Term Project: Waste Transfer Station Part I

7/31/2019 Term Project: Waste Transfer Station Part I

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MIDDLE EAST TECHNICAL UNIVERSITY

I E 3 7 2 S I M U L A T I O N

Term Project:

Waste Transfer Station

Part I

May 2011, Ankara

Group Name: Jelkala

Burcu Yzak

Fato lbi

Onur Ylmaz


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Table of Contents

PAGE

Table of Contents ............................................................................................................. 1

I. Introduction 2

II. Report ............................................................................................................. 3

1. Statement of the Problem ........................................................................................ 3

2. Structure of the Model ................................................................................. 3

2.1 Attributes .......................................................................................... 3

2.2 Variables .. 4

2.3 Modules .............................. 6

3. Model .. 8

3.1 Assumptions ................................................................................. 8

3.2 Input Analysis ....................................................................................... 9

3.2 Model Frame 10

3.3 Experiment Frame ............................ 16

4. Pilot Run Results .................................................... 20

4.1 Verification . 20

4.2 SIMAN Summary Report .. 22

4.3 Alternative Scenarios . 26

III. Conclusion 27


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I. Introduction

In the project, a transfer station for waste management is simulated. First of all, this report

includes statement of the problem which gives detailed information about the problem and the idea

behind the model construction. Then, structure of the model is given for showing the details by

giving the definitions of attributes and variables used, and explaining the distinguishable modules of

the model. Following these, the report includes assumptions made while constructing the model,

experiment and model frames and input analysis done in order to fit the given data of arrival times of

small trucks that transports loads to the transfer station. In addition to these, verification of the

model which is done by using SIMAN Summary Report can also be found. Finally, in order to satisfy

the goals of the management, initial thoughts on alternative scenarios are summarized which will be

studied in Part II of the project in detail.


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II. Report

1. Statement of the Problem

In this term project there is a problem environment which includes a transfer station for

waste management which operates continuously. The purpose of the station is to gather and then

decompose waste contents and transfer them to related warehouses. The main objective of the

transfer station is to operate with the limit of 180 minutes for keeping unit loads of remaining waste

at the station. Since, this is a business environment; the second aim is that the station must attain a

profit that pays back the investment in two years. In order to find any bottlenecks of the station that

prevents it from achieving these goals a simulation model is constructed. Our model approach is

based on answering How should a single load visit all the process areas in the station with using the

minimum computer time and memory? Therefore, model is constructed considering each process

area individually and then sending/receiving messages between them to form a flow. Identifying any

problems related to station, it is tried to answer the question How this station could reach these

goals? by developing alternative scenarios using the available resources and considering operational

changes.

2. Structure of the Model

2.1 Attributes

Attributes can be gathered into three groups as only related to single loads, related to

removal operations and the others.

PaperAmount Paper amount in a single load, which is uniformly distributed between 5 kg and

10 kg

PlasticAmount Plastic amount in a single load, which is uniformly distributed between 30 kg

and 40 kg

GlassAmount Glass amount in a single load, which is uniformly distributed between 10 kg and

20 kg

OrganicAmount Organic amount in a single load, which is uniformly distributed between 5 kg

and 20 kg

MetalAmount Metal amount in a single load, which is uniformly distributed between 1 kg and

5 kg

RestOfLoad Rest of the load which is calculated by subtracting sum of all above amountsfrom 100 kg, which is the weight of a single load


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RemovedPlasticAmount Amount of plastic removed (in kg) after plastic removal operations,

calculated using the initial plastic amount and efficiency of the

station

RemovedOrganicAmount Amount of organic removed (in kg) after organic removal operations,calculated using the initial organic amount and efficiency of the

station

RemovedGlassAmount Amount of glass removed (in kg) after glass removal operations,

calculated using the initial glass amount and efficiency of the station

RemovedPaperAmount Amount of paper removed (in kg) after paper removal operations,

calculated using the initial paper amount and efficiency of the

station

RemovedMetalAmount attribute is not used in the model since the entire metal amount is

removed in the metal gatherer.

ArrivalTime Arrival time of the small trucks which are carrying waste loads

ZipperArrival Time when all removal operations are completed and only remaining waste

is left in a single load

NumberofLoads Number of loads which is carried by the small trucks, calculated using

ANINT(UNIF(10,30)) function in Arena

OrganicLife Age of organic waste when the small trucks arrive at the station, uniformly

distributed between 1 and 2 days

OrganicVsCompost Decides whether the organic waste removed will be counted as organic or

as compost, assigned by checking the organic life when the trucks arrive at

the station for collecting organic waste amount.

