Get documents about "A Multi-criteria Decision Model For EOL Computers in Reverse Logistics
Description
IJCSIS, call for paper, journal computer science, research, google scholar, IEEE, Scirus, download, ArXiV, library, information security, internet, peer review, scribd, docstoc, cornell university, archive, Journal of Computing, DOAJ, Open Access, April 2011, Volume 9, No. 4, Impact Factor, engineering, international, proQuest, computing, computer, technology
Document Sample
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 4, April 2011
A Multi-Criteria Decision Model for EOL Computers
in Reverse Logistics
K.ArunVasantha Geethan Dr.S.Jose
Department of Mechanical Engineering Loyola-ICAM College of Engineering &
Sathyabama University, Chennai. India Technology ,Chennai. India
R.Devisree S.Godwin Barnabas
Cognizant Technology Solutions St.Joseph’s College of Engineering
Chennai. India Chennai. India.
Abstract- With obsolescence rates on the rise the question as to affecting the reverse logistics, some of these are
what the user ultimately does with the end-of-life (EOL) product interdependent among each other.
becomes an issue that has both environmental and economic
implication. An important concern in EOL management for Analytic Network Process (ANP) is a technique that captures
electronic products is to connect the equipment owners with
potential buyers who may be interested in their EOL items,
the interdependencies between the criteria under
whether for reuse, component retrieval or material recovery. consideration, hence allowing for a more systematic analysis
There is an estimate that the total obsolete computers originating [2]. It can allow inclusion of criteria, both tangible and
from government offices, business houses, industries and intangible, which has some bearing on making the best
household is of the order of 2.5 million numbers per year. decision. Further, many of these factors have some level of
Manufacturers and assemblers in a single calendar year are interdependency among them, thus making ANP modeling
estimated to produce around 1500 tons of electronic scrap. One better fit for the problem under study. The ANP model
of the important problems faced by the top management in the presented in this paper structures the problem related to
computer hardware industries is the evaluation of various selection of an alternative for the reverse logistics option for
alternatives for EOL computers. The paper aims at linking the
various issues of the reverse logistics in a single systematic
EOL computers in a hierarchical form and links the
framework for the selection of an alternative for the reverse determinants, dimensions and enablers of reverse logistics
logistics operations for EOL computers. The utility of the with different alternatives.
Analytic network process (ANP) in integrating both quantitative
as well as the qualitative characteristics and using C++ as the II. LITERATURE REVIEW
platform for arriving at the best possible solution proves to be Stock (1992) recognized the field of reverse logistics as being
more realistic and accurate.
relevant for business and society in general. Kopicki, Berg,
Keywords: end-of-life, obsolescence, analytic network program,
alternatives, reverse logistics.
Legg, Dasappa, and Maggioni (1993) paid attention to the
field and pointed out opportunities on reuse and recycling.
I. INTRODUCTION Fleischmann, Bloemhof-Ruwaard, Dekker, van der Laan, van
Nunen, and Van Wassenhove (1997) had given a
Reverse logistics is the process of planning, implementing and comprehensive review of literature of the quantitative models
controlling the efficient, cost effective low of raw materials, in reverse logistics. Reverse logistics programs in addition to
in-process inventory, finished goods and related information the various environmental and the cost benefits can
from the point of consumption to the point of origin for the proactively minimize the threat of government regulation and
purpose of recapturing value or proper disposal [1]. A reverse can improve the corporate image of the companies (Carter &
logistics defines a supply chain that is redesigned to efficiently Ellram, 1998). Reverse logistics is the process of planning,
manage the flow of products or parts destined for implementing, and controlling the efficient, cost effective flow
remanufacturing, recycling, or disposal and to effectively of raw materials, in-process inventory, finished goods and
utilize resource. According to a recent study, reverse logistics related information from the point of consumption to the point
is one of the twenty one top warehousing trends in the twenty of origin for the purpose of recapturing value or proper
first century (Brockmann,1999). Industries have started to disposal (Rogers & Tibben-Lembke, 1998). A reverse logistics
realize that the reverse logistics can be used to gain defines a supply chain that is redesigned to efficiently manage
competitive advantage. An evaluation framework, which the flow of products or parts destined for remanufacturing,
incorporates determinants and dimensions of reverse logistics, recycling, or disposal and to effectively utilize resources
would be useful in configuring the post activities associated (Dowlatshahi, 2000).
