Intelligent Information Management, 2012, 4, 261-268
http://dx.doi.org/10.4236/iim.2012.425037 Published Online October 2012 (http://www.SciRP.org/journal/iim)
Modeling and Simulation of Textile Supply
Chain through Colored Petri Nets
Francisca Santana-Robles1, Joselito Medina-Marín2, Oscar Montaño-Arango2,
Juan Carlos Seck-Tuoh-Mora2
1Academic Area of Engineering, School Higher of Sahagún City, Autonomous University of Hidalgo State, Pachuca, México
2Advanced Research Center in Industrial Engineering, Autonomous University of Hidalgo State, Pachuca, México
Received August 31, 2012; revised October 3, 2012; accepted October 12, 2012
ABSTRACT
The purpose of this paper is to describe the business process modeling and simulation of a textile supply chain using
Colored Petri nets. Our model takes into account both the source process and delivery logistics that exist between any
two members of supply chain; moreover, we model other activities performed by the company such as manufacturing
clothing. The model has been built to acquire a better understanding about the behavior of a textile company in the ful-
fillment of requests from costumers. The model has been built using CPN Tools. This model was built with modules for
activities of the supply chain textile, e.g. receiving orders of customers, determination of production plan, procurement
raw material, transportation of raw material, production and delivering products to customers. This modularized model
offers some advantages to represent complex supply chains according to their structure and requirements. Thus, we can
add modules easily depending on the necessary activities.
Keywords: Supply Chain; Business Process; Business Process Modeling Techniques; Colored Petri Nets
1. Introduction
The global competitive business environment and ad-
vances in information technology have forced enterprises
to look for efficiencies in their internal operations as well
as in coordinated operations with their suppliers and
customers. This forced enterprises to evaluate the per-
formance of their supply chain. Companies are improv-
ing their performance by a constant evaluation of the
value added in all parts of their processes. In this field,
simulation is a valuable tool to evaluate the design and
redesign of business process. Simulation approach offers
several advantages. Simulation is recognized to allow
more realistic observation of the supply chain behavior
or of complex economic models in general. It allows an
analysis of the supply chain dynamics and leads to an
observations along time. There are software tools to si-
mulate business process [1-3]. In [1] the authors describe
three categories of software tools that can be used for
business processes simulation (BPS). These categories
are business process modeling tools, business process
management tools, and general purpose simulation tools.
For each type they describe two specific tools and they
evaluate their applicability for BPS. They categorize
Protos and ARIS as Business process modeling tools;
FLOWer and FileNet as business process management
tools; and Arena and CPN Tools as general purpose
simulation tools; this is shown in Tables 1-3. On the
other hand, there are diverse techniques to model busi-
ness processes in supply chain [2,3] they propose tax-
onomy of classification oriented to supply chain. The
taxonomy includes the following process perspectives:
functional, behavioral, organizational, and informational;
similarly, they propose business process modeling tech-
niques, for example Petri Nets to model functional and
behavioral perspectives.
Textile and clothing industry is highly diverse and
heterogeneous. Moreover, in today’s markets competi-
tion is no longer on a company versus company model,
but instead of supply chain versus supply chain. In order
to success, companies need to achieve integration with
customers and suppliers. In addition, supply chain in
textile industry is complex. Supply chain is relatively
long, with a number of parties involved. Consequently,
careful management of supply chain is required in order
to reduce lead times and reach quick response, high-
lighting the need to use an approach such as agility [4].
In this field, Colored Petri Nets are a valuable tool to
build a model of textile supply chain because they give
the flexibility in the specification of the supply chain
configuration. An advantage of analyzing textile supply
chain simulation by using Colored Petri Nets is that
C
opyright © 2012 SciRes. IIM

