Worldwide Paper Company Essay

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Worldwide Paper Company Essay
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  • University/College:
    University of Chicago

  • Type of paper: Thesis/Dissertation Chapter

  • Words: 3829

  • Pages: 15

Worldwide Paper Company

Abstract—Coupling Vehicular Ad Hoc Networks (VANETs) with wired networks such as the Internet via access points creates a difficult mix of highly mobile nodes and a static infrastructure. In order to evaluate the performance of typical ad hoc routing protocols—in particular, we used Dynamic MANET On Demand (DYMO)—in such VANET scenarios, we combined microsimulation of road traffic and event-driven network simulation. Thus, we were able to analyze protocols of the Internet protocol suite in VANET scenarios with highly accurate mobility models. Varying parameters of DYMO for a multitude of traffic and communication scenarios helped point out approaches for improving the overall performance and revealed problems with the deployment. It could be shown that in realistic scenarios, even for medium densities of active nodes and low network load, overload behavior leads to a drastic decrease of the perceived network quality. Cross-layer optimization of transport and routing protocols therefore seems highly advisable.

I. NTRODUCTION

Recent research in the area of Vehicular Ad Hoc Networks (VANETs) was primarily focused on the development and
the evaluation of highly specialized protocols, e.g. for the exchange of position information or hazard warnings between cars. Significantly less work dealt with evaluating the use of existing Internet protocols, along with standard hard- and software, to create and maintain VANETs and couple these networks with the Internet. The Mobile Ad Hoc Network (MANET) working group of the Internet Engineering Task Force (IETF) develops standards for routing in dynamic networks of both mobile and static nodes. One protocol currently in the working group’s focus is Dynamic MANET On Demand (DYMO). It was conceived as successor to the popular Ad Hoc on Demand Distance Vector (AODV) routing protocol. Its use in the context of VANETs has already been extensively investigated. The DYMO protocol draft expressly provides for the coupling of a MANET with the Internet, which makes an evaluation of communication connections between mobile nodes and static infrastructure especially attractive. A car taking part in a MANET scenario could already establish such connections in reach of one of an ever growing number of public hotspots while driving in the city, and a deployment of access points along highways in the near future seems feasible. Apparently, this coupling of MANET and Internet is especially attractive for road users if it allows the utilization of virtually all existing resources of the Internet without relying on expensive dedicated channels provided by a cellular network.

Routing information dissemination in AODV and DYMO

In this work, the feasibility, the performance, and the limits of ad hoc communication using DYMO were evaluated and potentials for optimizing the deployed transport and routing protocols were investigated. Special care was taken to provide realistic scenarios of both road traffic and network usage. This was accomplished by simulating a variety of such scenarios with the help of two coupled simulation tools. A microsimulation environment for road traffic supplied vehicle movement information, which was then fed into an event-driven network simulation that configured and managed a MANET model based on this mobility data. The protocols of the transport, network, data link, and physical layers were provided by welltested implementations for the network simulation tool, while MANET routing was performed by our own implementation of DYMO.

II. DYNAMIC MANET O N D EMAND (DYMO)

DYMO is a new reactive (on demand) routing protocol, which is currently developed in the scope of the IETF’s MANET working group. DYMO builds upon experience with previous approaches to reactive routing, especially with the routing protocol AODV. It aims at a somewhat simpler design, helping to reduce the system requirements of participating nodes, and simplifying the protocol implementation. DYMO retains proven mechanisms of previously explored routing protocols like the use of sequence numbers to enforce loop freedom. At the same time, DYMO provides enhanced features, such as covering possible MANET–Internet gateway scenarios and implementing path accumulation as depicted in Figure 1. Besides route information about a requested target, a node will also receive information about all intermediate nodes of a newly discovered path. Therein lies a major difference between DYMO and AODV, the latter of which only generates route table entries for the destination node and the next hop,

III. S IMULATION T OOLS

For the selection of a suitable traffic simulation tool, two aspects had to be weighed against each other. Clearly, the
underlying traffic model was to be as simple and comprehensible as possible, so that reproducible results could be obtained. On the other hand, the simulation model needed to be complex enough to produce realistic patterns, which—as has been shown in related work—greatly influence the quality of results obtained from overlaid network simulations. Microsimulation of road traffic was performed by an adaptation of TrafficApplet 1 , an open source traffic microsimulation tool that provides an accurate model of microscopic driver behavior, as opposed to the still common simplistic or proprietary behavior models. It implements the microsimulation models IDM and MOBIL to calculate longitudinal and lateral movement, respectively. The behavior of simulated vehicles can be configured with simple parameters like “desired velocity” or “comfortable acceleration”, which were used to model two different types of road users.