with the EOL computers. There are number of variables
157 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 4, April 2011
Thus, the reverse logistics focuses on managing flows of multi-criteria decision making in the decision making related
material, information, and relationships for value addition as to reverse logistics practices in the case of EOL computers.
well as for the proper disposal of products. Reverse logistics
has been used in many industries like photocopiers (Krikke,
van Harten, & Schuur, 1999a; Thierry, Salomon, Nunen, & III. PROBLEM DESCRIPTION
Wassenhove, 1995; van der Laan, Dekker, & Van Reverse logistics have recently received much attention as
Wassenhove, 1999) single-use cameras (Toktay, Wein, & most of the companies are using it as a strategic tool to serve
Stefanos, 2000), jet engine components (Guide & Srivastava their customers and can generate good revenue. It is a vital
1998), cellular telephones (Jayaraman, Guide, & Srivastava, part of a successful business in warehousing and distribution.
1999), automotive parts (van der Laan, 1997) and refillable Recognizing that both the forward and reverse channels of the
containers (Kelle & Silver, 1989). In all the cases, one of the supply chain can be combined and doing this correctly will
major concerns is to assess whether or not the recovery of save a significant amount of money for the business.
used products is economically more attractive than the The representation of the model and decision environment
disposal of the products [3]. Reverse logistics are also clearly shows that the overall objective is to carry out reverse
extensively practiced in the computer hardware industry. IBM logistics processes for EOL computers. The determinants of
and Dell Computer Corporation have embraced reverse reverse logistics (economic factors, legislation, business
logistics by taking steps to streamline the way they deploy old strategy and customer service initiatives) are modeled to have
systems; and in the process make it easier for the customers to dominance over the dimensions of reverse logistics. The
refurbish existing computers or buy new parts (Ferguson, reverse logistics attribute enablers are those that assist in
2000). Grenchus, Johnson, and McDonell (2001) reported that achieving the controlling dimension of reverse logistics. Thus
the Global Asset Recovery Services (GARS) organization of these are dependent on the dimension. Also, there are some
IBM’s Global Financing division has integrated some of the interdependencies among the enablers. The reverse logistics
key components of its reverse logistics network to support and implementation alternatives in this model are the specific
enhance environmental performance. Moyer and Gupta (1997) projects or policies that a decision maker wishes to evaluate,
have conducted a comprehensive survey of previous works given the various attribute levels of the reverse logistics. The
related to environmentally conscious manufacturing practices, various alternatives available to the decision maker in this case
recycling, and the complexities of disassembly in the include third party reverse logistics, Self Support Logistics
electronics industry. Gungor and Gupta (1999) have presented and Virtual reverse logistics network.
the development of research in environmentally conscious
manufacturing and product recovery (ECMPRO) and provided REVERSE LOGISTICS OVERALL
a state-of-the-art survey of the published work in this area. WEIGHTED INDEX (RLOWI)
Veerakamolmal and Gupta (1997) have discussed a technique CALCULATION FOR BEST
ALTERNATIVE
for analyzing the design efficiency of electronic products, in
order to study the effect of end-of-life disassembly and
disposal on environment. Nagel and Meyer (1999) discuss a
novel method for systematically modeling end-of-life
networks and show ways of improving the existing and new
systems with ecological and economical concerns. Boon, DETERMINANTS
Isaacs, and Gupta (2002) have investigated the critical factors
influencing the profitability of end-of-life processing of PCs.