F. SANTANA-ROBLES ET AL.
262
Table 1. Modeling capabilities.
Feature Protos ARIS FLOWer FileNet Arena CPN Tools
Ease of model building ++ + + + + − −
Formal semantics/verif. + − − − − − +/− ++
Workflow patterns + − + +/− + +
Resources and data + ++ ++ +/− + +/−
Level of detail ++ ++ ++ + ++ − −
Table 2. Simulation capabilities.
Feature Protos ARIS FLOWer FileNet Arena CPN Tools
Performance dimensions − − ++ − − + ++ ++
Distributions + + − − − − ++ ++
Animation − − + − − + ++ +
Scenarios − − − − − +/− + +
Table 3. Output analysis capabilities.
Feature Protos ARIS FLOWer FileNet Arena CPN Tools
Statistics − − − − − − ++ ++
Format − +/− − − +/− + +/−
What-if analysis − − + − − − − − −
Conclusion-making support − − + − − − + − −
fewer assumptions need to be made regarding the behav-
ior of the system being modeled. The step in simulation
analysis covers both output-data and experimental design.
Simulation software, e.g. CPN Tools, provides basic
support for running and analyzing terminated simulations
and has capabilities for providing 95% confidence inter-
vals. An advantage of Coloured Petri Nets is that there
exist the potential for varying the values of non-numeri-
cal parameters when defining different configurations.
We have reviewed the literature and we have found
that Coloured Petri Nets have been used to model differ-
ent types of supply chains. However, they have not been
used to model and simulate textile supply chain. The
innovation of this paper is to show a model built with
modular Coloured Petri Nets. This model was built with
modules for activities of the supply chain textile, e.g.
receiving orders of customers, determination of produc-
tion plan, procurement raw material, transportation of
raw material, production and delivering products to cus-
tomers. This modularized model offers some advantages
to represent complex supply chains according to their
structure and requirements. Thus, we can add modules
easily depending on the necessary activities.
This paper shows the business process modeling and
simulation of a textile supply chain using Colored Petri
nets. The objective of the model has been built to acquire
a better understanding about the behavior of the textile
company in the fulfillment of requests from costumers.
The model has been built using CPN Tools.
2. Supply Chain
“One of the most significant paradigms shift of modern
business management is that individual business no
longer compete as solely autonomous entities, but rather
as supply chain”. Success of the single business will de-
pend on management’s ability to integrate the company’s
intricate network of business relationships [5].
A supply chain is composed of all parties involved di-
rectly and indirectly in the fulfillment of request from a
costumer [6]. Figure 1 shows a supply chain network
formed out of complex intercommunications amongst
various manufacturing companies and service providers
such as raw material vendors, original equipment manu-
facturers, logistics operators, warehouses, distributors,
retailers and customers [7]. There are four characteristics
of a supply chain: first, it goes through several stages of
increasing intra- and inter-organizational, vertical coor-
dination. Second, it includes many independent firms,

F. SANTANA-ROBLES ET AL. 263
Figure 1. The supply chain network.
suggesting that managerial relationship is essential. Third,
a supply chain includes a bi-directional flow of products
and information, and managerial and operational activi-
ties. Fourth, chain members aim to fulfill the goals to
provide high customer value with an optimal use of re-
courses.
In addition, the management of multiple relationships
across the supply chain is referred to as Supply Chain
Management (SCM). SCM deals with total business
process excellence and represents a new way of manag-
ing the business and relationships with others members
of the supply chain. SCM is the integration of key busi-
ness processes from end user through original suppliers
that provides products, services, and information that add
value for customers and others stakeholders [5].
3. Textile Garment Supply Chain
The Textile garment supply chain is comprised of a
group (garment supply chain) and members (retailer,
apparel, maker, textile manufacturer and fibre manufac-
turer). The network is arranged in the order that the flow
of materials, processes, and information occurs between
its members [8-11]. Figure 2 depicts a design of the tex-
tile garment supply chain. Customer demand is relayed
by retailer to apparel maker, textile manufacturer, fibre
manufacturer and ultimately to cotton grower.
4. Colored Petri Nets
Colored Petri Nets (CPN) is a graphical oriented lan-
guage for design, specification, simulation and verifica-
tion of systems. The more compact representation has
been achieved by equipping each token with an attached
data value (called the token color). The data value may
be of arbitrarily complex type. The use of color sets in
CPN is totally analogous to the use of types in program-
ming languages. Typical examples of application areas
are communication protocols, distributed systems, im-
bedded system, automated productions systems, and
workflow analysis [12-14]. On the other hand, CPN
Tools is a tool used to construct, modify, syntax check
and simulate CPN. The most important advantage of us-
ing computerized CPN Tools is the possibility of obtain-
ing better result. The CPN editor provides the user with a
precision and quality which by far exceed the normal
manual drawing capabilities of human beings. A second
advantage is the possibility of obtaining faster results. As
an example, the CPN editor multiplies the speed by
which modifications can be made. A third advantage is
the possibility of making interactive presentations of the
analysis results. The CPN simulator makes it easy to
trace the different occurrence sequences in a CPN [12].
5. Model of the Textile Supply Chain
Figure 3 depicts the supply chain of the textile company
modeled in this paper. Supply chain is linked by five
members: 1) Fibrer manufacturers (wool and synthetic
fibres), 2) Textile and accessories manufacturers, 3) Ap-
parel maker, 4) Distribution center, and 5) Retailers. This
company is apparel marker. It has two types of suppliers
(Textile manufacturer and Accessories Manufacturer)
and three customers (two retailers and one distribution
centre); moreover, it has supplier’s suppliers (fibre ma-
nufacturer) and customer’s customer (two retailers).
In addition, the garment poduction processing steps r