Nodes of type Truck traveled at a maximum speed of 22.2 m/s (approx. 80 km/h, 50 mph) and made up 20 % of the vehicles simulated. The remaining 80 % of vehicles were of type Car and traveled at speeds of up to 33.0 m/s (approx. 120 km/h, 75 mph). All simulations were performed at a density of 4.2 vehicles per kilometer and lane, representing nightly traffic, as well as at a density of 28.0 vehicles per kilometer and lane, which modeled rush-hour traffic. Sample speed traces recorded in both scenarios are shown in Figure 2. Obviously, using a smaller number of simulated vehicles allowed the cars to move nearly unimpaired by trucks or other cars and to travel at or near top speed. The scenario thus maximized speed differences between nodes, so links between cars of different lanes, between cars and trucks, as well as between vehicles and roadside infrastructure were while DYMO stores routes for each intermediate hop. This is illustrated in Figure 1. When using AODV, node A knows only the routes to nodes B and D after its route request is satisfied. In DYMO, the node additionally learned a route to node C. To efficiently deal with highly dynamic scenarios, links on known routes may be actively monitored, e.g. by using the MANET Neighborhood Discovery Protocol or by examining feedback obtained from the data link layer. Detected link failures are made known to the MANET by sending a route error message (RERR) to all nodes in range, informing them of all routes that now became unavailable. Should this RERR in turn invalidate any routes known to these nodes, they will again inform all their neighbors by multicasting a RERR containing the routes concerned, thus effectively flooding information about a link breakage through the MANET.

DYMO was also designed with possible future enhancements in mind. It uses a generic MANET packet and message format  and offers ways of dealing with unsupported elements in a sensible way. Speed samples of simulated cars at different traffic densities highly unstable. A larger number of simulated vehicles forced cars and trucks into a stop-and-go motion, reducing the cars’ top speed to that of trucks. This stabilized links between vehicles and reduced speed differences between vehicles and roadside infrastructure, but caused large oscillations of local node densities.
Realistic communication patterns of MANET nodes were modeled using OMNeT++ 3.2p1, a simulation environment free for non-commercial use, and its INET Framework 20060330, a set of simulation modules released under the GPL. OMNeT++ runs discrete, event-based simulations of communicating nodes on a wide variety of platforms and is getting increasingly popular in the communications community. Scenarios in OMNeT++ are represented by a hierarchy of reusable modules written in C++. Their relationships and communication links are stored as Network Description (NED) files and can be modeled graphically. Simulations are either run interactively in a graphical environment or executed as command-line applications. The INET Framework provides a set of OMNeT++ modules that represent various layers of the Internet protocol suite, e.g. the TCP, UDP, IPv4 and ARP protocols. It also provides modules that allow the modeling of spatial relations of mobile nodes and IEEE 802.11 transmissions between them. IV. S IMULATION M ODEL The DYMO routing protocol was implemented as an application-layer module of the INET Framework module set. Following the specification [2], it employs UDP to communicate with other instances of DYMO. Additionally, it uses two helper modules to support DYMO operation on the network layer. The complete protocol stack is shown in Figure 3. The first helper module is able to queue outbound packets before routing in the network layer occurs, so that a route can be set up by DYMO. The queue can then be signaled to release buffered packets for a given destination—either in order to have them routed to the first hop or to have them discarded by the network layer because no route could be found. The second helper module is installed as a hooking function in

DYMO and support modules in the protocol stack the inbound packet path. It notifies DYMO of the arrival of packets. This way, routing table entries can be refreshed and route errors can be sent, respectively. DYMO and its helper modules are assembled together with various components of the INET Framework to form simulated MANET nodes. Mobile nodes are represented by modules of type Car, which perform DYMO along with TCP or UDP applications that generate application specific traffic. Communication with other nodes takes place via an IEEE 802.11 module. The roadside infrastructure is provided by modules of type AccessPoint, which execute DYMO only to route between the wireless and the wired network, i.e. the Internet. Internet connectivity is modeled by a node of type CSTMGateway that is also running DYMO. It sends back delayed response messages to requests
via TCP or UDP, i.e. it simulates the application servers that are used by the clients (the Cars).
For all communications, the complete network stack, including ARP, was used and wireless modules were configured to closely resemble IEEE 802.11b network cards transmitting at 11 Mbit/s with RTS/CTS disabled. The TCP protocol implementation follows the TCP Reno specification. Thus, results can be readily compared with existing Linux implementations of DYMO, e.g. NIST DYMO or DYMOUM. For the simulation of radio wave propagation, a plain free-space model was employed and the transmission ranges of all nodes adjusted to a fixed value of 180 m, a trade-off between varying realworld measurements described in related work [17], [18]. All simulation parameters used to parameterize the modules of the INET Framework are summarized in Table I.

In order to ensure realistic application layer traffic, the following three different communication scenarios were modeled: 1) Vehicles polled traffic information from an Internet host. At 5 minute intervals, starting at a random point in time no more than 5 minutes from the start of a simulation, a vehicle tried to send a 256 Byte UDP packet to the gateway, which, upon reception of the packet, answered with a 1024 Byte response packet. 2) Mobile nodes checked a POP3 mailbox (using TCP) for new messages, configured with a maximum segment size of 1024 Byte and an advertised window size of 14 336 Byte, to send eight 16 Byte commands, each triggering a 32 Byte response. As in the first case, the mailbox check was repeated 5 minutes after sending the Simulated MANET scenario first command and the maximum session length limited accordingly. 3) Vehicles requested RSS feeds from a web server (also using TCP). This was represented by changing the second case’s parameters, so that nodes would only send a single, 256 Byte request message and receive a single, 65 536 Byte response message, with fragmentation and reassembly taking place in lower layers. The modeled nodes were then further combined to create the MANET scenario shown in Figure 4, a simulated highway with two lanes in each direction forming a 10 km long closed ring with evenly spaced access points at distances of 2 km, 5 km or 10 km, depending on the scenario.

