Multi-Objective Optimization of Electrochemical machining of EN31 steel by Grey Relational Analysis

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Abstract—Reverse logistics (RL) stands for all the operations
related to the reuse of used products, excess inventory of
products and materials including collection, disassembly and
processing of used products, parts, and/or materials. Over the
past few years, RL has received much attention because many
companies are using it as a strategic tool to serve their
customers and can generate good revenue. An efficient reverse
distribution structure may lead to a significant return on
investment as well as a significantly increased competitiveness
in the market. Therefore, analysis of barriers hindering the
successful implementation of RL is a crucial issue. These
barriers not only affect RL but influence each other also. In
existing models, the holistic view in understanding the
interrelation between the barriers is not accounted for but is
diagnosed independently. This paper utilizes the Interpretive
Structural Modeling (ISM) methodology to understand the
mutual influences among the barriers so that barriers that are
at the root of some more barriers (called driving barriers) and
those which are most influenced by the others (called driven
barriers) are identified.
Index Terms—Barriers, Interpretive Structural Modeling
(ISM) , Reverse logistics(RL), transitivity.
I. INTRODUCTION
In today’s manufacturing world, globalization policies and
rejuvenation have created a more intensive competition
amongst manufacturers. On the other hand, manufacturers
have turned to the option of adopting innovative technologies,
process re-engineering and strategies such as efficient supply
chain management to achieve a sustainable competitive
advantage. Supply chains are undergoing radical
transformations due to the mega-competition taking place on
a global scale. Technological changes are becoming a
primary driver in the domain of businesses. It is being
observed by companies that there is an increase in the flow of
returns of the product due to product recalls, warranty returns,
service returns, end-of-use returns, end-of-life returns, and so
on.
RL aims at the backward flow of materials from customer
to supplier with the goals of maximizing value from the
Manuscript received March 23, 2011; revised May 24, 2011.
Santosh Kumar Sharma is with the National Institute of Technology,
Rourkela India (e-mail: santoshsharma@csitdurg.in)
Biranchi Narayan Panda is with the National Institute of Technology,
Rourkela India (e-mail : Biranchi.panda3@gmail.com)
Siba Sankar Mahapatra is with the National Institute of Technology,
Rourkela 769008 India (phone: 91-661-2462512; fax: 91-661-2472926
e-mail: mahapatrass2003@yahoo.com).
Sadanand Sahu is with the Indian Institute of Technology, Kharagpur,
India (e-mail: sahus@mechiitkgp.ernet.in)
returned item or minimizing the total reverse logistics cost.
Reverse logistics (RL) can be defined as the process of
moving end products from their typical final destination for
the purpose of capturing value or proper disposal. A RL
system (RLS) incorporates a supply chain that has been
redesigned to manage the flow of products or parts destined
for remanufacturing, repairing, or disposal and to effectively
use the resources. Reverse logistics starts where the
traditional principles of supply chain management (SCM)
come to a conclusion; this is when a consumer product
reaches its end of life or use, and is redundant to its users. In
future, companies will have to look beyond the re-use or
recycling of packaging materials and into the potential value
recovery of redundant products and, more importantly, their
components and materials. This will enable them to establish
logistics infrastructures and supply management interfaces to
allow products to be re-used on similar markets rather than
being discarded, and eventually scrapped and disposed of in
landfill.
Over the past few years, RL has been gaining increasing
attention and awareness in the supply chain community, both
from practitioners and researchers point of view due to a
number of reasons. Competition and marketing motives,
direct economic motives and concerns with the environment
are some of the important reasons. RL is a complicated
process that requires detailed planning in terms of continual
audit of returns, determining the best disposition of products
that is both economically and technically feasible, warehouse
and transportation management, recycling programs, and
other related issues.
