International journal of computer integrated manufacturing , tập 23, số 1, 2010

International Journal of Computer Integrated Manufacturing
Vol. 23, No. 1, January 2010, 1–19

Development of collaborative transportation management framework
with Web Services for TFT–LCD supply chains
M.-C. Chena*, C.-T. Yehb and K.-Y. Chenc
a
Institute of Traffic and Transportation, National Chiai Tung University, Taiwan, ROC;
Department of Industrial Management, National Taiwan University of Science and Technology, Taiwan, ROC;
c
Department of Industrial Engineering and Management, National Taipei University of Technology, Taiwan, ROC
b

(Received 20 July 2008; final version received 3 May 2009)
Under the fierce global competition, enterprises face the challenge to respond quickly and accurately to customers’
diverse requirements. Excessive lead time, improper control of transportation resources and inaccessibility of
tracking information may lead to ineffective and unreliable delivery. The seamless integration of trading partners
such as suppliers, manufacturers and global third party logistics service providers (G3PLs) can improve the supply
chain execution. With supply chain collaboration, lead time can be significantly shortened whereas the resource
utilisation can be highly improved. Recently, collaborative transportation management (CTM) has provided the
collaborative mechanisms of information sharing and order fulfillment for carriers and trading partners in supply
chains. CTM initiative can reduce the ineffective transportation sections and better the delivery effectiveness. The
heterogeneous information systems first should be integrated for starting up information sharing and data
integration among carriers and trading partners. Web services possess characteristics of flexibility and
interoperability that are suited for developing the inter-enterprise collaboration platform by integrating
heterogeneous systems. With the web-services based CTM (WS–CTM), carrier and trading partners can collaborate
on the process of order fulfilment. In this paper, the WS–CTM framework is developed to collaboratively manage
transportation and distribution for a supply chain of thin film transistor liquid crystal display (TFT–LCD). The
proposed WS–CTM can assist the panel manufacturers, system manufacturers and G3PLs to reduce the uncertainty
in distribution, and improve the supply chain performance.

Keywords: supply chain management; collaborative transportation management; global logistics; Web Services;
TFT–LCD; e-Business

1.

Introduction

With the fierce global competition and the falling profit
margin, most companies engage in a global supply
chain to maintain the market share and to intensify the
profit (Tyan et al. 2003). Managing the global supply
chain is much more complicated compared with
managing the domestic supply chain (MacCarthy and
Atthirawong 2003). Excessive lead time, improper
control of transportation resources and inaccessibility
of tracking information may lead to ineffective and
unreliable delivery. The seamless integration of trading
partners such as suppliers, manufacturers and global
third party logistics service providers (G3PLs) can
improve the supply chain performance. Generally
speaking, lengthy lead time results in a higher level
of inventory and a higher cost. In addition, the global
distribution causes a notable increase of transportation
cost (Meixell and Gargeya 2005). The decision making
in a global supply chain has a higher impact on
performance. Collaboration and strategic alliance are

*Corresponding author. Email:
ISSN 0951-192X print/ISSN 1362-3052 online
Ó 2010 Taylor & Francis

DOI: 10.1080/09511920903030353


known as effective mechanisms reducing the uncertainty and risk in global business.
For achieving a certain customer service level,
suppliers generally concern about the accurate and
reliable delivery of products to the locations assigned
by buyers. On the other hand, 3PLs focus on satisfying
the delivery requirements set by customers and
maximising the utilisation of transportation resources.
To maximise the supply chain performance globally,
involved members need to collaborate on planning,
forecasting and execution. Collaborative planning,
forecasting and replenishment (CPFR) has hence
been introduced in supply chain management. Traditionally, the related issues of supply chain collaboration centre around material supplier–manufacturer
and manufacturer–retailer. The logistics of order
fulfilment is an extremely complicated process which
includes order generation, order picking, shipping,
transportation, payment, invoicing and so on. In
particular, these activities are performed geographically distributed in global business. Enterprises,


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M.-C. Chen et al.

generally, outsource their logistics function to 3PLs to
reduce the logistics cost as well as to concentrate on
their core competitive advantages.
Carriers or 3PLs are not often considered in the

seller–buyer collaboration and strategic alliance. However, carriers play the role of order execution as
physically delivering the goods to the locations
appointed by receivers. In addition to CPFR, collaborative transportation management (CTM) (CTM
Sub-Committee of the VICS Logistics Committee
2004) provides a collaboration mechanism among seller,
buyer and carrier. The initiative CPFR focuses primarily
on the planning of order fulfilment, whereas CTM
makes up the link between planning and execution.
For bringing the carrier in collaboration, shippers
(sellers) and receiver (buyers) need to share the related
information such as order forecasting, replenishment
plan, etc. such that carriers can plan the transportation
resources in advance and execute the delivery better.
Sellers and buyers can easily track the goods in transit
with the mechanism of distribution information sharing. The exceptions in goods delivery (e.g., delivery
delay) can be controlled in real time as well as can be
resolved collaboratively. Information sharing is an
essential task of supply chain collaboration. However,
the heterogeneous information systems among supply
chain partners cause a huge difficulty in information
exchanging and sharing.
This paper proposes a CTM platform (namely WS–
CTM) for a supply chain of thin film transistor liquid
crystal display (TFT–LCD). This platform integrates
the capability of Web Services with heterogeneous
systems in supply chains as a virtual system. Characteristics of Web Services such as flexibility and interoperability are particularly suited for developing the
inter-enterprise collaboration platform among heterogeneous systems. The proposed WS–CTM can assist the
panel manufacturers, system manufacturers and G3PLs
to reduce the uncertainty in distribution, and improve
the supply chain execution. They can collaboratively

execute the order fulfilment on WS–CTM platform to
increase the accuracy and reliability of distribution.
2. Web services and supply chains
Web Service (WS) is a new information technology of
web application (W3C 2004). Web Services are selfcontained, self-describing, modular applications that
can be published, located, and invoked across the web.
They are bases on open standards, i.e. hypertext
transfer protocol (HTTP), extensible markup language
(XML), simple object access protocol (SOAP), universal description discovery and integration (UDDI),
web services description language (WSDL) and a
common architecture, service-oriented architecture