V. P ERFORMANCE A NALYSIS

Perceived performance of the VANET was estimated by recording the overall success rate, i.e. the probability of
successful reception of a UDP information packet, the last POP3 response, or a complete RSS feed, at the requesting
vehicle depending on the traffic pattern in use. Performance was measured at four different node densities of 0.42, 2.8, 4.2, and 28 vehicles per kilometer and lane, corresponding to the two chosen traffic densities and fractions of 10 % and 100 % DYMO-equipped vehicles, respectively. Three different minimum route lifetimes of 1 s, 3 s, and 10 s were tried for each of the simulated scenarios. A value of 1 s proved to balance the amount of route request and route error messages in the network best. Also, setting the DYMO Network Size parameter to 50 hops instead of to the default 10 hops proved to be beneficial when access points were spaced more than 2 km apart and node densities did not exceed 28 vehicles per kilometer and lane. All results are shown as boxplots. For each data set, a box
is drawn from the first quartile to the third quartile, and the median is marked with a thick line. Additional whiskers extend from the edges of the box towards the minimum and maximum of the data set, but no further than 1.5 times the interquartile range. Data points outside the range of box and whiskers are considered outliers and drawn separately.

Figure 5 shows the overall probability of a simulated UDP session being successfully completed for different node densities and access point distances. As can be seen, even low node densities of 4.2 nodes per kilometer and lane, as well as sparse access point deployment of one node per 5 km highway, sufficed to permit the exchange of UDP packets in approx. 50 % of all tries. Results for other communication scenarios are shown in Figure 6, which plots the overall probability of a session being successfully completed for a fixed access point distance of 5 km. Due to the retry mechanisms offered by the TCP protocol, POP3 sessions always had a significantly higher chance of being completed than plain UDP sessions, even though completion of a POP3 session required the exchange of more packets. Also visible is a rapidly decreasing probability of sessions being successfully completed when node densities increased to above 4.2 nodes per kilometer and lane or when larger messages were to be delivered. While at 0.42 nodes per kilometer and lane, the probability of RSS sessions completing was almost at par with that of POP3 sessions, at 2.8 nodes per kilometer and lane already only half as many RSS sessions finished successfully—approx. 20 % compared to approx. 40 % POP3 sessions. Figures 7 and 8 illustrate a reason for this decrease. With a rising number of communicating nodes, network traffic on the shared medium was increasingly dedicated to DYMO packets until, at 28.0 vehicles per kilometer and lane, the MANET was almost exclusively busy exchanging routing messages. Reducing the number of actively participating nodes to 10 % significantly improved figures—even for node densities as low as 2.8 vehicles per kilometer and lane. To estimate the impact of overload effects on the quality
of routes established by DYMO in the VANET, the relation between the length of a route in number of hops and the
total distance bridged between vehicle and access point was examined. As can be seen in Figure 9, the bridged distance is closely related to the number of hops and it is increasing linearly by approx. 150 m per hop—not much less than the nodes’ communication range of 180 m. In order to reduce the stress imposed on the network due to constant link breakages and subsequent flooding of route error and new route request messages, a promising mechanism was implemented for estimating the potential route stability by taking movement directions into account. When comparing two routes to find the shortest path, DYMO now added a malus of 0.1–5.0 hops for each time a packet was sent to a vehicle traveling in the opposite direction. Information about a vehicle’s relative travel direction was assumed to be estimable by the physical layer. Figure 10 shows the results of this adaptation. Success rates of sessions could indeed be significantly improved by adding such a malus, but the adaptation failed to produce the huge effects observed by other groups  when completely ignoring oncoming traffic
for route selection.

VI. C ONCLUSION AND F UTURE WORK

Evaluation of the feasibility and the expected quality of VANETs operated with the routing protocol DYMO showed
that for small amounts of payload data to be transported, ad hoc networks of vehicles and static highway infrastructure can be successfully setup, maintained, and used with wellknown protocols from the Internet protocol suite alone. Even low node densities and sparse access point deployment sufficed to support routine polling of information via an Internet gateway, e.g. the checking of a POP3 mailbox. Larger amounts of network traffic to be transported over the ad hoc network, however, induced overload effects that noticeably destabilized the VANET. Particularly at higher node densities, which commonly occurred in micro-jams, the routing and transport protocol behavior led to a drastic increase in network load. When the network became congested and new connections could not be established, simple retry mechanisms only furthered congestion. Simulation results therefore seem to encourage an adaptation of the protocols in use, so problems perceived by lower layers are reacted to in a sensible way and application requirements are taken into account when the network becomes overloaded. Cross-layer optimization might keep nodes from using potentially unstable routes for low-priority messages in favor of a reduction of network load. Also, the results of the conducted simulations make a simple flooding of messages through the VANET and the selection of routes without taking node position and mobility into account, as proposed in the current draft of DYMO, appear wasteful. An experimental modification of DYMO, which penalized routes across the lanes when assessing the quality of potential routes, proved beneficial, but failed to produce the predicted increase in overall network quality that was claimed in related work.