2.2 Variables

All variables end with -RemovedOnHand are used to trace the storage level of the related

content. This variable is used in order to check whether or not the sending warehouse limit is

reached for the related content.

All variables tabulated as TotalXRemoved are used in order to trace the total amount of

removal for the related content. With the same approach, all variables starting with EarningsOn-

are used to trace the sale revenues made on the related content.


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MetalRemovedOnHand Amount of metal removed (in kg) and stored in metal storage area

TotalMetalRemoved Total amount of metal removed (in kg) in the system

EarningsOnMetal Total profit made on metal removal (in $)

PlasticRemovedOnHand Amount of plastic removed (in kg) and stored in glass storage area

TotalPlasticRemoved Total amount of plastic removed (in kg) in the system

EarningsOnPlastic Total profit made on plastic removal (in $)

GlassRemovedOnHand Amount of glass removed (in kg) and stored in glass storage area

TotalGlassRemoved Total amount of glass removed (in kg) in the system

EarningsOnGlass Total profit made on glass removal (in $)

TotalPaperRemoved Total amount of paper removed (in kg) in the system

EarningsOnPaper Total profit made on paper removal (in $)

TotalOrganicRemoved Total amount of organic removed (in kg) in the system

OrganicSent Total amount of organic waste (in kg) which is sent as organic material

CompostSent Total amount of organic waste (in kg) which is sent as compost

EarningsOnOrganic Total profit made on organic material (in $)

EarningsOnCompost Total profit made on compost (in $)

RemainingWasteOnHand Amount of remaining waste removed (in kg) and stored in the

storage area

TotalRemainingWasteRemoved Total amount of remaining waste removed (in kg) in the system

CostOfLandFilling Total cost of disposing the remaining waste to landfill area (in $)

SellingPrice 1 dimensional array which holds all selling prices of all types of contents (in $ / kg)

LandfillCost Cost of disposing one kg of remaining waste to the landfill area ($ 0.32 /kg)

ConveyorSize Total available space limit on the conveyor (9 units as given)

DeportingTime Time it takes to unload one load of waste from truck (1.2

minutes as given)

WarehouseSendingLimit 1 dimensional array which holds the threshold amount (in kg) of

different types of contents for sending warehouse

NumberOfManualProcessArea Number of manual process areas in the system (2 areas as

given)

WorkersIn1 Number of workers in the first group in manual process area (10

workers as given)

WorkersIn2 Number of workers in the second group in manual process area

(10 workers as given)


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2.3 Modules

In this part, distinguishable parts of the simulation model are described for clarity:

Small Trucks Porting:

First of all, input analyzer is used to fit the past data of small truck interarrivals to a

distribution and the best distribution is found. After a truck is created, number of loads in the truck

and age of the organic material in the loads of the truck are assigned according to distributions

specified in the project. Then these trucks are sent to port queue to wait for a port to become

available. When a port becomes available the truck seizes the port and unloads the waste it carries

which takes 1.2minutes timesNumber of loads in the truck.

Transforming into Loads and Assigning Waste Content:

Duplicate block is used to transform the trucks into loads and then paper, metal, plastic,

glass and organic amounts are assigned to each load according to distributions specified. Then by

subtracting these amounts from 100 kg, remaining waste amount is found and total loads entering

the system is counted to be able to trace the entities after the model is run.

Crane:

After being counted, loads enter the crane queue to wait for the crane to become available.

As soon as the crane becomes available it picks up a load and waits for the conveyor to become

available, i.e. have an available space. The crane counter counts the number of loads entering the

crane. If the counter is less than 10, namely for the first 9 loads, then the crane puts the load directly

on the conveyor. On the other hand, if the counter is greater than 10, then availability of the

conveyor is checked and the load is put on the conveyor after conveyor becomes available.

Conveyor:

If the entering load is not the 9th load on the conveyor, then the load enters the conveyors

entrance dummy queue waiting for a signal given when number of loads on the conveyor becomes

nine. If the entering load is the 9th load on conveyor then it gives a signal and the first load entered

the conveyors entrance dummy queue is released. If the metal gatherer is empty then the conveyor

drops the load. Otherwise, the load enters the conveyors exit dummy queue waiting for a signal


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given when the metal gatherer becomes available. After this signal comes, conveyor drops the load

and the load seizes the metal gatherer.