(SOA), to integrate heterogeneous business systems
and to support interoperable machine-to-machine
interaction over a network (W3C 2004). With the
self-recitation property of XML and WSDL, various
software components can recognise one another.
SOAP is a messaging protocol which allows components to interact each other. UDDI is a set of protocols
which can describe, register, search and integrate
service components.
With the trend of global supply chain and door-todoor service, the traditional distribution architecture
may not meet the diversified customers’ requirements.
In global business, inter-modal and/or multi-modal
transportation are necessary to execute the order
fulfilment process which increase the lead time in
consolidation and transportation (Tyan et al. 2003).
The strategic alliance among sellers (shippers), buyers
(receivers) and carriers (3PLs) can foster the logistics
efficiency and quality (Andersson 1995). The trading
partners can benefit from the strategic alliance with

3PLs for performing distribution activities. The
benefits include the larger economic scale, larger
bargaining power, better service accessibility, enabling
knowledge learning, investment reduction and so on.
G3PLs serve as a virtual global distribution centre to
link the supply chain members globally dispersed
(Tyan et al. 2003). Taking Taiwan’s Note Book (NB)
industry as an example, although companies have a
superior capability in manufacturing, they integrate
G3PLs (e.g. FedEx) to distribute products for enabling
door-to-door service.
Web Services support a new model for inter-system
and inter-enterprise collaboration. Web Services can
realise the network manufacturing, in which heterogeneity exists and must be addressed. Shen et al. (2007)
proposed ontology to deal with the heterogeneity in
Web Services composition. Hung et al. (2005) proposed a Web Services based e-Diagnostics Framework
(WSDF), which integrates diagnostics information
with Web Services technologies. WSDF can automatically collect equipment data, remotely diagnose, fix,
and monitor equipment, and analyse and predict the
equipment performance over the intranet and internet.
Dhyanesh et al. (2003) proposed a methodology for
constructing Web Services based infrastructure for
cross-enterprise collaboration, namely DEVISE, which
consists of a set applications. Flexibility, efficiency and
trustworthiness have become the crucial concerns in
the fierce market, and Web Services can provide a
solution for these concerns and business processes
integration (BPI). Yang et al. (2005) developed a
trustworthy Web Services based framework for BPI.
With the rapid growth of e-commerce, business

competition is much fiercer than years ago. A company
needs to build stronger relationship with its trading


International Journal of Computer Integrated Manufacturing
partners and customers for keeping their competitive
advantages. E-business is to perform the core business
processes on the internet which not only include
purchasing, selling products and services, but also
collaborating with trading partners on the internet.
The process integration is the key for successful
e-business implementation.
Chen et al. (2007) proposed a collaboration
architecture that uses Web Services for Business
Process Management (BPM) in support of collaborative commerce (C-commerce). With the advancement
of Web Services and BPI tools, BPM can execute Ccommerce more flexibly and dynamically. For modern
enterprises, various kinds of systems and applications
need to interoperate more flexibly and to be easily
integrated. Kalogeras et al. (2006) presented a distributed architecture utilising Web Services as a single
common interface to vertically integrate the application systems. Michalakos et al. (2005) used Web
Services to support the CPFR implementation, especially to facilitate the process of exchanging forecasting
outputs among heterogeneous systems of trading
partners. Web Services provide a mechanism for the
integration of buyer’s and seller’s heterogeneous
systems to facilitate information flow and collaboration along a supply chain.
Supply chain collaboration has become an important issue to enterprises. Supply chain partners can
benefit more from the higher degree of collaboration
(Simatupang and Sridharan 2004, Holweg et al. 2005).
Supply chain collaboration aims at integrating all
partners to work as one virtual network toward

common goals (Mentzer et al. 2000). Because retailers
have a greater power in supply chains, CPFR
Table 1.

The applications of TFT–LCD.

Panel size (in.)

Applications

5–7

Mobile Phones, PDAs, Handheld PCs,
Navigators, other portable information
and communication products
Sub–NB PCs, small LCD TVs
NB, PCs
LCD monitors
LCD monitors, LCD TVs

7–10
10–14.1
15
Over 15

Figure 1.

The TFT–LCD supply chain architecture.

3

programs are frequently initiated by retailers. They
therefore play the role of hub in supply chains in order
to reduce the bullwhip effect. From Chen et al. (2007),
it may be better to start the collaboration initiative
from a retailer (buyer)-driven program. CTM is an
initiative of deeper and wider supply chain collaboration because it extends the procedure of CPFR, as well
as CTM invites more partners to join the initiative.
CTM transforms order forecasts generated by CPFR
into shipment forecasts, and it brings about collaboration among shipper, receiver and carrier to ensure
accurate order fulfilment (Esper and Williams 2003).
3.

The TFT–LCD supply chain

Thin film transistor liquid crystal display (TFT–LCD)
industry is a technology-, capital-, and skilled personnel-intensive one in which the products have the
characteristics of short life cycle, high cost and high
value-added. The applications of TFT–LCD are
summarised in Table 1 (ITRI 2002). Owing to the
governmental initiatives, Taiwan has become one of
the main producers of LCD monitor. The competitive
advantage of Taiwan’s TFT–LCD industry is the huge
demand stemmed from the manufacturers of NB and
Personal Computer (PC).
Owing to the complex product structure and the
highly geographically dispersed component providers,
the supply chain integration can be a critical basis for
the success of TFT–LCD industry. Excellent logistics
network and collaboration can support a seamless and

effective integration for a TFT–LCD supply chain. The
TFT–LCD supply chain is complex with a wide variety
of engaged members belonging to several tiers. Figure 1
schematically illustrates the supply chain architecture
of TFT–LCD consisting of materials suppliers, panel
manufacturers, module and system manufacturers
(e.g., LCD monitor, LCD TV, PDA, cellular phone),
brand-owned channels.
Taiwan’s TFT–LCD industry focuses on the
section of manufacturing (ITRI 2006). The current
difficulties in this section are as follows:
(a) Materials suppliers: The demand of materials is
difficult to control because the downstream


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module/system manufacturers’ demand variations are high. Additionally, the complexity,
long lead-time and information invisibility in

the TFT–LCD supply chain cause the bullwhip
effect such that the inventory level is set high to
buffer the sharp fluctuation of production plan.

Figure 2.

The international supply chain of Taiwan’s TFT–LCD industry.

Figure 3.

The global logistics network of Taiwan’s TFT–LCD industry.


International Journal of Computer Integrated Manufacturing
(b) Panel manufacturers: For panel manufacturers,
the order cycle time of material procurement is
extended because the critical components are

Figure 4.