REFERENCES
[1] L. Wischhof, A. Ebner, H. Rohling, M. Lott, and R. Halfmann, “SOTIS – a self-organizing traffic information system,” in Proceedings of the 57th IEEE Vehicular Technology Conference (VTC 03 Spring), 2003. [2] I. Chakeres and C. Perkins, “Dynamic MANET On-Demand

(DYMO) Routing,” Internet-Draft, draft-ietf-manet-dymo-06.txt, October 2006. [Online]. Available: http://tools.ietf.org/wg/manet/ draft-ietf-manet-dymo/draft-ietf-manet-dymo-06.txt
[3] C. Perkins, E. Belding-Royer, and S. Das, “Ad hoc On-Demand Distance Vector (AODV) Routing,” RFC 3561, July 2003. [Online]. Available: http://www.ietf.org/rfc/rfc3561.txt
[4] C. Perkins and E. Royer, “Ad hoc On-Demand Distance Vector Routing,” in 2nd IEEE Workshop on Mobile Computing Systems and Applications, New Orleans, LA, February 1999, pp. 90–100.
[5] R. Baumann, “Vehicular ad hoc networks (VANET) – engineering and simulation of mobile ad hoc routing protocols for VANET on highways and in cities,” Master’s thesis, ETH Z¨ rich, 2004.
u
[6] C. Sommer, I. Dietrich, and F. Dressler, “Realistic Simulation of Network Protocols in VANET Scenarios,” in 26th Annual IEEE Conference on Computer Communications (IEEE INFOCOM 2007): Mobile Networking for Vehicular Environments (MOVE 2007), Poster Session. Anchorage, Alaska, USA: IEEE, May 2007.

[7] T. Clausen, C. Dearlove, J. Dean, the OLSRv2 Design Team, and the MANET Working Group, “MANET Neighborhood Discovery Protocol (NHDP),” Internet-Draft, draft-ietf-manet-nhdp-00.txt, June 2006. [Online]. Available: http://tools.ietf.org/pdf/draft-ietf-manet-nhdp-00. pdf

[8] T. H. Clausen, C. M. Dearlove, J. W. Dean, and C. Adjih, “Generalized MANET Packet/Message Format,” Internet-Draft,
draft-ietf-manetpacketbb-02.txt, July 2006. [Online]. Available: http://tools.ietf.org/pdf/ draft-ietf-manet-packetbb-02.pdf

[9] A. Mahajan, “Urban mobility models for vehicular ad hoc networks,” Master’s thesis, Department of Computer Science, Florida State University, 2006. [10] A. K. Saha and D. B. Johnson, “Modeling mobility for vehicular adhoc networks,” in Proceedings of the 1st ACM international workshop on Vehicular ad hoc networks, 2004.

[11] C. Lochert, A. Barthels, A. Cervantes, M. Mauve, and M. Caliskan, “Multiple simulator interlinking environment for IVC,” in Proceedings of the 2nd ACM international workshop on Vehicular ad hoc networks, 2005.

[12] M. Treiber, A. Hennecke, and D. Helbing, “Congested traffic states in empirical observations and microscopic simulations,” Physical Review E, vol. 62, p. 1805, 2000.
[13] M. Treiber and D. Helbing, “Realistische Mikrosimulation von Straßenverkehr mit einem einfachen Modell,” in ASIM 2002, Tagungsband 16. Symposium Simulationstechnik, 2002.
[14] O. Kaumann, K. Froese, R. Chrobok, J. Wahle, L. Neubert, and M. Schreckenberg, “On-line simulation of the freeway network of north rhine-westphalia,” in Traffic and Granular Flow ’99, D. Helbing, H. Herrmann, M. Schreckenberg, and D. Wolf, Eds.

Heidelberg:
Springer, 2000, pp. 351–356.
[15] B. Tilch and D. Helbing, “Evaluation of single vehicle data in dependence of the vehicle-type, lane, and site,” in Traffic and Granular Flow ’99, D. Helbing, H. Herrmann, M. Schreckenberg, and D. Wolf, Eds. Heidelberg: Springer, 2000.

[16] A. Varga, “The OMNeT++ discrete event simulation system,” in Proceedings of the European Simulation Multiconference (ESM2001), 2001. [17] F. Hui and P. Mohapatra, “Experimental characterization of multi-hop communications in vehicular ad hoc network,” in Proceedings of the 2nd ACM international
workshop on Vehicular ad hoc networks, 2005. [18] H. Wu, M. Palekar, R. Fujimoto, J. Lee, J. Ko, R. Guensler, and M. Hunter, “Vehicular networks in urban transportation systems,” in Proceedings of the 2005 national conference on Digital government research, 2005.