Metal Gatherer:

The duration of the gathering process is assigned as specified in the project. If a manual

process area is available then the load releases the metal gatherer by giving signal to the conveyor

that releases a load from the conveyors dummy queue. If all manual process areas are busy, then

the load enters DummyQ2 waiting for a signal which is given when an area becomes available.

After the load releases the metal gatherer, Total Metal Removed and Metal Removed on Hand

variables are updated. If metal removed on hand exceeds the warehouse limit, then sent to

warehouse by decreasing the metal removed on hand to zero and releasing manual process area.

Otherwise the load just releases the manual process area and then it is counted for the number of

loads entering the manual process area.

Manual Process Area:

Using the given formulas in the project, removal time of materials by each worker group and

percent removed for each material are calculated once and Expressions element is used in order to

let the model run efficiently.

Plastic and Glass Removal:

After plastic and glass are removed, Plastic Removed on Hand and Total Plastic Removed

variables; and Removed Plastic Amount attribute are updated. If plastic removed on hand exceeds

the warehouse limit, then plastic removed on hand is decreased to zero, total revenue is calculated

and plastic is sent to warehouse. With the same approach used in the plastic removal, glass removal

operations, variable and attribute updates are conducted.

Paper and Organic Removal:

After paper and organics are removed, Removed Paper Amount attributes and Total

Paper Removed variables are updated and paper is sold and total revenue is calculated. Then

Removed Organic Amount and Total Organic Removed are updated and manual process area is

released by giving signal to metal gatherer after counting the number of loads leaving the manual

process area. Then the load is duplicated, one of them goes to zipper and one of them enters to the

organic waste queue which waits organic trucks that come once in 36 hours. If age of the organic is


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more than 3 (assigned by using the attribute Organic Life and the tally that calculates the time

passed after the load entered the system) then it becomes compost and sold, otherwise it is sold as

an organic. Then total revenues earned from compost and organic are calculated.

Zipper:

After Remaining Waste On Hand is updated, if it is less than 100 kg then the load enters the

End Queue waiting for a signal coming when remaining waste on hand becomes greater than 100.

If remaining waste on hand is greater than 100, then a signal is given so loads waiting in the End

Queue are released and disposed. At his time the zipper is seized and a 2 minute-delay occurs. After

Total Remaining Waste Removed is calculated, zipper is released and the cost of disposing the

remaining waste to the landfill area is calculated.

3. Model

3.1 Assumptions

These assumptions are made when a simulation model is constructed for the given problem:

First of all, when plastic, glass or paper removals are to leave the station to another

warehouse, it is assumed that the trucks can carry all the removals which is accumulated. For

instance, considering plastic amount, when accumulated level reaches 1000, all plastic amount will

be carried without any consideration about how larger the accumulated value than 1000. Since

contents of single loads, which are given in uniform distribution levels, are very small when

compared to 1000, it is acceptable to assume that all accumulated value can be carried at once.

Secondly, since in the first part of the project it is only asked to model this environment,

number of workers and resources are taken as given and they are only considered in the alternative

scenarios.


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Thirdly, since any length of the simulation is not given, and the steady state does not seem

possible with given system features, the replication length is chosen according to where we run out

of entities due to ARENAs license agreement and limitations.

Fourthly, past 500 interarrival data for trucks are used for calculating the interarrival time of

the trucks in the following planning horizon. In other words, it is assumed that in the following

periods, trucks will be arriving with the theoretical distribution which is calculated from past data.

3.2 Input Analysis

As mentioned in the assumptions above, small truck arrivals are found by using the past data

of 500 interarrivals. Using the given .dstfile in Arenas Input Analyzer following output is retrieved:

Distribution Summary

Distribution: Gamma

Expression: GAMM(27.8, 1.07)

Square Error: 0.001411

Function Sq Error

-------------------------------

Gamma 0.00141

Weibull 0.0016

Erlang 0.00223

Exponential 0.00223

Beta 0.00361

Lognormal 0.006Normal 0.0483

Triangular 0.0791

Uniform 0.123

Gathered from the output of Arena Input Analyzer

As can be seen from the output, the best theoretical distribution which fits to given past data

is Gamma distribution with the given parameters. Therefore, interarrival distribution for small trucks

is used as what is taken from Input Analyzers output.