The 14 steps of CTM.

Figure 5.

The WS–CTM framework.

5

generally geographically dispersed. Generally,
system manufacturers do not share their
demand information to panel manufacturers.
The panel demand is difficult to forecast due to
the information invisibility and the high
demand variation. In such a situation, the
safety level of inventory is high resulting in high
inventory risk and cost. The production plans
of panel manufacturing may change frequently
over time since most of the panel manufacturers mix-up the production with OEM
(Original Equipment Manufacturer), ODM

(Original Design Manufacturer) and OBM
(Own Branding and Manufacturing). Furthermore, the panel is commonly manufactured in
multi-factory which causes the difficulty in
production planning and the increase in transportation distance and cost.
(c) System manufacturers: The business model of
system manufacturers as well mix-up with
OEM, ODM and OBM. Since system manufacturers and panel manufacturers do not have
close partnership, system manufacturers can
not flexibly respond the customer demands
with high fluctuation. To encounter such situations, system manufacturers raise the inventory
level for buffering, and raise the purchasing
price for higher supply priority. The inventory
cost and purchasing cost therefore increase
considerably.


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M.-C. Chen et al.

The materials of panel manufacturers in Taiwan
are supplied by local suppliers and foreign suppliers.
Additionally, the increasing offshore manufacturing of
LCM and system manufacturer rises up the difficulty
of the transportation of large-size panels (ITRI 2006).
After the final products have been assembled by system
manufacturers, they are delivered to channel companies and brand companies which are also geographically dispersedly as shown in Figure 2.
In the TFT–LCD supply chain, from suppliers
through panel manufacturers and system manufacturers to channel companies and brand companies, the
cross-country transportation is required which results

in higher logistics complexity and longer lead time
(refer to Figure 3). The panels can be used in various
applications. For example, 17’’ panels may be delivered to LCD monitor manufacturers, whereas 5’’
panels may be delivered to mobile phone manufacturers. Therefore, the logistics from panel manufacturers to system manufacturers is outsourced to 3PLs
for specialty concern. However, the shipment forecasts
are not shared to 3PLs by TFT–LCD manufacturers
causing frequent LTL (Less Than Truckload) transportation and higher transportation cost.
As mentioned above, it is necessary to effectively
integrate the TFT–LCD manufacturers with 3PLs,
particularly G3PLs, to reduce the transportation cost
and to satisfy the service level. The information such as
order forecast and shipment forecast of panel manufacturers and system manufacturers can be shared to
G3PLs for better transportation planning and more
reliable transportation. CTM proposed by Voluntary

Figure 6.

The global vision of WS–CTM framework.

Inter-industry Commerce Standards (VICS) can be
developed as a platform between manufacturers and
carriers for collaborative transportation. In addition,
Web Services can smoothly enable the development of
cross-enterprise collaboration initiative.
4. Development of WS–CTM
4.1. Collaborative transportation management
Collaborative transportation management (CTM) is
defined by VICS (CTM Sub-Committee of the VICS
Logistics Committee 2004) as ‘a holistic process that
brings together supply chain trading partners and

service providers to drive inefficiencies out of the
transport planning and execution process.’ CTM
mainly aims at improving the interaction and collaboration between three major parties, a shipper (seller), a carrier (3PL), and a receiver (buyer). Either the
shipper or receiver may be the owner of carrier under
CTM. The owner is responsible for hiring and paying
for the transportation service. CTM can be an
extension of CPFR such that CTM extends the
collaboration scope to shippers, receivers and carriers
(3PLs).
As both inbound and outbound transportation
flows are included in the CTM processes, both the
shipper and the receiver can perform some of the
CTM steps, while other steps are performed individually by either the shipper or receiver. The leading
party is responsible for the carrier relationship/
contract and the CTM steps. CTM process consists
of order/shipment forecasting, capacity planning and


International Journal of Computer Integrated Manufacturing
scheduling, order generation, load tender, delivery
execution, and carrier payment. Participating parties
collaborate on transportation by sharing the essential
information of demand and supply about forecasts,
event plans, expected capacity, etc., schemes and
capabilities for enhancing the performance of the
overall transport planning and execution process, and
assets, where feasible (i.e., trucks, warehouses).
CTM can be divided into three phases composed of
14 steps (refer to Figure 4) as follows (Browning and
White 2000):

(a) Strategic phase: This phase defines the strategic
issues of collaboration and includes of the two
steps, Develop Front-end Agreement and
Create Joint Business Plan. The first step
consists of the owner of carrier, which products, locations and types of shipments are

Figure 7.

The process and functions of WS–CTM.

7

included in the collaboration, the exception
management plan, and a summary of key
performance. The second step involves the
aggregate planning phase, in which planned
shipment volume should be matched to equipment asset plans.
(b) Tactical phase: It defines the procedure of
shipment planning beginning with the generation of a product/order forecast, and ending with
the generation of shipment forecast. In the step
of order/shipment forecast, the shipment forecast should be created according the collaborative scenario. The next two steps are to identify
the exceptions for order/shipment forecast and
resolve exception items of order/shipment forecast based on the exception management plan.
(c) Operational phase: This phase defines the
procedure for order execution and fulfilment


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including of the shipment tenders, identification and resolution of exceptions for tenders
forecast, freight contract confirmation, delivery, invoice and managing performance.

CTM extends CPFR to the order execution stage
by firstly translating the order forecasts generated from
CPFR to shipment forecasts. Except sellers and
buyers, carriers join CTM to play the role of order
shipment. From the study in Esper and Williams
(2003), with the help of information technology, CTM
improves the operations and efficiency of all members
joining the collaboration. In 2000, Wal-Mart extended
the CPFR initiative with Procter & Gamble to a partial
CTM by integrating the transportation logistics
company, J.B. Hunt (Dutton 2003). Although this
project is a partial CTM, two of these three partners

Figure 8. The use case diagram of Identifying and
Resolving Delivery Exception.

Figure 9.

obtain noteworthy benefits. For Wal-Mart, the number of steps to process goods for promotions is
reduced. With sooner information exchanging, J.B.
Hunt can take action on information some days earlier
than regular. Therefore, J.B. Hunt reduces the
unloading time by 16%, and empty miles by 3%.
Procter & Gamble has no change in its outcomes from
this CTM project.
4.2.