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Worldwide Paper Company Essay

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Worldwide Paper Company Essay
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  • University/College:
    University of California

  • Type of paper: Thesis/Dissertation Chapter

  • Words: 1149

  • Pages: 5

Worldwide Paper Company

INTRODUCTION
In December 2006, Bob Prescott, the controller for the Blue Ridge Mill, was considering the addition of a new on-site longwood woodyard. Two primary benefits for this new addition include eliminating the need to purchase shortwood from an outside supplier and creating an opportunity to sell shortwood on the open market. Also, the new woodward would reduce operating costs and increase revenues. Blue Ridge Mill currently purchased shortwood from the Shenandoah Mill, which is a direct competitor. Thus, adding the new longwood equipment would mean that the Prescott would no longer need to use the Shenandoah Mill as a shortwood supplier and that the Blue Ridge Mill would instead compete with the Shenandoah Mill by selling on the shortwood market. The question for Prescott was whether these expected benefits were enough to justify the $18 million capital outlay plus the incremental investment in working capital over the six-year life of the investment.

SYMPTOMS
The addition of a new on-site longwood woodyard would bring benefit to Blue
Ridge Mill in term of decreasing their operating cost and also increasing their revenue or sales. But the estimation of revenue and cost did by Prescott do not reflect the inflation rate. Thus, this project’s evaluation will be less accurate.

PROBLEMS
By adding the new on-site longwood woodyard, Prescott estimates that the revenue for their company would increase to $4 million in year 2008 and goes to $8 million every year until year 2013. And also the cost of goods sold would be 75% of revenue and SG&A would be 5% of revenue. But all of this estimation does not include the inflation. So, we are using the net present value (NPV) and internal rate of return (IRR) to evaluate this longwood woodyard project which these methods involve the discounted cash flow.

PROBLEM SOLVINGS
First, we need to find the required rate of return (WACC) to calculate the discounted cash inflow so that we can evaluate the longwood woodyard project more accurately. Calculate KE : Cost of Equity (CAMP)

KE = KRF + (KM – KRF) Beta

Beta = 1.1
KRF= 4.60% : Government bonds 10-year,
Risk premium = 6.0%
KE = 4.6% + (6.0%) 1.1
= 11.2%

Calculate KD: Cost of Debt

KD = Bank Loan Payable + Long Term Debt
= $ 500 + $ 2500
= $ 3000

KD = (500/3000) * (5.38% + 1%) + (2500/3000) * (5.78%)
= 5.88%

KD (1-Tax)
=5.88% (1-40%)
= 3.528%

Calculate capital structure: WE and WD
Equity = Current Market Share Price x Shares Outstanding
= $24 x 500m
= $12000m

Debt = Bank Loan Payable + Long Term Debt
= RM 500 + RM 2500
= RM 3000

E+D = $ 12000 + $ 3000
= $ 15000
WE = 12000/15000
= 0.8/80%

WD = 3000/15000
= 0.2/20%

Calculate WACC
WACC = WE. KE + WD .KD (1-T)
= 0.8 (11.2%) + 0.2 (3.528%)
= 9.6656 @ 9.67%

So. The WACC (required rate of return) is 9.67%

Second, we need to find the cash inflow of this project.

2007
2008
2009
2010
2011
2012
2013

$’million
$’million
$’million
$’million
$’million
$’million
$’million
Revenue

4
10
10
10
10
10
(-) COGS (75% of reveue)

3
7.5
7.5
7.5
7.5
7.5
(-) SG & A (5% of revenue)

0.2
0.5
0.5
0.5
0.5
0.5
Net Shortwood Income

0.8
2
2
2
2
2
Operating Saving

2
3.5
3.5
3.5
3.5
3.5
(-) Depreciation ($18million/6 years)
3
3
3
3
3
3
Earning Before Interest & Tax

-0.2
2.5
2.5
2.5
2.5
2.5
(-) Tax (40%)

-0.08
1
1
1
1
1
Earning After Tax

-0.12
1.5
1.5
1.5
1.5
1.5
Add Back Depreciation

3
3
3
3
3
3
Free Cash Flow

2.88
4.5
4.5
4.5
4.5
4.5

Third, we need to calculate the discounted cash inflow of this project.

Year
1
2
3
4
5
6

Cash inflow
($’million)
2.88
4.5
4.5
4.5
4.5
4.5
Total cash inflow=
$25.38million

Discounted cash inflow
($’million)
2.62606

3.7414

3.4115

3.1107

2.8364

2.5863

Total discounted cash inflow=
$18.31236million

Project Evaluation Methods

I. Net present value (NPV)
Discounted Cash Inflow – Cash Outflow
= $18.31236 million – $18 million
= $0.31236 million
The NPV is $0.31236 million which is positive.
This means that longwood woodyard project will bring positive return which is $0.31236 million.