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3.2 Model Frame

0$ CREATE, 1:GAMM(27.8,1.07):MARK(ArrivalTime):NEXT(64$);

64$ COUNT: SmallTruckEnter,1;1$ ASSIGN: NumberofLoads=ANINT(UNIF(10,30)):

OrganicLife=UNIF(24*60,48*60);

4$ QUEUE, PortQ;5$ SEIZE, 1,Other:Port,1:NEXT(2$);

2$ DELAY: DeportingTime*NumberofLoads,,Other:NEXT(6$);

6$ RELEASE: Port,1;3$ DUPLICATE: NumberofLoads-1,ContentAssignment:NEXT(ContentAssignment);

ContentAssignment ASSIGN: PaperAmount=UNIF(5,10):MetalAmount=UNIF(1,5):PlasticAmount=UNIF(30,40):GlassAmount=UNIF(10,20):OrganicAmount=UNIF(5,20);

25$ ASSIGN: RestOfLoad=100-(PlasticAmount+PaperAmount+MetalAmount+GlassAmount+OrganicAmount);

36$ COUNT: LoadsEnteredSystem,1;55$ QUEUE, CraneQ;8$ SEIZE, 1,Other:

Crane,1:NEXT(37$);

37$ DELAY: 2,CraneStorage,Other:NEXT(56$);

56$ COUNT: CraneC,1;


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9$ BRANCH, 1:If,NC(CraneC)=8,CraneDummy,Yes;

CraneRelease RELEASE: Crane,1;Conveyor QUEUE, Conveyor;58$ SEIZE, 1,Other:

ConveyorR,1:NEXT(ConveyorBranch);

ConveyorBranch BRANCH, 1:If,NR(ConveyorR)==9,Equal9,Yes:Else,Dummyy,Yes;

Equal9 SIGNAL: 9;Dummyy QUEUE, Dummy;54$ WAIT: 9,1:NEXT(CheckMetGath);

CheckMetGath BRANCH, 1:If,NR(MetalGatherer)==0,ReleaseConveyor,Yes:If,NR(MetalGatherer)==1,ConvDummy,Yes;

ReleaseConveyor RELEASE: ConveyorR,1;MetalGath SEIZE, 1,Other:

MetalGatherer,1:NEXT(7$);

7$ DELAY: UNIF(2,2+MetalAmount),,Other:NEXT(13$);

13$ BRANCH, 1:

If,NR(ManualProcessArea)


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Always,ManualProcess,Yes:If,MetalRemovedOnHand>=WarehouseSendingLimit(1),MetalWarehouse,Yes;

ManualProcess SEIZE, 1,Other:ManualProcessArea,1:NEXT(34$);

34$ COUNT: ManuelEnter,1;14$ DELAY: DelayExp*(PlasticAmount+GlassAmount),,Other:NEXT(26$);

26$ ASSIGN:PlasticRemovedOnHand=PlasticRemovedOnHand+PlasticAmount*EfficiencyExp(1):

RemovedPlasticAmount=PlasticAmount*EfficiencyExp(1):

TotalPlasticRemoved=TotalPlasticRemoved+PlasticAmount*EfficiencyExp(1);15$ BRANCH, 2:

If,PlasticRemovedOnHand>=WarehouseSendingLimit(2),PlasticWarehouse,Yes:Always,RemoveGlass,Yes;

PlasticWarehouse ASSIGN:EarningsOnPlastic=EarningsOnPlastic+PlasticRemovedOnHand*SellingPrice(2);27$ ASSIGN: PlasticRemovedOnHand=0;50$ DISPOSE: No;

RemoveGlass ASSIGN: TotalGlassRemoved=TotalGlassRemoved+GlassAmount*EfficiencyExp(2):RemovedGlassAmount=GlassAmount*EfficiencyExp(2):GlassRemovedOnHand=GlassRemovedOnHand+GlassAmount*EfficiencyExp(2);

16$ BRANCH, 2:If,GlassRemovedOnHand>=WarehouseSendingLimit(2),GlassWarehouse,Yes:Always,PaperOrganic,Yes;

GlassWarehouse ASSIGN:EarningsOnGlass=EarningsOnGlass+((GlassRemovedOnHand)*SellingPrice(3));30$ ASSIGN: GlassRemovedOnHand=0;52$ DISPOSE: No;


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PaperOrganic DELAY: DelayExp*(PaperAmount+OrganicAmount),,Other:NEXT(31$);

31$ ASSIGN: RemovedPaperAmount=PaperAmount*EfficiencyExp(3):TotalPaperRemoved=TotalPaperRemoved+PaperAmount*EfficiencyExp(3);

