J. Serv. Sci. & Management, 2008, 1: 251-254
Published Online December 2008 in SciRes (www.SciRP.org/journal/jssm)
Copyright © 2008 SciRes JSSM
1
Holonic Production System to Obtain Flexibility for
Customer Satisfaction
Gandolfo Dominici
University of Palermo, Faculty of Economy, Italy
Email: gandolfodominici@unipa.it
Received December 3
rd
, 2008; revised December 10
th
, 2008; accepted December 15
th
, 2008.
ABSTRACT
The Holonic Production System (HPS) can be a valid choice to overcome the problems of traditional production sys-
tems’ architectures, thanks to its capability to adapt and react to changes in the business environment whilst being able
to maintain systemic synergies and coordination. The HPS is made of holons seen as functional production units which
are simultaneously autonomous and cooperative. Although the holonic approach could represent a valid solution in
order to pursue the necessary levels of agility of production systems, they have been scarcely implemented in practice
and even less studied from a business studies perspective. The purpose of this discussion paper is to show the benefits of
further research on cases of implementation of HPS from a business organization studies perspective. Very little re-
search on this topic has been done outside the field of business engineering and computer science; the study of this
topic from a different perspective can shed the light on new aspects and new applications of the theory.
Keywords:
holonic production systems, production agility, customer satisfaction
1. Introduction
Mass production showed its effectiveness in stable envi-
ronments and with continuous growth trends
1
until the
end of the 80’s. Since the beginning of the 90’s, it has
begun to show its weaknesses due to the growing insta-
bility of business environments and of systemic complex-
ity. The spread of Internet made it possible for firms the
use of a low cost, worldwide extended, informative infra-
structure which can bring profound changes in the market.
In mature markets it is necessary to supply a wide variety
of products in order to adhere to the need of customers
whose role has changed from “consumer” to “prosumer”
2
.
Theses changes caused the shift from “mass production”
to “mass-customisation”. In order to fulfil these new
needs for agility, it becomes unavoidable for firms to
develop an extremely flexible production structure able to:
a) duly react to the market environment’s turbulences; b)
survive production system changes through the adoption
of new technologies; c) adapt to the uncertainties of pro-
duction systems in such environments.
Neither hierarchical or heterarchical systems are able
to fulfil these requirements [3,4]. Hierarchical systems
have a typically rigid structure which makes it very hard
for them to react to turbulences in an agile way. Heterar-
chical systems are networks of elements with common
aims in which each element shares with the others the
same “horizontal” position of power and authority.
Though heterarchical systems can easily adapt to envi-
ronmental changes and turbulences, their control system
cannot assure the high level of performance and the pre-
dictable organization behaviours needed for the industrial
production of goods.
2. Theoretical Framework
The growing power of IT opened new possibilities in the
worldwide arena and supplied management new and ef-
fective instruments for planning, budgeting, design and
customer care. The central role of the customer thrived to
the point that the supply chain has begun to be defined as
the “demand” chain [5]. Literature on this topic shows
several trends which manufacturing and supply chain
systems have to adapt to [6,7]: a) the paradigm shift from
mass production to semi-personalized production; b) the
opening to collaboration with other agents in order to
speed up production innovation and processes; c) the
critical role of effective and efficient cooperation inside
the network; d) understanding the problems connected to
the implementation of a centralized control system be-
tween different entities with different information, ex-
periences, activities, objectives and decisional authorities.
1
The hierarchical pattern on which mass production is founded pre-
sumes the steadiness of social, economic and technological factors.
2
In 1972 McLuhan & Nevitt [1] in “Take Today” suggested that elec-
tronic technologies would transform consumers into producers. Some
years later, in 1980, the futurologist Alvin Toffler [2] in “The Third
Wave” coined the term “prosumer”, predicting the blurring of the dis-
tinction between producer and consumer due to the saturation of mar-
kets with standardized products which would have pushed towards the
search for higher levels of differentiation and personalization of prod-
ucts.
252 Gandolfo Dominici
Copyright © 2008 SciRes JSSM
These changes call for new organization structures.
Traditional hierarchical systems show several inadequacies
to work in these new business environments: a) they
strongly limit the reconfiguration capacity, the reliability
and the growth capacity of the organization [7]; b) their
complexity grows together with the size of the organiza-
tion [8]; c) communication among the elements of the
system is strictly determined ex ante and vertically lim-
ited [9]; d) the structure’s modules may not take initia-
tives, therefore reducing the system’s readiness to react
thus resulting not agile in turbulent environments envi-
ronment [10]; e) the structure is expensive to build and to
maintain. Heterachical systems do not have the limits of
hierarchical systems, as they are able to obtain flexibility
and adaptability to external stimuli. In heterachical sys-
tems every hierarchy is banned and power is given to the
single “agents”
3
of the system. Agents interact with their
environment and with other agents according to their own
attributes and aims. Control is based on negotiation due
the lack of hierarchy.