II. IRR
Firstly, calculate the discounted cash flow by using required interest rateat 10%and 12% respectively.

10%
2.618208
3.7188
3.38085
3.0735
2.79405
2.54025
Total discounted cash inflow: $18.12566 million
*rate too low
12%
2.571552
3.5874
3.2031
2.85975
2.5533
2.2797
Total discounted cash inflow: $17.0548 million
*rate too high

X= 0.12566
0.02 1.07086
X =0.12566 (0.02)
1.07086
X=0.002346

IRR=0.102346 @ 10.23%

So, the IRR is 10.23% which is higher than required rate of return (10.23% > 9.67%) This means that the company will receive 10.23% for each dollar that invested in this project at a cost of 9.67%.

RECOMMENDATION
The expected benefits are enough to justify $18 million capital outlay plus the incremental investment in working capital over the six-year life of the investment. The current WACC (9.67%); the NPV is positive ($0.31236); the IRR is greater than WACC (10.23% > 9.67%). Therefore, Prescott should invest in the new longwood woodyard.

CONCLUSION
The investing in the new longwood woodyard gives benefits of eliminating the need to purchase shortwood from an outside supplier and creating an opportunity to sell shortwood on the open market. Besides, the new woodward will reduce operating costs and increase revenues. We use the current WACC, NPV and IRR method to decide whether Prescott should invest in the woodyard. The result shows that Prescott should invest in the new woodyard because the expected benefits are enough to justify $18 million capital outlay plus the incremental investment in working capital over the six-year life of the investment.

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Worldwide Paper Company Essay

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Worldwide Paper Company Essay
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  • University/College:
    University of Chicago

  • Type of paper: Thesis/Dissertation Chapter

  • Words: 1991

  • Pages: 8

Worldwide Paper Company

Executive Summary:

Blue Ridge Mill is a wood mill owned by Worldwide Paper Company and supplies wood pulp for the company for use in paper production. Blue Ridge Mill bought its wood supply from Shenandoah Mill’s excess production of shortwood that was processed from its longwood supplies. In 2006, Bob Prescott, the controller for Blue Ridge Mill, was considering a project that would give Blue Ridge Mill the capability to process longwood into shortwood, which would eliminate the need to purchase from Shenandoah Mill, as well as compete with Shenandoah Mill in the shortwood market.

Project Overview:

The project would provide Blue Ridge Mill with a new longwood yard, giving the mill the ability to produce shortwood, a required input for paper production, from longwood. The project would also product excess shortwood that would allow Blue Ridge Mill to sell shortwood as an additional revenue source, competing with their current shortwood supplier. Construction for project would begin in 2007 and production would begin in 2008. The project will cost $18 million, with $16 million in 2007 and an additional $2 million in 2008. The $18 million investment will be depreciated using the straight-line method for six years and a zero salvage value. Although, the equipment is believed to be able to be sold at the end of the project for $1.8 million.

The main purpose of the project is to save on operational costs by producing shortwood. The cost savings is estimated to be $2 million in the first year and $3.5 million in the following five years. In addition, the longwood yard would provide enough capacity to allow Blue Ridge Mill to sell shortwood on the market. Bob Prescott confidently estimates that shortwood sales in 2008 will be $4 million, and will increase to $10 million in the remaining five years. There are also expenses from the new shortwood sales as well as tax expenses.

Cost of goods sold (COGS) is estimated to be 75% of the new shortwood revenue. In addition, Sales, General and Administration (SG&A) expenses are estimated at 5% of the additional revenue. Blue Ridge Mill will also need to invest working capital as sales increase. The additional working capital required is estimated at 10% of the change in revenues from the previous year. However, the investment in working capital is fully recovered at the end of the project. Finally, the income tax rate for the company is 40% of earnings. Table 1 below shows all of the incremental cash flows as a result of this project.

Table 1: Longwood Yard Project Free Cash Flows
Discount Rate:

The internal rate of return (IRR) from the free cash flows of the project based on the estimates given by Bob Prescott is 11.30%, which is lower than the company’s published hurdle rate of 15%. However, that hurdle rate was calculated 10 years ago when the 30 year Treasury Bond was around 10%, more than double current interest rates (see table 2 below). Therefore, it is recommended that a weighted average return rate (WACC) be calculated and used as that hurdle rate. In order to calculate the WACC, the cost of debt and the cost of equity must be calculated first based on the information provided by the case. The interest rates and market risk premium are found in Table 2, and the company’s balance data, bond rating, Beta, and tax rate are found in Table 3. It is assumed that the debt and equity listed in Table 3 represents all of the debt and equity for the company.