System analysis

The key objective of CTM is to reduce the uncertainty
in demand, supply and transportation through effective information sharing and collaboration. For
integrating sellers, buyers and G3PLs, a Web Services
based CTM, namely WS–CTM, is developed in this
paper. The proposed WS–CTM can effectively respond
the demand and improve the resource utilisation of
transportation. The WS–CTM platform is designed
according to the process of CTM proposed by VICS
(CTM Sub-Committee of the VICS Logistics Committee 2004) and users’ requirements.
The proposed WS–CTM as shown in Figure 5
integrates the seller’s Enterprise Resource Planning
(ERP) system, buyer’s ERP and carrier’s Logistics
Management System (LMS). Through WS–CTM,
partners can share the necessary information such as
forecast, order, shipping, transportation capacity, etc,
and they can then collaborate on order fulfilment. The
global vision of WS–CTM (refer to Figure 6) with
multi-seller, multi-buyer and multi-carrier can be easily
achieved through the WS architecture. That is, the
trading partners in global supply chain can communicate with each other through WS–CTM platform
by using the internet. The process and functions of

The sequence diagram of Identifying and Resolving Delivery Exception.


International Journal of Computer Integrated Manufacturing

Figure 10.

9

The schema of WS–CTM relational database.

WS–CTM are illustrated in Figure 7. Each function of
WS–CTM is established based on CTM steps. Note
that the steps regarding the exception identification
and resolving are integrated into a single process
because the resolution of exception logically needs to
be continued until no exception exists.

The developed platform mainly includes WS–CTM
management platform, seller side CTM–ERP interface,
buyer side CTM–ERP interface and carrier side LMS.
Taking the step of delivery exception identification and
resolving as an example, the use case diagram
illustrated in Figure 8 displays that the client can


10

Figure 11.

M.-C. Chen et al.

The class diagram of Identifying and Resolving Delivery Exception.

implement the functions of providing tracking information, searching for the delivery exception and
resolving the delivery exception. The sequence diagram

illustrated in Figure 9 describes the process of this step,
and the interaction among WS–CTM platform, buyer
side, seller side and carrier side. Obviously, the related
information in this step is transmitted through WS–
CTM management platform.
For the requirement of information sharing among
seller (panel manufacturer), buyer (system manufacturer) and carrier, the related data of CTM are stored
in the WS–CTM database. The schema of relational

database of WS–CTM is illustrated in Figure 10. The
class diagram of Identifying and Resolving Delivery
Exception is illustrated in Figure 11. Note that owing
to the space limitation, only the related diagrams of
Identifying and Resolving Delivery Exception are
presented herein.
4.3. System development
WS–CTM is developed by Visual Studio. NET 2003
with Windows XP Professional, IIS and SQL Server
2000. The system architecture is illustrated in Figure 12.


International Journal of Computer Integrated Manufacturing
The WS–CTM management platform provides the
collaboration mechanism with Web Services for seller
(panel manufacturer), buyer (system manufacturer)
and carrier (G3PL). The seller side CTM–ERP

Figure 12.

The WS–CTM architecture.

Figure 13.

The WS–CTM management platform.

11

interface and seller side CTM–ERP interface integrate
WS–CTM with seller’s and buyer’s ERP systems. The
carrier side CTM–LMS interface integrates WS–CTM
and carrier’s LMS. The functions of WS–CTM are
described as follows:
(a) Development of Front-End Agreement: The Web
Services in this function provide the services for
Development of Front-End Agreement in
which the collaboration scenarios, forecast
and tender parameters, performance metrics
are jointly set by the collaborative members of
TFT–LCD supply chain.
(b) Creating Joint Business Plan: According to
Front-End Agreement, the items, strategies and
goals for collaborations are set by the Web
Services of Creating Joint Business Plan.
(c) Creating Shipment Forecast: These Web Services provide the services for creating shipment
forecasts.
(d) Shipment Forecast Exception Identification and
Resolving: These Web Services identify the
forecast exceptions and collaboratively resolve
the identified exceptions.
(e) Creating Shipment Tenders: These Web Services provide the services for creating shipment

tenders.
(f) Shipment Tender Exception Identification and
Resolving: These Web Services identify the
shipment tender exceptions and collaboratively
resolve the identified exceptions.


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M.-C. Chen et al.

Figure 14.

Front-End Agreement page in buyer side.

Figure 15.

Collaboration Scenario Settings in WS–CTM platform.

Figure 16.

Performance Settings in WS–CTM platform.


International Journal of Computer Integrated Manufacturing
(g) Freight Contract Confirmation: These Web
Services provide the services for confirming
the freight contracts.
(h) Delivery Exception Identification and Resolving:
These Web Services identify the delivery exceptions and collaboratively resolve the identified

exceptions.

Figure 17.

Collaborative Item Settings in WS–CTM platform.

Figure 18.

Item Strategy Settings in WS–CTM platform.

13

(i) Invoice Exception Identification and Resolving:
These Web Services identify the invoice exceptions and collaboratively resolve the identified
exceptions.
(j) Performance Management: These Web Services
support the performance management for panel
manufacturer, system manufacturer and carrier.


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M.-C. Chen et al.

Figure 19.

Creating Shipment Forecast in seller side.

Figure 20.

Creating Shipment Forecast in carrier side.


International Journal of Computer Integrated Manufacturing

Figure 21.

Shipment Exception Identification and Resolving in buyer side.

Figure 22.

Creating Shipment Tenders in carrier side.

The proposed WS–CTM management platform is
presented in Figure 13. WS–CTM management platform
provides the related CTM WSs for the TFT–LCD panel

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delivery and collects the related information from
involved partners. These data are then stored in the
databases of WS–CTM platform, seller, buyer and


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M.-C. Chen et al.

carrier. Owing to the space limitation, the ERP–CTM
pages of panel manufacturer (seller) and system manufacturer (buyer) sides as well as G3PL’s LMS are omitted.

5. A case
This section presents a case study for describing the
implementation of developed WS–CTM. In this case
study, TFT–LCD system manufacturer plays the role
of buyer, panel manufacturer, seller, and G3PL,
carrier. Note that only some important pages are
illustrated in the following owing to the space
limitation.

(a) Development of Front-End Agreement: In the
beginning, Front-End Agreement among seller,
buyer and carrier is jointly developed to determine collaboration policies such as collaboration scenario, forecast and tendering
parameters, exception criteria, key performance
indicators (KPIs), etc. The three involved
members can use their own Front-End Agreement WSs to get the related information and
perform the related functions (refer to Figure 14
for buyer’s Front-End Agreement page).
In Front-End Agreement, the collaboration
scenario can be set in WS–CTM platform (refer

Figure 23.