They also suggested suitable policies for both PC
manufacturers and legislators to ensure that there is a viable
PC recycling infrastructure. Lambert (2003) presented a state-
of-the-art survey of recently available literature on DIMENSIONS
disassembly sequencing and the papers closely related to this
topic. Krikke, van Harten, and Schuur (1999b) have discussed
a case of the recycling PC-monitors as a part of a broader pilot
project at Roteb (the municipal waste company of Rotterdam,
The Netherlands) where by using the model developed, it
achieved a reduction of recycling costs by about 25%. ENABLERS
Ferguson and Browne (2001) discussed the issues in EOL
product recovery and reverse logistics. Knemeyer, Ponzurick,
and Logar (2002) utilized a qualitative methodology to
examine the feasibility of designing a reverse logistics system
to recycle or refurbish EOL computers that are deemed no
longer useful by their owners [7]. From the literature review, it ALTERNATIVES
is observed that there is not much work reported till date for
Fig.1.ANP model for EOL Computers
158 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 4, April 2011
Step 5: Pair-wise comparison matrices between component
IV. METHODOLOGY /enablers levels
The case study approach was selected because it is an ideal
method when a holistic, in-depth investigation is needed. This D1 D2 D3 D4
case study approach helps to gather the facts from the real Waste
Uncertainity Demand Convenience(CON)
world and explain the linkages between causes and effects. Reduction
Modeling(UM) Forecasting(DF)
One such benefit is that the information provided is usually (WR)
more concrete and contextual, specifically due to the in depth Management of Cost
Forecasting Green
analysis it offers of the case being studied. Collection
cost(FS) Products(GP)
Savings
Centers(MCC) (CSA)
Recapturing
A. Algorithm Impact of Remanufacturing Customer
Value
Transportation(IT) cost(RC) Satisfaction(CSF)
(REV)
Step 1: Start
Table .1. Enablers with respect to the Dimensions
Step 2: Model development and problem formulation Two components would be compared at a time with respect to
an upper level control criterion. The pair-wise comparisons of
Step 3: Pair-wise comparison of determinants the elements at each level are conducted with respect to their
relative influence towards their control criterion. For a
Determinant, Pair-wise comparison is done between the
applicable enablers within a given dimension cluster.
Economic Legislation
Factors
Step 6: Pair-wise comparison matrices of interdependencies
among the enablers
Determinants
Step 7: Evaluation of alternatives
Business Customer Service
Strategy Initiatives
Self
Support
Logistics
Fig.2. Determinants (SSL)
Third Virtual
Step 4: Pair-wise comparison of dimensions for each Party Reverse
determinants Reverse Logistics
Logistics (3PRL) Network (VRL)
D2
D1
Design
Remanufacturing Fig.4.Alternatives
Dimensions Step 8: Develop Super matrix from Pair-wise comparison
matrices of interdependencies
Step 9: Selection of the best alternative for a determinant
D3 Customer Financial D4
Step 10: Calculation of reverse logistics overall weighted
index (RLOWI)
Fig.3. Dimensions Step 11: Stop
159 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 4, April 2011
V. CASE ILLUSTRATION B. Super Matrix
The model presented in this paper has been evaluated in an UM MCC IT DF FS RC CON GP CSF WR CSA REV
actual computer manufacturing company, which was UM 0 0.14 0.14
interested in the implementation of the reverse logistics MCC 0.86 0 0.86
IT 0.14 0.86 0
practices. DF 0 0.83 0.8
FS 0.2 0 0.2
RC 0.8 0.17 0
A. Main function of the ANP implementation program CON 0 0.86 0.83
GP 0.83 0 0.17
CSF 0.17 0.14 0
void main() WR 0 0.86 0.2
CSA 0.86 0 0.8
{ int i,k,n=0,j; REV 0.14 0.14 0
float detevect[20]={0},rlowii[20]={0};
float rlowic=0, rlowin[10]={0}; Table.2. Super matrix
float
det[4][4]={1,6,5,3,0.1667,1,3,2,0.2,0.333,1,2,0.333,0.5,0.5,1}; C. RLOWI calculation for alternatives
cout<<"\n\t\t DETERMINANTS\n\n";
float * evectordet=evectformation(det);
for( k=0;k<3;k++) Alternatives 3PRL SSL VRL
{ detevect[k]=*(evectordet+n); Weights
n++; }
float * edi=economicfactors();
for( k=0;k<3;k++) Eco 0.18 0.1 0.06
{ rlowi[k][0]=*(edi+n); 0.56
n++; }
float * ldi=legislation(); Legi 0.4 0.21 0.13
for( k=0;k<3;k++) 0.2
{ rlowi[k][1]=*(ldi+n);
n++; }
0.51 0.38 0.18
float * bdi=businessstrategy(); BS