The cost of debt is the weighted average cost of each debt held by the company. Table shows two debts to include: a bank loan payable at 6.38% (LIBOR + 1%) and Long Term debt. LIBOR is a floating interest rate that changes daily. However, since the bank loan is only a small portion of the total debt, the floating LIBOR will be ignored and treated as a fixed LIBOR. Since the company has a Bond Rate of A, the company’s long term debt is at 5.78%. As a result, the cost of debt is 5.88% and is calculated as follows:

The cost of equity can be calculated by using the capital asset pricing model (CAPM). CAPM requires that a market risk free rate, the market risk premium, and the beta for the company. The market risk premium (6%) and the company beta (1.1) is given directly and can be seen in tables 2 and 3 below. Government bonds are used for the risk free rate. Since 10 year corporate bonds are used for the cost of debt, the 10 year Treasury Bond of 5.60% will be selected as the risk free rate. The 10 year bonds are also a good match for the project duration, which is between 5 and 10 years. The cost of equity of 11.20% is than calculated as follows:

With the cost of debt and the cost of equity calculated, the WACC is calculated below. The cost of debt is further discounted by one minus the tax rate since the interest paid on debt is treated as an expense prior to being taxed.

Table 2: Interest Rates December 2006

Table 3: Company Financial Information

Using the calculated WACC and the company’s hurdle rate for this project, under Bob Prescott’s cost savings and additional revenues assumption, the project’s IRR is now greater than the hurdle rate. Furthermore, the net present value (NPV), payback period and the additional value added to the earnings per share (EPS) are shown in Table 4 below. Using just these figures, the project should be accepted. However, prior to making that decision, the base assumptions should be examined closer.

Table 4: Project Performance

Sensitivity Analysis:

Sales demand for the excess produced shortwood and the savings in operations costs due to the project were both estimates and may not match the actual values in the years to come. These two values where adjusted to perform a sensitivity analysis on how these changes influence the NPV. Table 4 shows the result of the sensitivity analysis. The Sales Demand is represented in the first column and ranges from $0 to $12 million. Values from $0 to $4 million are used for all six years. For values greater than $4 million, $4 million is used for the first year, and the larger number is used for the remaining five years. Operation savings is shown as percentages across the top row. These represent percent changes to the amount estimated in the base case. For example, -10% means that instead of a savings of $2 million in the first year and $3.5 million in the remaining years, the realized savings are $1.8 million in the first year and $3.15 million in the remaining years. Positive percentages mean that savings were greater than the expected amount.

Table 4 shows the output of the sensitivity analysis in NPV (in millions). The negative values are filled with a light red. The positive NPVs that are less than the base case are filled in light green, the base case is green, than NPVs greater than the base case are dark green. The table shows that if operations savings are as expected (0% change) than the sales would have to be 60% less than expected before the project becomes a negative NPV project.

If operations savings are 10% less than expected, than new sales with have to be 40% less. Presumably, Bob Prescott has very good data on the operations savings and the actual is within 10% of the estimated, than the sales data can be off as much as 40% before this becomes a negative project. However, because there are possible negative values in the sensitivity analysis (especially at $4 million in sales), there is still risk in having a negative NPV project.

A desired piece of information that would be useful in this decision would be to calculate expect values for operations savings and sales demand. Table 5 show an example of using possible outcomes and their probabilities to calculate the expected values. To make the example complete, the expect values where inputted into the model and project performance is shown as part of Table 5.

Table 4: Sensitivity Analysis Table – Various Additional Shortwood Revenues vs. percent changes to operation savings with resulting NPV

Table 5: Example of calculating expected values for sales and savings, along with the performance outputs with the expected values

Other Risks:

To make a final decision on whether to accept the longwood yard project, other risks can be considered. Particularly, what are the risks if the project is not accepted? One risk hinges on the fact that Blue Ridge Mills will still be depended on Shenandoah Mill for the supply of shortwood. There are two risks. First, there is a supply shortage risk. Shenandoah may find other ways to use their shortwood, which would reduce the excess amount they use for sales. If Blue Ridge Mills does not receive enough supplies, than they will not be able to provide the company with the volume required, which could reduce the amount of paper production, resulting in a loss of sales. Another risk with Shenandoah Mill is the risk of shortwood price increases. This could happen if another consumer of shortwood enters the market. If shortwood prices increase, profit margins for Worldwide Paper will decrease.

Another risk to consider is the paper industry market. If Worldwide Paper Company’s paper sales volume declines, Blue Ridge Mill’s production will need to slow down as well. This is because they only supply one product to one customer, Worldwide Paper. The longwood yard project would help Blue Ridge Mill diversify and reduce that risk.

Both of these risks could be quantified and added to the model’s sensitivity analysis if more financial data and shortwood market data where available. This could be done by calculating the expected values of the impact of shortwood supply shortages and declines in the paper market. These expected values would then be added as an increase in annual project value, increasing the project cash flows through the life of the project. As a result, the sensitivity analysis would show that the project will provide positive NPV through greater reductions of the operations savings and new shortwood revenues than what is shown on table 4, giving a stronger case for acceptance.

Conclusion:

Although the initial response would have been to reject the project based off of the project not meeting the company’s published 15% hurdle rate, evaluating the ten year old hurdle rate reveals that this rate is about 8% too high based on 2006 Treasury Bond rates. Using the updated hurdle rate of 7%, the project does surpass this rate with an 11.2% IRR and provides Blue Ridge Mill with a $2.64 million NPV return on the project investment.