In the field of artificial intelligence, the term agent is
used to define the intelligent elements of a system who
observe and act in the environment as entities capable of
awareness and purposive behaviors; such agents must
have the following attributes [11,12]:
- Autonomy - they act without the help or guide of any
superior entity;
- Social ability-they interact with other agents;
- Reactivity-they perceive their environment and respond
rapidly to changes;
- Pro-activity-they are able to have initiative and spe-
cific behaviors for a specific scope.
For example, in a heterachical manufacturing system,
the relation between the work station and supply orders is
such that every supplier has direct contact with the work
station in order to exploit all possible options to face un-
expected fluctuations in supply and/or demand.
In spite of their agility, heterachical systems are not
able to operate following predefined plans, hence their
behavior is hardly predictable, increasing variability in
systemic dynamics. Heterarchical structures work well in
simple, non complex and homogeneous environments
NEGOTIATION
Local AgentLocal Agent
Local Agent
Local Agent
Figure 1. Heterachical control architecture
with abundance of resources [10], while in complex en-
vironments they can bring to instability because of their
unpredictability; moreover, with scarcity of resources,
they are not able to act efficiently due to the lack of plan-
ning.
It is therefore necessary to conceptualize and implement a
system able to assure both performance and reactivity at
the same time. The answer to this challenge could come
from the theories on living organisms and social organi-
zations, which, if applied to the business, present a rep-
resentation of the firm as a living system. The holonic
paradigm emerges in this research stream, amidst the
holistic
4
approach and the vital systemic approach [13].
The holonic paradigm stems from the thoughts of Arthur
Koestler [14] who underlined how complex systems can
originate only if they are composed by stable and
autonomous sub-systems, which are able to survive tur-
bulences and, at the same time, can cooperate forming a
more complex system. Koestler underscores that analyz-
ing both the biological and the physical universe shows
that, it is necessary to take into account the relations be-
tween the whole and the part of the entities we observe.
To understand the abearance of the world, according to
Koestler, is not enough to study atoms, molecules, cells
individuals or systems as independent entities, but it is
crucial to consider such unities as simultaneously part of
a larger whole; in other words, we have to consider it as a
holon. The term holon is a combination of the ancient
Greek “λος with the meaning of “whole” and the suffix
ν” meaning “entity” or part; thus the whole is made of
parts which unlike atoms are also entities. The holon is,
indeed, a whole which includes, simultaneously, the ele-
ments or the subparts which form it and give it structural
and functional meaning. Holons act as intelligent,
autonomous and cooperative entities working together
inside temporary hierarchies called “holarchies”. A
holarchy is a hierarchy of self-regulating holons working,
in coordination with their environment, as autonomous
wholes which are hierarchically superior to their own
parts and, at the same time, are parts dependent by the
control of superior levels. Figure 2 shows the general
relationship between holon and holarchy.
Holons of the same level process elements and infor-
mation coming from lower level holons and they transfer
the results to higher level ones for further processing. Proc-
esses of holons belonging to level ‘n’ hence originate from
Holon level n+1
Holon level nHolon level n
Holon level
n-1 Holon level
n-1 Holon level
n-1
Hlon level
n-1
level of
analysis
component
structures
composite
structure
Figure 2. Holons and holarchies
3
Most of the system architectures based on
agents are heterarchical.
Nevertheless there are also agent based systems which do not adopt
heterarchical control.
4
Holistic scientific paradigm focusing on the study of Complex Adap-
tive Systems (C.A.S.) .
Holonic Production System to Obtain Flexibility for Customer Satisfaction 253
Copyright © 2008 SciRes JSSM
process of ‘n-1’ level subordinated holons and at the
same time are the input for the processes of ‘n+1’ supe-
rior holons. [15,16]. The strength of the holonic approach
resides in the concept of holarchy, which allows the de-
velopment and implementation of extremely complex
systems which are able to use resources efficiently, are
resilient to disturbances and, at the same time, adaptable
to changes of the environment. What makes the holonic
system extremely effective in turbulent environments is
that, inside a holarchy, holons are able to dynamically
create and change hierarchies and also to participate to
different hierarchies simultaneously. The holonic system
can therefore be defined as a global and organized entity
made of interrelations among highly self-regulating op-
erative units which are able to cooperate with each other,
keeping their autonomy, seeking shared results and
common aims. It is possible to find the three pillars of
holonic systems [17]:
1) the shared-value system in the organization allows
the spontaneous and continuous interaction among
groups of people who are far from each other and are not
linked by legal or ownership ties, in order to take advan-
tage of the economies of cooperation and of the increased
stability of the system. Examples of shared value systems
are some of the elements of lean production, that are of-
ten embedded in the company’s vision, such as the prin-
ciple of continuous improvement (kaizen);
2) the distributed network information system which is
the neural sub-system [18] supporting real time supply of
information between operating units which consents the
pursuit of maximum income by better exploiting the
coming business opportunities;
3) the autonomous distributed hierarchy which is
based on the ability of each autonomous part to become
leader according to requirements of specific situations
caused by the turbulent changes in the environment.
Every entity is able to directly interact with other entities
without mediation. Due to this property in a holonic sys-
tem every holon has potentially the same importance and
the same responsibility; the involvement of a holon as
operative unit is based on its knowledge and competen-
cies and is not a consequence of predefined leadership.