32$ ASSIGN:EarningsOnPaper=EarningsOnPaper+((RemovedPaperAmount)*SellingPrice(4)):NEXT(RemoveOrganic);

RemoveOrganic ASSIGN: RemovedOrganicAmount=OrganicAmount*EfficiencyExp(4):

TotalOrganicRemoved=TotalOrganicRemoved+OrganicAmount*EfficiencyExp(4);35$ COUNT: ManuelLeave,1;18$ RELEASE: ManualProcessArea,1;47$ TALLY: TimeAtStation,INT(ArrivalTime),1;19$ SIGNAL: 8;17$ DUPLICATE: 1,Zipper:NEXT(OrganicWasteQ);

OrganicWasteQ QUEUE, OrganicWasteQueue;39$ WAIT: 1,NQ(OrganicWasteQueue);43$ ASSIGN: OrganicVsCompost=((OrganicLife+TNOW-ArrivalTime)


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RemainingWasteOnHand+RestOfLoad+(PlasticAmount-RemovedPlasticAmount)+(GlassAmount-RemovedGlassAmount)+(PaperAmount-RemovedPaperAmount)+(OrganicAmount-RemovedOrganicAmount)

:MARK(ZipperArrival);20$ BRANCH, 1:

If,RemainingWasteOnHand>=100,Zip,Yes:Else,DisposalOfLoadEntity,Yes;

Zip ASSIGN: RemainingWasteOnHand=RemainingWasteOnHand-100;63$ SIGNAL: 55;22$ SEIZE, 1,Other:

Zipper,1:NEXT(23$);

23$ DELAY: 2,,Other:NEXT(49$);

49$ ASSIGN: TotalRemainingWasteRemoved=TotalRemainingWasteRemoved+100;24$ RELEASE: Zipper,1;48$ TALLY: TimeWhenZipped,INT(ArrivalTime),1;60$ TALLY: ZippingInterval,TNOW-ZipperArrival,1;33$ ASSIGN:CostOfLandfilling=CostOfLandfilling+100*LandfillCost:NEXT(DisposalOfLoadEntity);

DisposalOfLoadEntity QUEUE, EndQueue;61$ WAIT: 55;62$ TALLY: ZippingInterval,INT(ZipperArrival),1;21$ DISPOSE: No;

MetalWarehouse ASSIGN:EarningsOnMetal=EarningsOnMetal+(MetalRemovedOnHand)*SellingPrice(1);29$ ASSIGN: MetalRemovedOnHand=0;51$ DISPOSE: No;

DummyQ2 QUEUE, DummyQ2;12$ WAIT: 8,1:NEXT(ReleaseMetalGatherer);


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ConvDummy QUEUE, ConveyorDummy;53$ WAIT: 7,1:NEXT(ReleaseConveyor);

CraneDummy QUEUE, DummyQ;57$ SEIZE, 1,Other:

ConveyorR,1:NEXT(59$);

59$ RELEASE: Crane,1:NEXT(ConveyorBranch);

38$ CREATE, 1,36*60:36*60:NEXT(40$);

40$ SIGNAL: 1,NQ(OrganicWasteQueue);42$ COUNT: OrganicTruckLeft,1;41$ DISPOSE: No;


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3.3 Experiment Frame

PROJECT, "IE372 - Term Project","Jelkala",,Yes,No,No,No,No,No,No,No,No,No,No;

ATTRIBUTES: PlasticAmount,DATATYPE(Real):NumberofLoads,DATATYPE(Real):OrganicLife,DATATYPE(Real):OrganicVsCompost,DATATYPE(Real):RemovedPaperAmount,DATATYPE(Real):PaperAmount,DATATYPE(Real):RestOfLoad,DATATYPE(Real):GlassAmount,DATATYPE(Real):RemovedOrganicAmount,DATATYPE(Real):RemovedGlassAmount,DATATYPE(Real):ArrivalTime,DATATYPE(Real):OrganicAmount,DATATYPE(Real):MetalAmount,DATATYPE(Real):RemovedPlasticAmount,DATATYPE(Real):ZipperArrival,DATATYPE(Real);

STORAGES: CraneStorage;

VARIABLES: 8,MetalRemovedOnHand,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):9,TotalMetalRemoved,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):10,EarningsOnMetal,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):11,PlasticRemovedOnHand,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):12,TotalPlasticRemoved,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):13,EarningsOnPlastic,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):14,GlassRemovedOnHand,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):