F. SANTANA-ROBLES ET AL.
264
Figure 2. Textile garment supply chain.
Figure 3. The supply chain of the textile c ompany modeled.
and techniques involved in the manufacturing garments
for the large scale of production in industrial basis for
business purposes is called Garments Manufacturing
Technology. The basic Production Flowchart of a gar-
ment includes following activities (some of the process
can be added or removed): Design or Sketch, Pattern
Design, Sample Making, Production Pattern, Grading,
Marker Making, Spreading, Cutting, Shorting and Bun-
dling, Sewing and Assembling, Inspection, Pressing or
Finishing and Packing. In this case study, we focus on
the following activities: Design, Cutting, Sewing and
Assembling, Finishing and Packing.
5.1. Problem Description
The company has high inventory levels due to uncer-
tainty and risks throughout the chain and also high pro-
duction costs due to low fulfillment rate of suppliers. In
addition, the company has low fulfillment rate.
5.2. Model Description
Figure 4 shows the conceptual model of the business
process of the company. This process is modeled through
of modular Colored Petri Nets. Because the Petri nets has
been proven an effective language for modeling concur-
rent and asynchronous systems because of its clear
graphical representation and extensive expressiveness for
modeling both qualitative and quantitative systems. Fos-
tered by its highly human, comprehensible and visual
format, it is also used for modeling structural dynamic
systems in production. A modular colored Petri net
(MCPN) is a modular structure which is composed of
one or more colored Petri net modules. Each colored

F. SANTANA-ROBLES ET AL. 265
Figure 4. Conceptual model of supply chain of the textile c ompany (Source processes, manufacturing and delivery logistics).
Petri net module, in turn, encapsulates a CPN. Our model
begins with the design of clothing; next the catalogues
are made and are delivered to customers. Customers
place orders, company receives these orders and deter-
mines the quantity to order, next company places orders
to suppliers. Suppliers receive orders and check exis-
tences in their inventory, if they have enough raw mate-
rials in stock then schedule products deliveries, generate
the corresponding invoice and deliver products; however,
if suppliers are out stock then they place orders to sup-
pliers, receive products, authorize suppliers’ payment
and schedule products deliveries, invoice and deliver
products. Company receives products, authorizes suppli-
ers’ payment and begins manufacturing clothing, packing
and delivering to customers. The process described
above is shown in Figure 4. In addition, these processes
shown in Figures 4-9 are modeled in CPN Tools. Figure
5 shows the design process, the delivering of the cata-
logues to customers, receiving of orders and compute of
raw materials; similarly, Figure 6 shows the place orders
to suppliers, the receiving to orders suppliers’, checking
existences and confirmation of the orders. Figure 7
shows the compute of the transportation cost from cor-
poration suppliers to company and date of delivering.
Figure 8 shows garment manufacturing process (Design,
Cutting, Sewing and Assembling, Finishing and Packing)
and deliver products to customers. Finally, Figure 9 shows
some results obtained after run the model. It is impor-
tant to note that this textile supply chain is type pull
because trough the customers the supply chain activities
start. Furthermore, trends in clothing markets change
frequently.
6. Conclusions
We described the modeling of the supply chain of the
textile company using Colored Petri nets. CPN are a
powerful tool to model complex system of manufacturing
and logistics process which include: transportation, in-
ventory management, orde processing, warehousing, r

F. SANTANA-ROBLES ET AL.
266
Figure 5. Design process, delivering of the catalogues to customers, receiving of orders and compute of raw materials.
Figure 6. Place orders to suppliers, the receiving to orders suppliers’, checking existences and confirmation of the orders.
distribution and production. With our model we can
know the company performance. We can be able to know
how affect the behavior of the supplier’s company in the
fulfillment of requests from costumers’ company. We
could observe how affect the quantity of existences in
inventory in the manufacturing processes of company;
moreover could know the importance of sharing infor-
mation between members of supply chain to reduce un-
certainty. In the results obtained after run the model we
could observe the average of occupation of the production

F. SANTANA-ROBLES ET AL. 267
Figure 7. Compute of the transportation cost from corporation suppliers’ to company and date of delivering.
Figure 8. Garment manufacturing proc e ss and de live r pr oduc ts to c ustome r s.
equipment. This is important for the reason that in the
textile supply chain require to eliminate waste including
time because retailers require rapid replenishment of
product, and shipments need to meet strict requirements
in terms of the delivery times, order completeness and
accuracy. In addition, is necessary the supply chain need
to find an effective response to constantly changing and
highly competitive business environment. With simula-
tion results to able to react to possible volatile fluctua-
ions in demand. t

F. SANTANA-ROBLES ET AL.
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Timed statistics
Name Count Avrg Min Max
Marking_size_New_Page’En_produccion1_1 26 0.083333 0 2
Marking_size_New_Page’En_produccion_2_1 26 0.088889 0 3
Marking_size_New_Page’En_produccion_3_1 26 0.000000 0 1
Marking_size_New_Page’En_produccion_4_1 26 0.019444 0 1
Marking_size_New_Page’Recursos_corte_1 26 1.916667 0 2
Marking_size_New_Page’Recursos_acabado_1 26 4.000000 3 4
Marking_size_New_Page’Recursos_confeccion_1 26 4.911111 2 5
Marking_size_New_Page’Recursos_empaquetado_1 26 3.980556 3 4
Figure 9. Results obtained after run the model.
In the further research, we want to extend our model to
calculate some performance attributes of the SCOR
Model such as Delivery Performance, Fill Rates, Perfect
Order Fulfillment and Cost of Goods.
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