauled multiple times per day), and “Tipping fee ($/ton)” is
defined as the amount of money charged per ton of waste collected by the hauler. “Capacity of dumpster” is in
tons and is used in the equation that establishes the “Money spent on waste management”:
Money spent on waste management = “Weekly dumpster rent ($)” + IF THEN ELSE( (“Waste sent to
receptacle(tons)”/7) <= ((0.5)*(“Capacity of dumpster (tons)”)), 4*(“Daily hauling fee ($)), 7*(“Daily
hauling fee ($)) ) + (“Tipping fee ($/ton)”)*(“Waste sent to receptacle (tons)”)
In other words, the money spent on waste management per week for a particular restaurant is equal to the
weekly dumpster rent plus the either 4 times the daily hauling fee or 7 times the daily hauling fee (the logic
states that, if the amount of waste sent to the receptacle each day is less than or equal to half of the capacity of
the dumpster, then a hauling of waste from the dumpster is needed only once every other day, and therefore the
daily hauling fee would only be assessed four times per week, rather than each day) plus the amount charged
weekly from tipping fees.
With the “Money spent on waste management” variable fully defined, the concept model is complete. It is
important to acknowledge the many limitations presented by this concept model: again, the model does not
model a restaurant with multiple waste streams, and, even if it did, then it would be ignoring the realities of
imperfect waste sorting. There is also no feedback loop that denotes how “Money spent on waste management”
might influence a reduction in “Average tons of waste generated per week.” Nevertheless, despite its
limitations, the concept model highlights both how waste moves as part of a waste stream, and it offers a very
realistic outline of how the costs of waste management are assessed. In short, this concept model can introduce
to stakeholders the ways in which system dynamics can be used in order to evaluate their waste streams.
Figure 2 shows the modeling tool developed after the concept model was created.
Figure 2. Restaurant Waste Management Modeling Tool
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As is apparent, this modeling tool is significantly more complicated than the concept model. The timestep is
still in weeks. The summation of the “Paying for landfilling waste,” “Paying for Recycling Waste,” and “Paying
for composting waste” variables make up the “Money spent on waste management” stock equation. Each of the
three variables contain some form of the previously outlined equation, where
Paying for landfilling waste = “Weekly landfill dumpster rent” + IF THEN ELSE( (Waste sent to landfill
receptacle)/7) <= ((0.5)*(Capacity of landfill dumpster)), 4*(“Daily hauling fee (landfill)), 7*(“Daily hauling
fee (landfill)) ) + (“Tipping fee ($/ton)”)*(Waste sent to landfill receptacle)
and where the “Paying for Recycling Waste” and “Paying for composting waste” variables are of the same
layout, save replacing variables like “Weekly landfill dumpster rent” with their sister variables (e.g., “Weekly
recycling dumpster rent” and “Weekly composting dumpster rent”). Thus, the cost calculations are essentially
of the same form for this model.
On a different note, the “Waste sent to receptacle (tons)” variable from the concept model has been broken out
into “Waste sent to landfill receptacle,” “Waste sent to recycling receptacle,” and “Waste sent to compost
receptacle” variables, each of which is impacted by the “Landfillable Waste generated weekly,” “Recyclable
Waste generated weekly,” and “Compostable Waste generated weekly” variables, the latter three of which make
up a modeling step not specified in the concept model (namely, that the average amount of waste generated per
week is made up of waste that should be landfilled, waste that should be recycled, and waste that should be
composted).
The calculations for the “Landfillable Waste generated weekly,” “Recyclable Waste generated weekly,” and
“Compostable Waste generated weekly” variables is easily calculated: a precursor variable, “Avg tons waste
generated per week,” is multiplied by any one of three exogenous variables: “Percent of waste that’s
landfillable,” “Percent of waste that’s recyclable,” and “Percent of waste that’s compostable” in order to get the
respective kind of waste (in tons) generated weekly. In other words,
Compostable Waste generated weekly = (Avg tons waste generated per week)*(Percent of waste that’s
compostable)
and the other two variables (“Landfillable Waste generated weekly” and “Recyclable Waste generated weekly”)
have complementary calculations.
Thus, in calculating “Waste sent to recycling receptacle,” for example, which has the units “Tons/Week,” a
particular summation is performed:
Waste sent to recycling receptacle = (Recyclable Waste generated weekly)*(Recycling to recycling matchup
(percent)”) + (Landfillable Waste generated weekly)*(“Landfill to recycling error (percent)”) + (Compostable
Waste generated weekly)*(“Compost to recycling error (percent)”)
where, “Recycling to recycling matchup (percent)” denotes the percentage of “Recyclable Waste generated
weekly” that actually ends up in the recycling container. “Landfill to recycling error (percent)” denotes what
percentage of “Landfillable Waste generated weekly” ends up in the recycling container. So, the values of
“Recycling to recycling matchup (percent),” “Recycling to landfill error (percent),” and “Recycling to compost
error” should then sum to 1 (or, “100%”).