Shipment Tender Exception Identification and Resolving in carrier side.

Figure 24.

Freight Contract Confirmation in buyer side.


International Journal of Computer Integrated Manufacturing

to Figure 15), and the involved members can
logon their own system through WSs to get the
related scenario settings. Additionally, the involved members can assess the same KPIs
through Performance Settings WS as shown in
Figure 16.
(b) Creating Joint Business Plan: According to the
settings in Front-End Agreement, system manufacturer, panel manufacturer and G3PL can
jointly create the Joint Business Plan to determine the collaborative items, item strategies, and
so on. Figures 17 and 18 respectively illustrate
the WSs of Collaborative Item Settings and Item
Strategy Settings in WS–CTM platform.
(c) Creating Shipment Forecast: According to the
forecast parameters set in Front-End Agreement, the three involved members can create
the shipment forecast. Figures 19 and 20
illustrate the WSs of Creating Shipment Forecast in seller and G3PL sides, respectively.
(d) Shipment Exception Identification and Resolving: WS–CTM will notify the exceptions if the
exception criteria are met. Next, the three
involved members will try to collaboratively
resolve the forecast exceptions. Figure 21
illustrates the WS of Shipment Exception
Identification and Resolving in buyer side.

Figure 25.

17

(e) Creating Shipment Tenders: Also, according to
the tender parameters set in Front-End Agreement, the three involved members can create
the shipment tenders. Figure 22 illustrates the
WS of Creating Shipment Tenders in G3PL

side.
(f) Shipment Tender Exception Identification and
Resolving: WS–CTM will notify the tender
exceptions if the exception criteria are met.
Next, the three involved members will try to
collaboratively resolve the tender exceptions.
Figure 23 illustrates the WS of Shipment Tender
Exception Identification and Resolving in carrier side with the example of CTMID: CTM.
(g) Freight Contract Confirmation: After resolving
the exceptions, the freight contract will be
generated by the leader side of collaboration,
and be confirmed by the other two sides.
Figure 24 illustrates the WS of Freight Contract
Confirmation in buyer side.
(h) Delivery Exception Identification and Resolving:
After confirming the shipment contract, the
TFT–LCD shipment will be executed accordingly. System manufacturer and panel manufacturer can track the shipment in LMS. Figure 25
illustrates the WS of Delivery Exception Identification and Resolving in carrier side.

Delivery Exception Identification and Resolving in carrier side.


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M.-C. Chen et al.

Figure 26.

Invoice Exception Identification and Resolving in seller side.

Figure 27.

Performance Management in buyer side.

(i) Invoice Exception Identification and Resolving:
Figure 26 illustrates the WS of Invoice Exception Identification and Resolving in seller side.
(j) Performance Management: After the order fulfilment of TFT–LCD, WS–CTM will provide
KPIs for performance management to improve
the CTM projects. Figure 27 illustrates the WS
of Performance Management in buyer side.
6. Conclusions
Under the fierce global competition, enterprises face
the challenges of diverse customer requirements and
speedy delivery. Additionally, the global supply chain

significantly increases the complexity of logistics network and the difficulty of transportation activities.
Excessive lead time, improper control of transportation resources and inaccessibility of cargo tracking
information may lead to ineffective and unreliable
delivery. Collaborative management among shipper,
receiver and carrier is an essential task to deal with the
above issue. The steps and process of Collaborative
Transportation Management proposed by VICS only
provide guidelines for implementation. For seamless
collaboration, enterprises face a challenge of how to
integrate the various heterogeneous information systems. Web Services can integrate the heterogeneous
systems of various cross-enterprise applications. This


International Journal of Computer Integrated Manufacturing
paper develops a WS–CTM platform serving as a

collaboration mechanism among panel manufacturers,
system manufacturers and G3PLs in a TFT–LCD
supply chain.
WS–CTM can extend the collaborative initiatives
between panel manufacturers and system manufacturers to shipping by including G3PLs. The involved
trading partners and G3PLs can collaboratively
execute the order fulfilment by this WS–CTM
platform to increase the accuracy and reliability of
distribution. Through information sharing and transportation collaboration, G3PLs obtain the shipment
information sooner for planning, thus system manufacturers can reliably receive the orders from panel
manufacturers. Nevertheless companies have an
excellent capability in manufacturing, design or
marketing, efficient delivery service can still be a
competitive instrument in dynamic market. The
developed WS–CTM can easily support the intersystem and inter-enterprise distribution collaboration
for achieving efficient delivery. Since WS–CTM is
developed with the technology of WS, it can be a
reference model for other applications and industries. The development of WS–CTM platform only
focuses on the TFT–LCD panel industry, but it
provides the concept of realising CTM for other
industries.
With the continuous application of WS–CTM,
there will be a huge amount of transaction data
collected in databases. These enormous data can be
used to generate more accurate forecasts by using some
advanced technologies such as data mining. Additionally, since CTM focuses on order execution, it can be
further linked to CPFR to establish an integrated
collaborative platform. These further works can be
taken as the potential directions of future study.
Acknowledgement

This work is partially supported by National Science
Council, Taiwan, ROC under grants NSC 95-2221-E-009361-MY3.

References
Andersson, D., 1995. Logistics Alliances and Structural
Change. Tech. Lic. Thesis No. 470. Linkoping
University.
Browning, B. and White, A., 2000. Collaborative Transportation Management- A Proposal. Atlanta: Logility, Inc.
Chen, M., Zhang, D., and Zhou, L., 2007. Empowering
collaborative commerce with Web services enabled
business process management systems. Decision Support
Systems, 43 (2), 530–546.
CTM Sub-Committee of the VICS Logistics Committee,
2004. Collaborative Transportation Management [Online].
White Paper, Version 1.0. Available from: http://www.
idii.com/wp/ctm.pdf [Accessed May 2008].

19

Dhyanesh, N., Vineel, G.C., and Raghavan, S.V., 2003.
DEVISE: a methodology for building Web services based
infrastructure for collaborative enterprises. In: Proceedings of Twelfth IEEE International Workshops on
Enabling Technologies: Infrastructure for Collaborative
Enterprises. WET ICE, pp. 12–17.
Dutton, G., 2003. Collaborative Transportation Management [Online]. World Trade Magazine, February (1).
2003, />issue¼ 60704 [Accessed July 2008].
Esper, T.L. and Williams, L.R., 2003. The value of
Collaborative Transportation Management (CTM): its
relationship to CPFR and information technology.
Transportation Journal, 42 (4), 55–65.