India is well endowed with both technology and human
resources. Despite this, the concept of Reverse logistics is yet
not widely accepted because of lot many barriers for its
successful implementation. Some of these barriers are lack of
systems, management inattention, financial resources,
personal resources, company policies. It is a risky endeavor
for the top management as it involves financial and
operational aspects which determine the performance of the
company in long run. The barriers mentioned not only affect
the operations of reverse logistics but also influences one
another. Thus, it is very essential to understand the mutual
relationship among the barriers. A critical analysis of the
barriers hindering RL and their interaction with the various
aspects in integrative planning can be a valuable source of
information to decision makers. The identification of barriers
which can aggravate few more barriers and those
independent barriers, which are most influenced by driving
barriers) would be helpful for the top management
implementing the reverse logistics programs. This can be a
guide for taking appropriate action to tackle barriers in
Analysis of Barriers for Reverse Logistics: An Indian
Perspective
S. K. Sharma, B. N. Panda, S. S. Mahapatra, and S. Sahu
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reverse logistics. An ISM approach has been proposed here
to for structuring the barriers.
II. LITERATURE REVIEW
During the early nineties, the Council of Logistics
Management started publishing studies where reverse
logistics was recognized as being relevant both for business
and society [1]. Other studies followed stressing the
opportunities on reuse and recycling [2]. In the late nineties,
marketing aspects of reuse and extending product life of
manufactured items have been focused and detailed
framework to set up and carry out reverse logistics programs
have been proposed. Rogers and Tibben-Lembke have
presented a broad collection of reverse logistics business
practices [3]. Eltayeb et al. have explored that taking back
products and packaging, business organizations can generate
benefits to the environment, in the form of reduced waste and
better resource utilization, in addition to economic benefits
and cost reductions to the organizations [4].
Carter and Ellram have investigated drivers and
constraints determining a company's reverse logistics
activities [5]. Based on a literature study, they identify
regulation and customer preferences as major stimulating
factors. At the same time, inferior quality of input resources
and a lack of stakeholder commitment are found to be major
obstacles for successful reverse logistics programs.
Moreover, they have suggested critical factors in the reverse
logistic process and developed a model that proposes how
these factors interact. Subramanian et al. have discussed
analysis and evaluation of RL strategies according to the
following decision making focus: Reverse Logistics Network
Structure, Relationships, Inventory management, and
planning and control [6].
Many articles dedicated to analysis of practice of reverse
logistics have appeared. Pokharel and Mutha have
investigated the current development in research and practice
in RL through content analysis of the published literature and
have shown that research publication on RL is increasing
specially after 2005 and therefore it shows the growing
recognition of RL as a driver of supply chain and logistics [7].
Janse et al. have summarized Barriers and facilitators in
managing reverse logistics in the consumer electronics sector
and provided a diagnostic tool for assessing a Consumer
Electronics company's RL practices and identifying potential
for RL improvement, from a business perspective [8].
In a complex system to structure the variables and get the
interrelation between them is always a matter of concern [9].
However, Interpretive structural modeling (ISM)
methodology which is a computer-assisted learning process
that enables individuals or groups to develop a map of the
complex relationships between the many elements involved
in a complex situation is used to understand interrelation
among elements. Faisal explored the barriers to corporate
social responsibility (CSR) in supply chains and presented a
hierarchy-based model and established the contextual
relationships among these barriers using ISM [10]. Raj et al.
identified enablers which help in the implementation of FMS
and analyzed the mutual interactions between them using
ISM approach. They explored that ISM methodology
strengthens the practical views of manufacturing managers
and depicts a clear picture about the significance of different
enablers [11]. Jharkharia and Shankar have used ISM
methodology to evolve the mutual relationship between
barriers to the IT- enablement of a supply chain [12]. Jha and
Devaya have presented a hierarchal model showing the
interrelationships between international construction risk
factors from the Indian construction professionals’ viewpoint
using ISM [13].