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15,TotalGlassRemoved,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):16,EarningsOnGlass,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):17,TotalPaperRemoved,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):18,EarningsOnPaper,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):19,TotalOrganicRemoved,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):20,OrganicSent,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):21,CompostSent,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):22,EarningsOnCompost,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):23,EarningsOnOrganic,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):24,TotalRemainingWasteRemoved,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):25,RemainingWasteOnHand,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):26,CostOfLandFilling,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real):ConveyorSize,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real),9:SellingPrice(6),CLEAR(System),CATEGORY("None-

None"),DATATYPE(Real),2.55,0.05,0.76,0.28,0.17,0.10:LandfillCost,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real),0.32:DeportingTime,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real),1.2:WarehouseSendingLimit(2),CLEAR(System),CATEGORY("None-

None"),DATATYPE(Real),300,1000:NumberOfManualProcessArea,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real),2:WorkersIn1,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real),10:WorkersIn2,CLEAR(System),CATEGORY("None-None"),DATATYPE(Real),10;

QUEUES: EndQueue,FirstInFirstOut,,AUTOSTATS(Yes,,):OrganicWasteQueue,FirstInFirstOut,,AUTOSTATS(Yes,,):

ConveyorDummy,FirstInFirstOut,,AUTOSTATS(Yes,,):Dummy,FirstInFirstOut,,AUTOSTATS(Yes,,):DummyQ,FirstInFirstOut,,AUTOSTATS(Yes,,):PortQ,FirstInFirstOut,,AUTOSTATS(Yes,,):Conveyor,LowValueFirst(ArrivalTime),,AUTOSTATS(Yes,,):DummyQ2,FirstInFirstOut,,AUTOSTATS(Yes,,):CraneQ,FirstInFirstOut,,AUTOSTATS(Yes,,);


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RESOURCES:1,CompostTruck,Capacity(1),,Stationary,COST(0.0,0.0,0.0),,AUTOSTATS(Yes,,),EFFICIENCY(1,):

2,OrganicTruck,Capacity(1),,Stationary,COST(0.0,0.0,0.0),,AUTOSTATS(Yes,,),EFFICIENCY(1,):4,Port,Capacity(2),,Stationary,COST(0.0,0.0,0.0),,AUTOSTATS(Yes,,),EFFICIENCY(1,):5,Crane,Capacity(1),,Stationary,COST(0.0,0.0,0.0),,AUTOSTATS(Yes,,),EFFICIENCY(1,):

6,Worker,Capacity(20),,Stationary,COST(0.0,0.0,0.0),,AUTOSTATS(Yes,,),EFFICIENCY(1,):

7,ManualProcessArea,Capacity(2),,Stationary,COST(0.0,0.0,0.0),,AUTOSTATS(Yes,,),EFFICIENCY(1,):

8,Zipper,Capacity(1),,Stationary,COST(0.0,0.0,0.0),,AUTOSTATS(Yes,,),EFFICIENCY(1,):

9,MetalGatherer,Capacity(1),,Stationary,COST(0.0,0.0,0.0),,AUTOSTATS(Yes,,),EFFICIENCY(1,):

ConveyorR,Capacity(9),,Stationary,COST(0.0,0.0,0.0),,AUTOSTATS(Yes,,),EFFICIENCY(1,);

COUNTERS: LoadsEnteredSystem,,Replicate:ManuelLeave,,Replicate,"cikanlar.dat":SmallTruckEnter,,Replicate:ManuelEnter,,Replicate:CraneC,,Replicate:OrganicTruckLeft,,Replicate;

TALLIES: TimeWhenZipped:

TimeWhenOrganicOrCompost:ZippingInterval:TimeAtStation,"TimeAtStation.dat";

DSTATS: 8,TotalMetalRemoved:9,MetalRemovedOnHand:10,EarningsOnMetal:11,TotalPlasticRemoved:


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12,PlasticRemovedOnHand:13,EarningsOnPlastic:14,TotalGlassRemoved:15,GlassRemovedOnHand:16,EarningsOnGlass:17,TotalPaperRemoved:18,EarningsOnPaper:19,TotalOrganicRemoved:20,TotalRemainingWasteRemoved:21,RemainingWasteOnHand:22,CostOfLandfilling:24,CompostSent:25,EarningsOnCompost:26,OrganicSent:27,EarningsOnOrganic:45,NC(ManuelLeave),,"outs.dat":NQ(OrganicWasteQueue):NSTO(CraneStorage):NQ(CraneQ):NQ(Dummy):NR(ConveyorR):NR(MetalGatherer):NR(ManualProcessArea):NR(Crane):NQ(Conveyor);