Holweg, M., Disney, S., Holmstro¨m, J., and Sma˚ros, J., 2005.
Supply chain collaboration: making sense of the strategy
continuum. European Management Journal, 23 (2), 170–
181.
Hung, M.H., Cheng, F.T., and Yeh, S.C., 2005. Development
of a web-services-based e-Diagnostics framework for the
semiconductor manufacturing industry. IEEE Transactions on Semiconductor Manufacturing, 18 (1), 122–135.
Industry Technology Research Institute (ITRI), 2002. Annual
Report of Flat Panel Display Industry. Hsinchu, Taiwan.
Industry Technology Research Institute (ITRI), 2006.
Industrial Economics and Knowledge Center (IEK).
, [Accessed February 2006].
Kalogeras, A.P., Gialelis, J.V., Alexakos, C.E., Georgoudakis,
M.J., and Koubias, S.A., 2006. Vertical integration of
enterprise industrial systems utilizing Web Services. IEEE
Transactions on Industrial Informatics, 2 (2), 120–128.
MacCarthy, B. and Atthirawong, W., 2003. Factors Affecting Location Decisions in International Operations – A
Delphi Study. International Journal of Operations and
Production Management, 23 (7), 794–818.
Meixell, M.J. and Gargeya, V.B., 2005. Global supply chain
design: A literature and critique. Transportation Research
Part E: Logistics and Transportation Review, 41 (6), 531–550.
Mentzer, J.T., Foggin, J., and Golicic, S., 2000. Collaboration: the enablers, impediments, and benefits. Supply
Chain Management Review, September/October, 52–58.
Michalakos, S., Anagnostopoulos, A., Depasta, C., and
Pramatari, K., 2005. Using Web-Services to support
collaboration practices along the supply chain. In:
Proceeding of the International Conference on Next
Generation Web Services Practices.
Shen, D., Yu, G., Kou, Y., Nie, T., and Zhao, Z., 2007.

Resolving heterogeneity of Web-service composition in
network manufacturing based on ontology. International
Journal of Computer Integrated Manufacturing, 20 (2),
222–233.
Simatupang, T.M. and Sridharan, R., 2004. Benchmarking
supply chain collaboration: An empirical study. Benchmarking: An International Journal, 11 (5), 484–503.
Tyan, J.C., Wang, F.K., and Du, T.C., 2003. An evaluation
of freight consolidation policies in global third party
logistics. Omega, 31 (1), 55–62.
W3C, 2004. Web Service Architecture Requirement [Online].
Available from: />[Accessed May 2008].
Yang, S.J.H., Lan, B.C.W., and Chung, J.Y., 2005. A
trustworthy Web services framework for business processes integration. In: Proceedings of 10th IEEE
International Workshop on Object-Oriented Real-Time
Dependable Systems. WORDS 2005, pp. 186–193.


International Journal of Computer Integrated Manufacturing
Vol. 23, No. 1, January 2010, 20–39

A hybrid particle swarm optimisation algorithm and fuzzy logic for process planning and production
scheduling integration in holonic manufacturing systems
Fuqing Zhaoa*, Yi Honga, Dongmei Yua, Yahong Yangb and Qiuyu Zhanga
a

School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, Gansu, P.R. China; bCollege of
Civil Engineering, Lanzhou University of Techchnology, Lanzhou 730050, Gansu, P.R. China
(Received 29 January 2009; final version received 25 July 2009)
Modern manufacturing systems have to cope with dynamic changes and uncertainties such as machine breakdown,
hot orders and other kinds of disturbances. Holonic manufacturing systems (HMS) provide a flexible and

decentralised manufacturing environment to accommodate changes dynamically. HMS is based on the notion of
holon, an autonomous, co-operative and intelligent entity which is able to collaborate with other holons to complete
the tasks. HMS requires a robust coordination and collaboration mechanism to allocate available resources to
achieve the production goals.
In this paper, a basic integrated process planning and scheduling system, which is applicable to the holonic
manufacturing systems is presented. A basic architecture of holonic manufacturing system is proposed from the
viewpoint of the process planning and the scheduling systems. Here, the process planning is defined as a process to
select suitable machining sequences of machining features and suitable operation sequences of machining
equipments, taking into consideration the short-term and long-term capacities of machining equipments. A fuzzy
inference system (FIS), in choosing alternative machines for integrated process planning and scheduling of a job
shop in HMS, is presented. Instead of choosing alternative machines randomly, machines are being selected based
on the machine’s capacity. The mean time for failure (MTF) values are input in a fuzzy inference mechanism, which
outputs the machine reliability. The machine is then being penalised based on the fuzzy output. The most reliable
machine will have the higher priority to be chosen. In order to overcome the problem of un-utilisation machines,
sometimes faced by unreliable machine, the hybrid particle swarm optimisation (PSO) with differential evolution
(DE) has been applied to balance the load for all the machines. Simulation studies show that the proposed system
can be used as an effective way of choosing machines in integrated process planning and scheduling.
Keywords: holonic manufacturing systems (HMS); process planning, production scheduling; particle swarm
optimisation; differential evolution (DE)

1.

Introduction

A holonic manufacturing system (HMS)(HMS Consortium) (Van Brussel et al. 1998) is a manufacturing
system where key elements, such as machines, cells,
factories, parts, products, operators, teams, etc., are
modelled as ‘holons’ having autonomous and cooperative properties.
The decentralised information structure, the distributed decision-making authority, the integration of
physical and informational aspects, and the cooperative relationship among holons, make HMS a new

paradigm to meet today’s agile manufacturing challenges (Valckanaers et al. 1997, Giret and Botti 2006).
Manufacturing scheduling is very important because of its direct link to product delivery, inventory
levels, and machine utilisation. Effective scheduling,
however, has been proven to be extremely difficult
because of the combinatorial nature of integer