III. BARRIERS FOR REVERSE LOGISTICS
A. Lack of awareness about reverse logistics
The lack of awareness of benefits of reverse logistics is a
major barrier for its implementation. Today, the customers
have the benefits of greater product variety. It has resulted in
an increase in unsold products, rate of returns, packing
materials, and also the waste. This has given rise to increase
in the volume of product returns in the form of reverse
logistics. The reverse logistics can lead to economic benefits
by the recovery of the returned products for reuse,
remanufacturing, recycling, or a combination of these
options for adding value to the product.
B. Management Inattention
The conventional wisdom has been that over the last few
years, most companies have practiced reverse logistics
primarily because of government regulation or pressure from
environmental agencies, and not for economic gain. Thus the
management is taking less interest thinking no-profit issue.
Companies are organized around the forward flow of goods.
C. Financial Constraints
Cost considerations are a prime challenge in commercial
recycling. Companies require allocation of funds and other
resources for the implementation of reverse logistics.
Information and technological systems require more funds
because without these, the returns product tracking and
tracing and product recovery by various processes like reuse,
remanufacturing, recycling, etc. is not possible in the present
environment. The training of personnel related to the reverse
logistics is also very important for efficiently managing and
eventually making the reverse logistics profitable. However,
all these require financial support.
D. Personal Resources
A significant barrier to good reverse logistics is lack of
personnel resources .Lack of training and education is a
major challenge to commercial cycling. Education and
training are prime requirements for achieving success in any
organization.
E. Problems with product quality
The product quality is not uniform in reverse logistics
compared to the forward logistics where the product quality
is uniform. Customers usually expect the same level of
quality of product from the manufacturer regardless of the
nature of the returned product. The returned product quality
could be in any range; like that it could be faulty, damaged, or
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simply unwanted by the customer. Thus, there could be
variations in the pricing of the products.
F. Lack of appropriate performance management system
Measuring and managing the true performance of reverse
logistics is very hard. Internal and operational metrics are in
place, but metrics for end-to-end process performance are
seldom used or available. If the firms take action linking
their performance measurement system to their reverse
logistics practices, they will be in a better position to succeed
in their endeavor.
G. Inadequate information and technological systems
An efficient information and technological system is very
necessary for supporting the reverse logistics during various
stages of the product life cycle. Efficient information systems
are needed for individually tracking and tracing the returns of
the product, linking with the previous sales. Information
technology, software and hardware, is essential for
end-to-end control and transparency along the reverse chain.
H. Company policies
It also is related to corporate strategy for handling returns
and non-salable items. Because companies do not want to see
their “junk” cannibalizing their first quality or
“A” channel, they often develop policies that make it very
difficult to handle returns efficiently, and to recover much
secondary value from those returns.
I. Legal Issues
Under Indian Regulations excise paid goods once sold by
the manufacturer cannot be brought back to the plant without
prior documentation and declaration to excise authorities.
This is a very cumbersome & time consuming process and
non-compliance may mean that the manufacturer will have to
face legal actions. Most companies find this policy as a
hurdle in applying the reverse logistics.
J. Administrative and financial burden of tax
Proper planning and management of direct and indirect
taxes is a vital financial consideration within the reverse
chain. Complex (and cross border) flows of goods as well as
the diverse bought-in services engrained in the reverse chain
create a high degree of tax complexity and lead to unexpected
tax exposures and costs.
K. Limited forecasting and planning.
Accurate return forecasts are hardly available. This is a
direct barrier for both strategic and operational planning.
Many companies experience difficulties in forecasting and
planning the reverse chain due to the degree of diversity of
goods and flows.
L. Co-operative Behavior of Chain members
Co-operative behavior of chain members is desired for
sharing of information. Important barrier to the reverse
logistics is the reluctance of the support of the dealers,
distributors, and retailers towards the reverse logistics
activities.
IV. ISM METHODOLOGY AND MODEL DEVELOPED
Interpretive Structural Modeling was first proposed by J.
Warfield in 1973 to analyze the complex socioeconomic
systems. The ISM process transforms unclear, poorly
articulated mental models of systems into visible,
well-defined models useful for many purposes. It is a method
for developing hierarchy of system enablers to represent the
system structure.