OUTPUTS: NC(ManuelLeave),"outputdavg.dat";

REPLICATE, 1,0.0,(24*60*30),Yes,Yes,0.0,,,24.0,Minutes,No,No,,,No,No;

EXPRESSIONS: DelayExp,DATATYPE(Native),0.12/LOG(11):EfficiencyExp(4),DATATYPE(Native),(1-(0.6/10)),(1-(1.8/10)),(1-(0.3/10)),(1-

(0.7/10));


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4. Pilot Run Results

4.1 Verification

Number of trucks arrived to facility and the loads flowing in the facility should be

consistent:

SmallTruckEnter x Expected Number of Loads = LoadsEnteredSystem

Theoretical Output Results Explanation

Number of trucks arrived (1) 1420

Expected number of loads per truck (2) 20 E[UNIF (10,30)]

Expected number of loads ported (3) 28400 28237 (1) x (2)

Number of single loads entered the

waste removal area10012

Every load entered the system should be traceable:

LoadsEnteredSystem = NQ(CraneQ) + NR(Crane) + NR(Conveyor) + NR(MetalGatherer) +

NR(ManualProcessArea) + Number of entities left the station

28237 = 18224 + 1 + 9 + 1 + 2 + 10000

Our model works correctly, in other words our model is valid to investigate such system,

because the results are consistent with the statistical expectations before any simulation run:


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TheoreticalOutputResults

Explanation

Number of trucks arrived (1) 1420

Expected number of loads per truck(2)

20 E[UNIF (10,30)]

Expected number of loads ported(3)

28400 28237 (1) x (2)

Number of single loads entered thewaste removal area (4)

10012

Expected total metal amountremoved (5)

30036 30117 (4) x E[UNIF(1,5)]

Expected total plastic amountremoved (6)

329394,8 329030 (4) x E[UNIF(30,40)] x (1-0,6/10)

Expected total organic removed (7) 116389,5 116160 (4) x E[UNIF(5,20)] x (1-0,7/10)

Expected organic shipped towarehouse (8)

93111,6 4776,2 (7) x E(UNIF(1,2)+UNIF(0,1.5)


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4.2 SIMAN Summary Report

ARENA Simulation Results

Department of Industrial Engineering

Summary for Replication 1 of 1

Project: IE372 Run execution date : 5/19/2011

Analyst: Jelkala Model revision date: 5/19/2011

Replication ended at time : 43200.0 Minutes

Base Time Units: Minutes

TALLY VARIABLES

Identifier Average Half Width Minimum Maximum Observations

_______________________________________________________________________________________________

TimeWhenZipped 13502. (Corr) 58.987 27288. 3286

TimeWhenOrganicOrCompost 14579. (Corr) 1432.8 27986. 10000

ZippingInterval 7.1233 .03084 .19669 23.740 13283

TimeAtStation 13500. (Corr) 49.726 27296. 10000


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DISCRETE-CHANGE VARIABLES

Identifier Average Half Width Minimum Maximum Final Value

___________________________________________________________________________________________________

TotalMetalRemoved 15034. (Corr) .00000 30117. 30117.

MetalRemovedOnHand 148.89 2.0517 .00000 299.99 254.26

EarningsOnMetal 37957. (Insuf) .00000 76151. 76151.

TotalPlasticRemoved 1.6426E+05 (Corr) .00000 3.2903E+05 3.2903E+05

PlasticRemovedOnHand 491.25 2.4305 .00000 999.92 915.30

EarningsOnPlastic 8188.5 (Corr) .00000 16405. 16405.

TotalGlassRemoved 61346. (Corr) .00000 1.2301E+05 1.2301E+05

GlassRemovedOnHand 495.85 5.1399 .00000 999.79 162.08

EarningsOnGlass 46246. (Insuf) .00000 93362. 93362.

TotalPaperRemoved 36492. (Corr) .00000 73003. 73003.

EarningsOnPaper 10217. (Corr) .00000 20440. 20440.