*Corresponding author. Email:
ISSN 0951-192X print/ISSN 1362-3052 online
Ó 2010 Taylor & Francis
DOI: 10.1080/09511920903207472


optimisation and the large size of practical problems
(Cooke 2004). In practice, material planning systems,
e.g. MRP or MRP II are often used for high-level
production planning and scheduling (Turgay and
Taskin 2007). MRPII system is a hierarchically structured information system which is based on the idea
of controlling all flows of materials and goods by
integrating the plans of sales, finance and operation, in
applying MRPII in practice, one of the main problems
is that there is little help with the necessary aggregation
and disaggregation process, especially when uncertain
demand exists. Because these systems generally ignore
resource capacities, resulting plans or schedules are
usually infeasible. Many heuristic methods have been
developed to dispatch parts at the local (resource or
machine) level based on due dates, criticality of
operations, processing times, and machine utilisation
(Malakooti 2004, Axsater 2007, Monch Lars et al. 2007,

International Journal of Computer Integrated Manufacturing
Pedersen et al. 2007). Artificial intelligence (AI)
approaches have also been proposed based on the
application of scheduling rules (Jawahar et al. 1998,
Masood 2004, Yin Xiao-Feng and Wang Feng-Yu
2004). Schedules obtained by heuristics, however, are
often of questionable quality, and there is no good way
systematically to improve the schedules generated.
The concept of holonic manufacturing has been
studied by IMS-HMS consortium. Similar research
has been performed under the banner of ‘agent-based
manufacturing.’ When applied to manufacturing, an
agent is a software object representing an element in a
manufacturing system such as a product or a machine.
Similar to a holon, an agent may have autonomous
and cooperative properties, and is the building block of
the system.
In practice, scheduling and planning problems are
considered together as manifested in classic combinatorial problems (Wang et al. 2008, Chan et al. 2009,
Shao Xinyu et al. 2009). The practical problems always
involve multiple objectives that need to be addressed
simultaneously. Hence, the actual optimisation objective is to determine the process plan and schedule
concurrently. Owing to the complexity of manufacturing systems, process planning and scheduling are often
carried out sequentially with little communication.
Process planning seldom considers job shop capacity
and scheduling information, such as resource capacity
and availability. Production scheduling, on the other
hand, is performed under fixed parameters without
alternatives which provide alternative production

flows. Re-planning is frequently required by improvisation with a long throughput time and other unexpected
problems. During the last decade, several integration
approaches have been proposed, but most integrated
process planning and scheduling methods focused on
the time aspects of alternative machines when conducting scheduling.
HMS is a holarchy which integrates all procedures
of manufacturing activities from order management
through design, production and marketing to fulfill
the agile manufacturing enterprise. An HMS is
therefore a manufacturing system where key elements,
such as raw materials, machines, products, parts, and
AGVs, have autonomous and cooperative properties
(Deen 2003.).
Currently, HMS consortium partners have developed their own testbeds using their existing software
and hardware environments under the same concepts
and similar system architectures. Most of the early
research results on HMS were reported only internally
in the HMS consortium. However, some results have
been published, (McFarlane and Bussman 2000) give
a review of existing work in holonic manufacturing systems relevant to production planning and

21

control, and provide an analysis of the scope and
applicability for specific application domain. Heragu,
et al. proposed a framework, which models the entities
(e.g., parts) and resources (e.g., material handling
devices, machines, cells, departments) as holonic
structures, and introduces real-time negotiation mechanisms to solve task allocation and planning
problems (Heragu et al. 2002). Leitao, Paulo and

Restivo, Francisco present a holonic approach to
manufacturing scheduling which combines centralised
and distributed strategies to improve responsiveness of
manufacturing systems to emergence (Leitao and
Restivo 2002, Leitao and Restivo 2008). A decentralised holonic approach in manufacturing planning
and control is presented to allocate material
handling operations to the available system resources
(Babiceanu and Chen 2009). Shrestha et al., adopt
genetic algorithm (GA) and dispatching rule (DR) in
an integrated process planning and scheduling system
which is applicable to HMS (Shrestha et al. 2008). Rais
et al., applied the GA and the dynamic programming
(DP) methods to select suitable machining sequences
and sequences of machining equipment in holonic
manufacturing control and planning systems (Rais
et al. 2002). It has become a very active research area
with a large number of publications including several
related books (Deen 2003, Vladimı´ r Marˇ ı´ k 2007,
Vicente and Adriana 2008).
Applications of HMS have been at the interenterprise level on holonic collaborative enterprises,
and mostly at the enterprise and manufacturing system level, and at the manufacturing execution system
(MES) level (Vladimı´ r Marˇ ı´ k et al. 2007, Vicente and
Adriana 2008).
The objective of this paper is to present an
integrated process planning and scheduling system
which aims at realising a flexible production control in
holonic manufacturing systems. This paper deals
mainly with the process planning of product machining
process, taking into consideration the future schedules
of machining equipments. The following issues are

discussed in the paper: (a) basic architecture of target
HMS and process planning systems; (b) formulation of
an objective function based on job time and machining
cost of products; and (c) procedure to select suitable
machining sequences and sequences of machining
equipment for integrating the process planning task
with the scheduling task.
In this paper, a fuzzy logic (FL) is proposed to
decide alternative machines for integrated process
planning and scheduling. The FL is introduced for
the purposes of choosing appropriate machines
based on the machines’ reliability characteristics.
This ensures the capability of the machine in fulfilling
the production demand. In addition, based on the


22

F. Zhao et al.

capability information, the load for each machine
is balanced by using the hybrid particle swarm
optimisation (PSO) with differential evolution (DE).
The remainder of the paper is arranged as follows:
Section 2 describes a holonic architecture for manufacturing systems and common scheduling problems
and challenges. A proposed method to face these
challenges is proposed in Section 3. Analysis results
and discussions are provided in Section 4. Finally, the
conclusions and future researches are given out in
Section 5.

2. A holonic architecture for manufacturing systems
and common scheduling problems
Figure 1 illustrates a holonic architecture that we are
proposing for manufacturing systems with the focus on
the system parts of process planning and production
planning. The figure illustrates components of a
manufacturing system holarchy. In Figure 1, resource
holons (e.g. machines, robots) and task holons
(product orders) are grouped in scheduling holons.
Scheduling holons are grouped with other holons (e.g.
stock management holon, etc) and form production
planning holons. One holon may be part of more than
one holarchy. For example, a resource holon may be
the member of a scheduling holon and of a process
planning holon at the same time. This kind of
architecture provides more flexibilities than static and
traditional computer integrated manufacturing (CIM)
architectures do.

Figure 1.

The holonic architecture.