ISM is an interactive learning process in which a set of
different and directly related elements are structured into a
comprehensive systematic model. The basic idea of ISM is to
decompose a complicated system into several subsystems
(elements) by using practical experience of experts and their
knowledge.
The important characteristics of ISM are as follows:
 This methodology is interpretive as the judgment of the
group decides whether and how the different elements
are related.
 It is structural on the basis of mutual relationship as
overall structure is extracted from the complex set of
elements.
 It is a modeling technique, as the specific relationships
and overall structure are portrayed in a digraph model.
 It helps to impose order and direction on the complexity
of relationships among various elements of a system.
The various steps involved in ISM methodology:
1) Identification of barriers: The elements of the system
are identified which are relevant to the problem or issue
and then achieved with a group problem-solving
technique like brain storming sessions. On the basis of
review of literatures for reverse logistics, a total 12
barriers were identified.
2) Contextual Relationship: From the barriers identified in
step 1, a contextual relationship is identified among
barriers with respect to which pairs of variables would
be examined. After resolving the barriers set under
consideration and the contextual relation, a structural
self-interaction matrix (SSIM) is prepared. Four symbols
are used to denote the direction of relationship between
the criterion (i and j):
V -- for the relation from element i to element j and
not in both directions;
A -- for the relation from element j to element i and
not in both directions;
X – for both the directional relations from element i to
element j and j to i;
O–if the relation between the elements did not appear
valid.
The following will explain the use of Symbols V, A X and
O in SSIM (Table I).
 Barrier 1 helps alleviate barrier 2 i.e. as the
awareness about reverse logistics will promote the
top management to start taking attention towards its
implementation. Thus the relationship between 1
and 2 is denoted by V
 Barrier 4 can be alleviated by barrier 7 i.e. with the
availability of adequate information and
technological systems the personal resources will
automatically get enriched with the facilities to
enable themselves in implementation of reverse
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logistics. Thus the relationship between 4 and 7 is
denoted by A.
 Barrier 2 and 4 helps to achieve each other .With the
trained and skilled employees the management can
understand the importance of reverse logistics in
present scenario and if management will take
attention then will surely plan to educate their
manpower to get support regarding the same.
Therefore the relationship between 2 and 4 is X.
 No relationship exists between financial constraint
and lack of appropriate performance management
system therefore is denoted by 0.
TABLE I STRUCTURAL SELF-INTERACTION MATRIX (SSIM)
3) Initial reachability matrix: The SSIM is transformed into
a binary matrix, called the initial reachability matrix by
substituting V, A, X, O by 1 and 0 as per the case. The
rules for the substitution of 1’s and 0’s are:
 If the (i, j) entry in the SSIM is V, then the (i, j) entry
in the reachability matrix becomes 1 and the (j, i)
entry becomes 0.
 If the (i, j) entry in the SSIM is A, then the (i, j) entry
in the reachability matrix becomes 0 and the (j, i)
entry becomes 1.
 If the (i, j) entry in the SSIM is X, then the (i, j) entry
in the reachability matrix becomes 1 and the (j, i)
entry also becomes 1.
 If the (i, j) entry in the SSIM is O, then the (i, j) entry
in the reachability matrix becomes 0 and the (j, i)
entry also becomes 0.
TABLE II. INITIAL REACHABILTY MATRIX
4) Final reachabilty matrix: The reachability matrix
obtained in step 3 is converted into the final reachabilty
matrix by checking it for transitivity. The transitivity of
the contextual relation is a basic assumption in ISM
which states that if element A is related to B and B is
related to C, then A is related to C.
TABLE III. FINAL REACHABILTY MATRIX
5) Level partition: The reachabilty and antecedent set for
each barrier is found out from final reachabilty matrix.
The reachabilty set includes criteria itself and others
which it may help to achieve and antecedent set consists
of itself and other criterion which helps in achieving it.