TotalOrganicRemoved 58103. (Corr) .00000 1.1616E+05 1.1616E+05

TotalRemainingWasteRemoved 1.6405E+05 (Corr) .00000 3.2860E+05 3.2860E+05

RemainingWasteOnHand 49.900 .51058 .00000 99.990 84.056


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CostOfLandfilling 52497. (Corr) .00000 1.0515E+05 1.0515E+05

CompostSent 50680. (Insuf) .00000 1.1139E+05 1.1139E+05

EarningsOnCompost 5068.0 (Insuf) .00000 11138. 11138.

OrganicSent 4531.0 (Insuf) .00000 4776.2 4776.2

EarningsOnOrganic 770.28 (Insuf) .00000 811.96 811.96

NC(ManuelLeave) 4993.2 (Corr) .00000 10000. 10000.

NQ(OrganicWasteQueue) 249.83 (Corr) .00000 504.00 .00000

NSTO(CraneStorage) .46355 .00100 .00000 1.0000 1.0000

NQ(CraneQ) 8809.7 (Corr) .00000 18226. 18224.

NQ(Dummy) 7.9945 (Corr) .00000 8.0000 8.0000

NR(ConveyorR) 8.9936 (Corr) .00000 9.0000 9.0000

NR(MetalGatherer) .99911 (Corr) .00000 1.0000 1.0000

NR(ManualProcessArea) 1.8678 .00552 .00000 2.0000 2.0000

NR(Crane) .99953 (Corr) .00000 1.0000 1.0000

NQ(Conveyor) .00000 (Insuf) .00000 .00000 .00000


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COUNTERS

Identifier Count Limit

_____________________________________________________________

LoadsEnteredSystem 28237 Infinite

ManuelLeave 10000 Infinite

SmallTruckEnter 1420 Infinite

ManuelEnter 10002 Infinite

CraneC 10012 Infinite

OrganicTruckLeft 20 Infinite

OUTPUTS

Identifier Value

_____________________________________________________________

NC(ManuelLeave) 10000.

Simulation run time: 0.02 minutes.

Simulation run complete.


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4.3 Alternative Scenarios

According to our simulation outputs and observations, the main problem is the huge

accumulation in the storage area before the crane. Given the situation, the time limit of 180 minutes

seems unattainable. Although, true utilization of the crane is near 50%, there is a large queue

preceding it. This is because; succeeding stations works at almost full utilization levels. Therefore,

main purpose of the improvements that could be done on the system should be about increasing

resource capacities.

Rather than increasing number or capacities of all resources at once, considering step by step

improvements is a more advisable way due to managements consideration about the compensation

of the investment within two years. Namely, for instance, one should consider the effects of hiring

more workers for the manual process area and duplicating the numbers of the manual process areas

by considering both the additional income that firm generate and the cost of the implementation for

the company in two cases. The main benefit of increasing number of workers will be that the more

workers will gather more collected waste in less time, due to efficiency and time expressions used in

the model. Therefore, increase in the worker level at different process areas could yield different

profit margins and this should also be considered.

Moreover, there are such details that can be missed. Such as, increasing numbers of or the

capacity of conveyors would not be so effective because they are succeeded by a station (metal

gatherer) that operates at near full capacity. Also, considering buying a conveyor and a metal

gatherer could be more effective rather than just buying one of them. Therefore, such relations

among the resources of the facility should be taken into account while deciding on the policy that will

be followed.

In addition to those resource capacity improvements, some other options could be beneficial

for the profit margins of the firm. Firstly, for instance, separation of the organic could be done at a

more upstream station if it is possible, so that the rate of organic waste that turning into compost,

which has a lower profit margin, is reduced and sales to the power plant would be increase.

Considering organic waste, although it is not mentioned, decreasing interarrival time of the trucks


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could also increase the level of organic waste sent to power plant. Secondly, it is obvious that the

station operates continuously but process areas operate discretely, in other words, one load at one

time. If this discrete flow could change into a more continuous flow after loads are entered to

system, station could benefit more. For instance, when second group of workers are collecting, the

first group of workers are idle in manual process area.

III. Conclusion

To conclude, it could be stated that the aim of the Part I of the project was to find alternative

scenarios to the given problem by using a simulation model and its output. With this aim, this report

gives the problem situation and then the structure of the model which is constructed to simulate the

problem environment. Frames and outputs of the model with the assumptions are presented and in

the next part, the model is tried to be verified with statistical and numerical methods. In Part II of the

project, the alternative scenarios which are given in the last part of this report will be examined and

the optimal one will be chosen.

Term Project: Waste Transfer Station Part I

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Transcript of Term Project: Waste Transfer Station Part I