There are many advantages to this modeling tool. To begin with, this model acts as a way for users who are
familiar with Vensim software to evaluate current waste management practices of a restaurant fairly accurately.
In particular, it allows consideration for how each of the major aspects of waste management (generation of
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waste, sorting of waste, and paying for waste) can impact overall waste management costs. Reflecting reality,
this tool allows the user to characterize the recyclability and compostability of the waste stream, and it allows
other such waste audit conclusions to be inputted into the model (that is, waste audits often produce insight into
the rate of error in sorting the waste stream into receptacles). The model also permits detailed specification of
the costs associated with each form of waste management; this differentiation is characteristic of most
municipalities’ waste management public policies – namely, that the cost of landfilling items tends to be
different than the cost of recycling items, which also tends to be different than the cost of composting items, so,
for instance, the tipping fee variables would all be different).
The model does have a few limitations. To begin with, actually utilizing the tool would require a significant
level of data, and this data would likely only be accurate if an actual waste audit was conducted. So, the use of
this model is limited by the user’s desired level of accuracy and/or experience with the waste stream. Moreover,
it is not specified how the accumulation of money spent on waste management might affect other variables in
the model, though it is worth noting that this modeling tool is not necessarily intended to produce such an
insight; instead, it could be thought of as a dynamic waste management cost calculator. Finally, the seasonal
variation of waste production is not addressed, which is a limitation because waste streams rarely look exactly
the same over the entire course of a year.
Simulations were not run on this model due to the lack of a comprehensive set of data for any particular
restaurant.
Website
The student’s website for this project can be found at http://seniordesignjdl.weebly.com
Accompanying Materials
Materials accompanying this report include the two Vensim models shown above, as well as the initial Senior
Design Project proposal that was written in the Fall 2013 semester.
Reflections
I have a few reflections about my work on my Senior Design Project. To begin with, I regret not being able to
complete my initial project. I felt as if I chose to come up with an innovative and useful project, made
meaningful connections with important stakeholders, and reasonably pursued my work collecting data during
the Fall semester. However, I cannot cast the blame for an incomplete project on my stakeholders; admittedly, I
did start my project at the beginning of October, and moreover, there were periods of time when I got
discouraged after receiving no responses to my survey, leaving me to ignore my Senior Design Project work for
a bit until I felt re-inspired. Additionally, I cannot really blame the stakeholders for not wanting to provide me
with internal, cost-related data; after all, I am a young adult and a part of an institution that they might not
entirely respect or like.
Some of my classmates have complained to me about the lack of direction provided for the Senior Design
Project class; I actually do not believe this lack of direction is a bad thing. In fact, I think it offers the
opportunity for students to be innovative and play to their strengths. I do think it might be handy to have ready
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some example projects that students can pursue if initial attempts fail or if students cannot think of project
ideas, but I sincerely appreciated the freedom offered by the Senior Design Project class.
Finally, I would say that I am somewhat disappointed in my own final products for this class. I do believe that I
my informal sustainability education, garnered from volunteer work with the Office of Sustainability during my
time at WashU and from summer internships, provided me with a knowledge base for my efforts. However, my
concept model felt elementary, and my waste management tool is limited by users’ familiarity with Vensim, a
software tool with which many restaurant managers probably are not familiar. Also, my efforts probably would
have been more difficult had I not been enrolled in ESE 408 this semester. So, I feel as if I synthesized tools at
my disposal, but I feel as if I did this in a relatively mediocre way that wasn’t especially innovative. Still, I
certainly appreciated the willingness of Professor Hovmand and Professor Mell to accommodate me and my
struggles to complete a project by the end of the year, and I did very much enjoy the work that I pursued, even
if the products were not exactly what I would have imagined or liked.
Thanks so much, Professors!
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APPENDIX A: Final Draft of Waste Management Survey for Restaurants in The Delmar Loop
The below survey was distributed to each restaurant location in The Delmar Loop as part of the initial
project effort
The Loop Waste Management Survey
Basic Information
Name of Food Business:
Business Contact Name:
Business Contact #:
Business Contact Email:
Extension:
I WOULD / WOULD NOT like to be kept up to date on this project’s progress by email (circle one)
Name of food service location’s building’s owner:
Building Owner’s Phone #:
Building Owner’s Email:
Trash
1) Please state the name and contact information of your trash contractor. This study requires data about the fees
for trash services, and your contractor can provide this information:
2) How many total outside trash receptacles are used by your business?