Subsequently, the intersection set is derived and the
variable having reachabilty and intersection set same is
given top level in ISM hierarchy.
Table IV shows the first iteration where in barrier 5 and
12 are found at level I
TABLE IV. PARTITION OF REACHABILTY MATRIX: ITERATION 1
Once the top level element is found out, it is separated
from other elements. In the similar manner iteration process
is repeated to find the criterion in the next level and is
continued till the level of each element is found . (Table
V,VI,VII, and VIII)
TABLE V. PARTITION OF REACHABILTY MATRIX: ITERATION 2
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TABLE VI. PARTITION OF REACHABILTY MATRIX: ITERATION 3
TABLE VII. PARTITION OF REACHABILTY MATRIX: ITERATION 4
TABLE VIII. PARTITION OF REACHABILTY MATRIX: ITERATION 5
Table IX shows the final partition level of barriers for
reverse logistics after all iterations.
TABLE IX. LEVELS OF BARRIERS FOR REVERSE LOGISTICS
6) Development of ISM model: Diagraph for interpretive
structural modeling is drawn. Having identified the levels of
the elements, the relation between the elements is drawn
with the help of an arrow. The diagraphs thus drawn are
complex in nature. The level I barriers is given top level in
the hierarchy and it won’t help any other barrier to achieve.
The barriers having same level are kept on the same level of
hierarchy the diagraphs give information about hierarchy
between the elements of barriers for successful
implementation of reverse logistics.
Fig. I. ISM based model for barriers of reverse logistics
V. MICMAC ANALYSIS
The MICMAC analysis has been done by drawing simple
two dimensional graphs fig. 2. The objective of the
MICMAC analysis is to analyze the driver power and
dependence of variables
Fig. II. Driver Power and Dependence Diagram
The barriers of reverse logistics are classified into four
clusters:
 The first cluster consists of autonomous variables that
have weak driver power and weak dependence.
These variables are disconnected from the system,
with which they have only a few but strong links.
 The second cluster consists of the dependent variable
that have weak driver power but strong dependence.
 The third cluster has the linkage variables that have
strong driving power and also strong dependence.
These variables are unstable in that any action on
these variables will have an effect on others and also
feedback effect on themselves.
 The fourth cluster includes the independent variables
having strong driving power but weak dependence. It
is observed that variables with very strong driving
power, called the key variables, fall into the category
of independent variables. The driving power and the
dependence of each of the variables are calculated.
VI. DISCUSSION AND CONCLUSION
The methodology proposed here identifies the hierarchy of
actions to be taken for handling different barriers hindering
the implementation of reverse logistics. The managers can
get an insight of these barriers and understand their relative
importance and interdependencies. Some of the barriers are
identified and are put into an ISM model to analyze the
interaction between them. The driver dependence diagram
gives some valuable insight about the relative importance and
interdependencies among barriers. From figure 2 it can be
seen that there is no autonomous barrier. Problems with
product Quality, Inadequate Information and technological
systems, limited forecasting and planning and co-cooperative
behavior of Chain members have a weak driving power, but
strong dependence on other barriers. This indicates that it
requires all of other barriers to come together for overcome
difficulties in successful implementation of Reverse logistics.
Management Inattention, lack of appropriate performance
management system, personal resources, company policies
and administrative and financial burden of tax comes under
category of linkage variables. They have strong driver power
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105

and strongly dependence power. These enablers should be
studied even more carefully than the others. The analysis
reveals that three barriers Lack of awareness about reverse
logistics, Financial Constraints and Legal issues are ranked
as Independent enablers as they are having the maximum
driver power. This implies that these variables are key
barriers in the successful implementation of Reverse
Logistics in Supply Chain.
Thus the ISM based model proposed for identification of
barriers of reverse logistics can provide the decision makers a
realistic representation of the problem in the course of
implementing reverse logistics. This can help in deciding the
priority to proactively take steps in combating these barriers.
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