Integrating transport systems in supply chain management software tools
| Published date | 01 October 2003 |
| DOI | https://doi.org/10.1108/02635570310489205 |
| Pages | 503-515 |
| Date | 01 October 2003 |
| Author | Antonio C. Caputo,Pacifico M. Pelagagge,Federica Scacchia |
| Subject Matter | Economics,Information & knowledge management,Management science & operations |
Integrating transport systems in supply chain
management software tools
Antonio C. Caputo
Faculty of Engineering, University of L'Aquila, L'Aquila, Italy
Pacifico M. Pelagagge
Faculty of Engineering, University of L'Aquila, L'Aquila, Italy
Federica Scacchia
Faculty of Engineering, University of L'Aquila, L'Aquila, Italy
1. Introduction
Supply chain management (SCM) involves
planning and management of material,
information and financial flows in a network
consisting of manufacturers, distributors,
vendors and customers with the objective of
reducing operating costs and improving
customer service (Lummus and Vokurka,
1999) (Figure 1).
The ever-increasing complexity and
globalization of production processes and
markets are shifting the attention from the
performances of single firms to competitive
advantages of entire SC. In particular the
transition from mass production to mass
customisation requires companies' ability to
effectively and efficiently coordinate
activities, such as production and
transportation, across SCs that are
dynamically set up in response to constantly
changing and increasingly customized
market requirements (Furst and Schmidt,
2001).
Consequently the major goal of most
manufacturing organizations is the
development and adoption of global SCM
approaches based on higher levels of
integration and coordination, with the aim of
improving competitiveness and enhancing
customer service (Chandra and Kumar, 2000,
2001; Copachino, 1997; Poirier and Reiter,
1996).
Within this context, logistics strategies,
and in particular transportation decisions,
can be considered as key factors to increase
SC effectiveness. More specifically, the
optimization of logistics networks enables
transport and storage costs reduction and
quick response, leading to higher customer
satisfaction (Lummus et al., 2001; Stank and
Goldsby, 2000). In fact transportation services
play a central role in seamless SC operations,
moving in-bound materials from supply sites
to manufacturing facilities, repositioning
inventory among different plants and
distribution centres, and delivering finished
products to customers (Figure 2).
Benefits accruing from world-class
operations at the locations of supply,
production, and customers are pointless
without the accompaniment of appropriate
transportation planning and execution (Fox,
1992).
Moreover, in recent years the scope of SCM
has evolved to cross the enterprise
boundaries, involving numerous
participants in a logistics network that,
because of globalization of markets, is often
geographically distributed throughout the
world (Archibald et al., 1999), making the role
of the transportation system still more
prominent. As a matter of fact,
transportation management is an area that
remains critical to overall logistics and SC
success.
Such a complex scenario emphasizes the
importance of intertemporal coordination of
all SC activities, as well as their functional
merging, and at the same time highlights the
growing need of integrating not only
materials, cash and information flow, but
also production processes among
participants to a logistics network (Shapiro,
1999).
The traditional approach for SC modelling
is represented by linear programming (LP)
(Ignizio, 1982; Takakuwa, 1998; Tayur et al.,
1999). The LP approach is effective in
implicitly and quickly generating and
evaluating large numbers of alternative
designs, providing a global optimal solution.
Nevertheless LP has a deterministic
structure that is not able to consider
stochastic effects through time, precluding
dynamic analysis of SC. Moreover, a number
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[ 503 ]
Industrial Management &
Data Systems
103/7 [2003] 503-515
#MCB UP Limited
[ISSN 0263-5577]
[DOI 10.1108/02635570310489205]
Keywords
Supply chain management,
Logistics, Transport operations,
Simulation,
Geographic information systems,
Software tools
Abstract
Logistic strategies represent a
key factor to increase supply
chain (SC) effectiveness, as the
optimization of logistics networks
enables transport and storage
costs reduction as well as quick
response leading to higher
customer satisfaction. A useful
approach for SC performance
improvement may be pursued by
resorting to advanced software
tools able to analyze complex
production scenarios, performing
concurrent, synchronized and
distributed simulations. Support to
the logistics planning phase is
offered by geographical
information system technology,
included in the simulation
environment in order to manage
related geographical data (i.e.
warehouse location, choice of
vehicle routeings, etc.). In the
paper the main characteristics of
the proposed hardware and
software architecture have been
illustrated, focusing attention on
the logic phases for
implementation by the transport
federate. Furthermore, a
preliminary functionality validation
of the developed tool is presented
with reference to simplified test
cases.
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