3) Do you share these receptacles? If so, with which businesses?
4) What is the volume and weight of your trash receptacle(s)?
5) How many days per week does your trash hauler empty these receptacles?
6) What monthly equipment rental costs are you charged for your receptacles?
Recycling
7) Please state the name and contact information of your recycling contractor. This study requires data about the
fees for recycling services, and your contractor can provide this information:
8) How many total outside recycling receptacles are used by your business?
9) Do you share these receptacles? If so, with which businesses?
10) What is the volume and weight of these receptacle(s)?
11) How many days per week does your recycling hauler empty these receptacles?
12) What monthly equipment rental costs are you charged for your receptacles?
Composting
13) Does your location currently compost any organic waste generated from business operations?
General
14) How much trash and recycling waste by weight does your location generate monthly, on average? Feel free
to estimate this number
15) Would your business be willing to be part of a sample of business waste audits that have to be conducted for
this survey? It’s projected that little effort would be required of staff to complete the audit:
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APPENDIX B: Letter Accompanying Delivered Copies of Waste Management Survey
The below letter was delivered to each recipient of the Waste Management Survey shown in Appendix A so
that the recipient understood why they were receiving the survey, as well as how to respond to the survey.
“Dear Food Service Business in The Loop,
My name is Jake Lyonfields, and I am an engineering student studying at Washington University. I
appreciate your time and consideration in reading this message.
Earlier this fall I contacted Mr. Joe Edwards because I am currently enrolled in a class at Washington
University called “ESE 499: Capstone Design Project,” the purpose of which is to encourage senior year
engineering students to apply their engineering education in a real world context. Specifically, the class requires
students to find a client organization that they can benefit in some way through a systems engineering project.
My systems engineering studies have been grounded in an applied mathematics approach that
emphasizes the modeling, analysis, and optimization of systems. So, when I contacted Mr. Edwards I proposed
using these skills to assess the economic feasibility of different waste management strategies for food service
businesses in The Loop. In particular, I suggested trying to build a model that reflected realistic constraints on
business’ current waste management practices. Analyzing this model would help me determine which waste
management strategies are optimal for differently sized businesses. It would also allow me to determine whether
practices not currently employed, such as composting organic waste, are economically viable waste
management options. These findings could be helpful for food service businesses like yours in making decisions
about improving waste management.
I’ve written a formal technical proposal for this modeling work, which Mr. Edwards has reviewed and
approved and which details how I plan to approach this work. I am happy to share it with any interested parties.
In addition to sharing all of this information with you, I’ve also written today to ask for your help. The
model I plan to build for my calculations is only valuable if it reflects current waste management practices for
food service businesses in The Loop. So, to be successful I will need to collect data from businesses like yours.
To streamline this data collection I’ve designed, with input from Mr. Edwards, a formal survey for food
service businesses in The Loop. It asks those who take it some questions about their business’s waste
management practices. The results will be kept strictly confidential, and the information from this survey will
only be used to help me make calculations with my model that are both reasonable and realistic. I ask your
consideration in completing this survey, which accompanies this message. While the survey may seem long, in
reality most questions need answers of one sentence or less, and some of the questions may not even apply to
your business.
Once you complete the survey it can be send to me through the mail with the address I have provided
below. An electronic version can also be sent to the email I’ve provided. Additionally, I can also stop by in
person to pick it up if that is most convenient.
Let me stress that I acknowledge what I’ve outlined here might seem a bit complicated. I have resolved
to be as available as I can be in order to answer questions by those who are interested in participating in this
endeavor. I will very readily respond via email if you have questions about the project or the survey, and I am
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more than happy to meet in person with anyone interested. Let me also stress that my interest in this effort is
purely academic in nature; I’m doing this because I enjoy my class and because I care about getting the correct
answer for your business. I firmly believe that the results of the proposed modeling project could very well
benefit your business, even if it is only through informing you of your waste management options.
Again, thank you so much for your time and consideration in taking the accompanying survey. I look
forward to your response, and I hope you have a wonderful day.
Sincerely,
Jake Lyonfields
(636)-484-4282
jlyonfields@wustl.edu
School of Engineering and Applied Science
Class of 2014
Washington University in St. Louis
6021 Pershing Avenue, Apt #3East
St. Louis, MO 63112”
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