2.1.

The initial planning holon

In the holonic manufacturing system, each holon
cooperates with other holons and makes use of
external resource to accomplish the task delivered by

the system. So the chains from customer requirement,
through internal production planning holon and
cooperative production task holon to supplier delivered task are established in the system, as shown in
Figure 2.
After analysing the relationship and activity of
each pair of entities, we find that we can model the
relations between each pair of entities as the connection of customers and suppliers. The role of the initial
planning holon is that of matching the task and
resource capacity to accomplish the task that is fulfilled
by the supplier. The decision processes are based on a
supply and demand relationship and the outcomes are
decided by selling and buying activity in respect of
the resource and by market behaviour. As shown in
Figure 2, there are four basic elements in the market
behaviour: supplier, customer, item required and rules
of transaction.
Suppliers are the holders of resource and the
providers of the requirement of the project. The
customer is the consumer of the requirement. Supplier
and customer can be the rational entities of supplier,
manufacturer, subseller, section in manufacturing
enterprise and customer. The project requirement is
the stuff which has value for the customer, including
processed materials, semi-finished articles, final


International Journal of Computer Integrated Manufacturing

Figure 2.

23

Initial planning holon.

product, services, and so on. Transaction rules are
the criteria of transfer of project ownership from
supplier to customer. That is to say, the rules for
transaction and trade for resource capacity are in
different time.
In the initial planning holon, all the relations
between suppliers and customers are dynamic.
Customer orders first enter into the system, according to the item required by customers, and the initial
order details are generated by the order holon.
Product holons generate the detailed information for
the concrete production according to the collaboration information delivered by the order holon, then
the product holons need to select the suppliers
according to the different component combination
to fulfil the customer order. In addition, product
holons simultaneously need to collaborate with
resource holons according to the capacity of
the resource combination. All the processes in the
collaboration are guided by certain rules in the
concrete transaction.
In the application of the system, roles can change.
For example, when one holon provides the resource to
another holon, its role is as supplier. It will, however,
play the customer role when capacity cannot meet the

requirement and it turns for help to another holon. In
the market mechanism all we need to do is to define the

connectivity and activity of the entities in the holonic
manufacturing system. So, when an enterprise holon
lays out its production planning, it can use market
mechanism method based on market equilibrium
theory, and apply it to the modification feature that
matches order/task to resource in the market, and
consequently lay out the appropriate strategy, rule, or
optimisation method to realise the optimum allocation
of resource. The production planning and control
system can respond to the market quickly through the
holonic manufacturing system. The responsiveness can
be seen at several points: 1) when the production task
and resource experience changes, the system can
reconfigure to set a new production planning and
control system. 2) the system can collect, save, fetch
and keep track of the information online. 3) it can
respond quickly when the resource encounters any
problems.
2.2. The detailed planning holon
A scheduling holon includes two kind of holon:
resource holons and task holons, as shown in Figure 3.


24

Figure 3.

F. Zhao et al.

Task and resource holons for scheduling.

The resources are basic components of a manufacturing system (robots, NC machine, conveyors) or
they can be cells made up of basic resources. Each
resource is presented by a holon. The number of
resources does not vary, except when resources are
introduced or removed from the manufacturing
system. A resource holon represents one resource
with status, such as delivered activities and activities to
be carried out. The activity of a resource is represented
in an agenda. The agenda is the sequence of operations
to be carried out and it specifies the expected durations
for these operations as well as the free time intervals of
the resource (Cheng 2004). The activity of a resource
changes according to the operation of the resource
and the dynamic situation of the manufacturing system (e.g. new orders, failures and delays in other
resources).
The function of a task holon is managing the
task system undertaken. It accepts the static programming and overall monitoring from the supplier;
on the other hand, it will feedback the status of task
which is carried on to the supplier. In some cases, if
the activities which are implemented by task holons
are the activities corresponding with input/output
interface, task holons will communicate with the
suppliers by input message/output message. In
addition, task holons will collaborate with other
task holons to propel the finish of the task under the
satisfactions of priority. Furthermore, task holons
will communicate with production holons and
resource holons to instruct the task allocation
according to the capacity constriction of the resources. Last but not least, task holons will monitor

the task progress online and adjust according to the
timely status collected in the system.
The ‘task manager’ interfaces with the user
receiving orders for new tasks for the manufacturing
system. This holon is responsible for launching ‘task
holon’ whenever a new task is ordered. Besides, the
task manager is responsible for dealing with dynamic
changes of task conditions (e.g. when the user
changes the deadline of a task). Task holons

represent the possibilities to execute a plan for a
task into a plan structure (Stahmer 2004, Babiceanu
et al. 2005). The task manager has the knowledge
about the resources that each task may need. Once
launched, they directly negotiate with appropriate
resource holons. The task manager is responsible for
launching task holons, however, it will not launch
task holons immediately after receiving requests from
users. the task manager maintains a priority list of
waiting tasks. The next task holon to be launched is
the one with more priority and that does not conflict
with other tasks that are still negotiating with
resource holons. The possibility of conflict is detected
when a task needs a resource that has received task
announcement messages but has not received the
correspondent acknowledgements or ‘give up’ messages. This means that this resource is still establishing a contract with other previously launched task
holons.
The task holon and initial planning holon
exchange production operation information which
includes the information and method on how to

accomplish certain processes in corresponding resources with constriction of time and cost, i.e. the
process can be fulfilled by the certain resources
combination with the required machining parameters
and quality. The production knowledge, which
includes information and methods on how to utilise
certain resources to produce a certain type production, is communicated between production holon and
task holon. In the process of communication with
production holon and task holon, the production
processes certain resource, the data structure for
expressing production results and evaluation methods
for production planning belong to production knowledge. The machining operation knowledge flows
between production holon and operation holon. The
procedure in the collaboration is monitored by the
on-line supervision holon, which can also make
suggestions for all the holons involved.
In an HMS, holons may form holarchies whose
members collaborate through Cooperation Domains.
Using the mechanism of virtual clustering, holons can
be dynamically involved in different clusters (holarchies) and cooperate through a Cooperation Domain.
The cluster exists for the duration of its cooperation
tasks and disappears when the tasks are completed. A
cooperation domain can be implemented and maintained through the creation of a mediator holon (as
shown in Figure 4).
The process of the operation is as follows.
(1) A new order/task is generated in the market
during the system operation. The order
holon will send a bidding request to a