Preforming a sensitivity analysis on the estimated savings and additional revenues of the project shows that the project’s rate of return remains above the 7% hurdle rate for most of the reasonable reductions in those input variables. Considering the risks of Blue Ridge Mill’s shortwood supply of either increase in prices or supply shortages adds further value to the project. Another risk that adds value to the project is the diversification the project creates, which could serve to protect Blue Ridge Mill from downturns in the paper market. As a result, Worldwide Paper Company should accept the longwood yard construction project at Blue Ridge Mill.

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Worldwide Paper Company Essay

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Worldwide Paper Company Essay
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  • University/College:
    University of Arkansas System

  • Type of paper: Thesis/Dissertation Chapter

  • Words: 593

  • Pages: 2

Worldwide Paper Company

Bob Prescott, the comptroller for the Blue Ridge Mill, was weighing the pros and cons of adding a new-on site longwood woodyard. Two primary benefits for this new addition include eliminating the need to purchase shortwood from an outside supplier and creating an opportunity to sell shortwood on the open market. Also, the new woodward would reduce operating costs and increase revenues. Blue Ridge Mill currently purchases shortwood from the Shenandoah Mill, which is a direct competitor. If Blue Ridge Mill decides to utilize longwood woodyard then the company would decrease its WACC from 15% to 9.77%. Blue Ridge Mill can then make better investment decisions with a lower WACC. The new woodyard would begin in 2008 where an investment outlay of $18 million would be spent over calendar years 2007 and 2008.

Before making a capital budget decision we must ignore any sunk costs and include both opportunity costs and side effects. Capital budgeting must be done on an incremental basis and Worldwide Paper Company did not have any sunk costs. In order to analyze the capital budgeting process for this case, I took Sales Revenue and found the difference from operating expenses and cash flows to get operating cash flows. It is imperative to calculate the Net Present Value for this project before making any sort of capital budgeting decision. When calculating the Net Present Value, we used the WACC rate of 9.77% and came up with NPV of $720,000. The initial conclusion is to accept this project as long as everything stays the same, and that they should evaluate themselves yearly as things may change. Blue Ridge Mill should take into account the depreciation expense per year when making an educated capital budgeting decision.

Depreciation generated cash flows should be included in this project for many reasons. The depreciated generated cash flow gives us a better understanding of the financial breakdown of the project and tells the investor whether or not it is a good investment. The depreciation expense is consistently $3 million from 2008 to 2013 because the straight-line depreciation has zero salvage value. Also, depreciated generated cash flows help us determine the non-operating or terminal cash flow for this project and purchase of longwood woodyard. In 2007 there wasn’t any depreciation charges because Worldwide Paper Company wanted to get a good grasp on how inflation would affect Prescott’s analysis. Depreciation charges did not begin until 2008 where all of the $18 million was spent and the machinery was working correctly.

The beta is 1.1 and the bond rating for this project is A which tells us that this project looks like it has minimal risk from the outside. In order to adjust for project risks one can increase the required rate of return discount factor for the projects cash flow. This will essentially reduce the value of future cash flows. If Prescott is believes that there is a risk that future payments will not be paid then he can reduce cash flows from an expected loss percentage. If WPC believes the project is going to be delayed before launch then they can delay cash flow payments for a year. Another way WPC can adjust for risks by subtracting the start up costs from the projects estimated Net Present Value. Lastly, WPC can adjust for project risks by generating cash reserves in case there are hidden costs within the project. Project risks are very hard to predict but every investor should always try to account for them.

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Worldwide Paper Company Essay

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Worldwide Paper Company Essay
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  • University/College:
    University of California

  • Type of paper: Thesis/Dissertation Chapter

  • Words: 306

  • Pages: 1

Worldwide Paper Company

1.What are the yearly cash flows that are relevant for this investment decision? Do not forget the effect of taxes and the initial investment amount. (Submit an excel spreadsheet into D2L containing your computations.) Worldwide Paper Company (WPC) has an opportunity to take on a new project. With this project they would be considering an addition of a new on-site Longwood wood yard.

The yearly cash flows for this investment seem to be very good if everything remained or exceeded the assumptions on which we calculated the cash flows. $18 million is not a small investment but in the long run we can see the company catching up to get back the invested money and also allowing them to make huge profits. The company is paying a 40% tax from their earning which is huge money but even after that, the company is making lots of profits.

2.What discount rate should Worldwide Paper Company (WPC) use to analyze those cash flows? Be prepared to justify your recommended rate and the assumptions that you used to estimate it. We first used the 15% discount rate to calculate NPV and the Cash Flows by using that discount rate we ended up with a negative NPV of $ (2,137,217.21).

We determined that the discount rate of 15% was out dated and insufficient. Therefor to calculate a more accurate NPV for the project, we decided to use the rate of 9.62% that we computed. And using this number we got the NPV of $746,981.31. I would recommend Worldwide Paper Company (WPC) to use the 9.62% discount rate, but this is a good project and the returns will be great only if everything remains like expected. So, I would also recommend them to evaluate themselves at least yearly as things may change from year to year.

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