for( k=0;k<3;k++) 0.13
{ rlowi[k][2]=*(bdi+n);
n++; } 0.65 0.53 0.23
CSI
float * cdi=customerserviceini(); 0.11
for( k=0;k<3;k++)
{ rlowi[k][3]=*(cdi+n); RLOWI Calculation
n++; } RLOWIi = ∑ Dia Ca
Where
for(i=0;i<3;i++) Dia is the summation of the
{ for(k=0;k<4;k++) products of the desirability indices
{ cout<<rlowi[i][k]<<" "; } Ca is the relative importance
cout<<"\n"; } weights of the determinants
for(i=0;i<3;i++)
{ rlowii[i]=0.0;
for(k=0;k<4;k++)
{ rlowii[i]+= detevect[k]* rlowi[i][k]; }}
cout<<"\n\t\t REVERSE LOGISTICS OVERALL RLOWI 0.245025 0.148481 0.0868695
WEIGHTED INDEX \n\n";
for( i=0;i<3;i++)
{ cout<<rlowii[i]<<"\n"; }
for(i=0;i<3;i++) Fig.5. RLOWI calculation for alternatives
{ rlowic+=rlowii[i]; }
for(j=0;j<3;j++)
{ rlowin[j]=(rlowii[j]/rlowic); }
cout<<"\n\t\t NORMALISED VALUE OF REVERSE
LOGISTICS OVERALL WEIGHTED INDEX \n\n";
for(i=0;i<3;i++)
{ cout<<rlowin[i]<<"\n"; } }
160 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 4, April 2011
VII. REFERENCES
[1] He, B., Yang, C., Ren, M. M. A Fuzzy Multi-objective
programming for optimization of reverse logistics for solid waste
through genetic algorithms. In Fourth international conference on
fuzzy systems and knowledge discovery. China 2007, pp. 416-420.
[2] Kärkkäinen, M. Increasing efficiency in the supply chain for short
shelf life goods using RFID tagging. International Journal of
Retail and Distribution Management, 31(10), 2003, pp 526-536.
[3] Lee, D. H., & Dong, M. A heuristic approach to logistics network
design for end-of-lease computer products recovery.
Transportation Research Part E: Logistics and Transportation
Review, 44(3), 2008, pp 455-474.
[4] Caruso, C., Colorni, A., & Paruccini, M. . The regional urban
solid waste management system: A modeling approach. European
Journal of Operational Research, 70(1), 1993, pp 16-30.
Fig.6. Normalised Values for RLOWI
[5] Aras, H., Erdogmus, S., & Koc, E. Multi-criteria selection for a
wind observation station location using analytic hierarchy process.
Renewable Energy, 29, (2004) pp 1383-1392.
VI. CONCLUSION
[6] Bian, W., & Yu, M.. Location analysis of reverse logistics
The reverse logistics practices may cost in millions of dollars operations for an international electrical manufacturer in Asia
for company. The implementation of these may be a risky Pacific using the analytic hierarchy process. International Journal
endeavor for the top management as it involves financial and of Services Operations and informatics, 1 (1/2), 187-201.
operational aspects, which can determine the performance of Management and Decision Making, 9 (4), (2006), 350-365.
the company in the long run. However, with the legislative
measures tightening up, there are not many options. The [7] V.Ravi, Ravi Shankar & M.K.Tiwari, Analyzing alternatives in
question now is not whether to go for it or not but which reverse logistics for end-of-life computers: ANP and balanced
framework to pick up. scorecard approach, Computers & Industrial Engineering
48,(2005),pp 327-356.
For the case undertaken in this study, the results indicate that
Third party reverse logistics (3PRL) is the first choice of the
case company which is followed by self support logistics
(SSL) and Virtual reverse logistics network (VRL).
Growing complexity of the logistics function and increased
impetus on core competence has led the company under study
to outsource logistics activities to third party reverse logistics
providers as the value of this alternative is higher( 0.510107)
than the other two alternatives. Another important factor
influencing the adoption of 3PRL is globalization.
The major contribution of this paper lies in the development of
a comprehensive model, which incorporates diversified issues
for conducting reverse logistics operations for EOL
computers. The C++ program developed for the execution of
the above ANP problem is more flexible, that it can be used
for any other type of industry under study.
161 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
Related docs
Other docs by ijcsiseditor
Digital Images Encryption in Spatial Domain Based on Singular Value Decomposition and Cellular Automata
Views: 0 | Downloads: 0
Agent Behavior in Multiagent Systems: Issues and Challenges in Design, Development and Implementation
Views: 1 | Downloads: 0
Optimizing Cost, Delay, Packet Loss and Network Load in AODV Routing Protocols
Views: 2 | Downloads: 0