3. The Holonic Production System
The Holonic Production System (HPS) can be a valid
choice to overcome the problems of traditional produc-
tion systems’ architectures, thanks to its capability to
adapt and react to changes in the business environment
whilst being able to maintain systemic synergies and co-
ordination. The HPS is made of holons seen as functional
production units which are simultaneously autonomous
and cooperative. These holons can be represented as
networked agents which define different levels of a sys-
tem [19].
Every element represented in Figure 4 is a holon (work
cell, factory, firm, supply chain). At the supply chain
level the interaction among firms, their suppliers and
their clients takes place. It is possible to determine a
subsystem for each firm in the supply chain level, this
subsystem is an enterprise level holon. In the enterprise
there is cooperation among factories and sales depart-
ments. Inside each factory there are several working cells
which interact with each other; the working cell is the
basic level of the holarchy described which is
self-controlled by the interaction among men and ma-
chines [20].
4. Cases of Application of Theory and Further
Possible Developments of Research
Although the holonic approach could represent a valid
solution in order to pursue the necessary levels of agility
of production systems, they have been scarcely imple-
mented in practice and even less studied from a business
studies perspective. Furthermore few studies of imple-
mentation of holonic-like systems can be found in the
literature. Shen [21] noted that IBM has been one of the
first firms to adopt a system based on intelligent agents to
avoid bottlenecks and smooth production. Jennings &
Bussman [22] developed a way to implement a standard
modules system, where each module is flanked by an
Cooperation
Cooperation
Coordination
Coordination
Coordination
Cooperation
Coordination
Coordination
Coordination
Cooperation
Cooperation
Coordinator
Holon
Holon
Holon
Holon Holon
Holon
Figure 3. Architecture of an autonomous distributed system
254 Gandolfo Dominici
Copyright © 2008 SciRes JSSM
Figure 4. Production holarchy and relation among the different holon-levels
intelligent agent in order to compose a holon which becomes
the building block of the system; this system has been tested
by Daimler-Chrysler in order to evaluate its resilience of the
system. The result obtained was of 99,7% of the theoretical
optimum and the system has been adopted in the Factory of
Stuttgart-Untertürkheim in Germany.
The purpose of these notes is to show the benefits of
further research on cases of implementation of HPS from
a business organization studies perspective. Very little
research on this topic has been done outside the field of
business engineering and computer science; the study of
this topic from a different perspective can shed the light
on new aspects and new applications of the theory.
The HPS is surely not easy to implement in a real fac-
tory, nevertheless a step-by-step approach for the intro-
duction of this system in those industries where the need
for flexibility goes together with the scarcity of resources
and margins, can become the way for the factory of the
XXI century.
REFERENCES
[1] M. McLuhan and B. Nevitt, “Take today: The executive
as dropout. B. J. Harcourt, 1972.
[2] A. Toffler, “The third wave,” Bantam, 1980.
[3] D. M. Dilts, N. P. Boyd, and H. H. Whorms, “The evolution
of control architectures for automated manufacturing sys-
tems," Journal of Manufacturing Systems 10(1), pp. 79-93,
1991.
[4] T. J. Crowe and E. J. Stahlman, “A proposed structure for
distributed shopfloor control,” Integrated Manufacturing
Systems 6 (6), pp. 31-36, 1995.
[5] R. Blackwell and K. D. Blackwell, “The century of the
consumer: Converting supply chains into demand chains,”
Supply Chain Management Review, pp. 22-32, 1999.
[6] F. Frederix, “From production to a product perspective,”
New Industrial Scenario, In Yoon S. et all. Evolution of
Supply Chain Management, Symbiosis of Adaptive Value
Networks and ICT, Kluwer Academic Publishers, Nor-
well, 2004.
[7] L. Gou, P. B. Luh, and Y. Kyoya, “Holonic manufactur-
ing scheduling: Architecture, cooperation mechanism, and
implementation,” Computers in Industry, 37 (3), pp.
213-231, 1998.
[8] J. Hatvany, “Intelligence and cooperation in heterarchic
manufacturing systems,” Robotics & Computer-Integrated
Manufacturing, 2 (2), pp. 101-104, 1985.
[9] H. V. Brussel, L. Bongaerts, J. Wyns, P. Valckenaers, and
T. V. Ginderachter, “A conceptual framework for Holonic
manufacturing: Identification of manufacturing holons,”
Journal of Manufacturing Systems, 18 (1), pp. 35-52, 1999.
[10] P. Valckenaers, E. Bonneville, H. V. Brussel, L. Bon-
gaerts, and J. Wyns, “Results of the holonic control sys-
tem benchmark at the kuleven,” Proceedings of CIMAT,
pp. 128-133, 1994.
[11] T. Moyaux, B. Chaib-draa, and S. D’Amours, “Supply
chain management and multiagent systems: An over-
view,” In B. Chaib-draa, J. P. Müller (editor), Multiagent
based Supply Chain Management. Springer, 2006.
[12] M. Paoloucci and R. Sacile, “Agent-based manufacturing
and control systems,” CRC Press, 2005.
[13] G. M. Golinelli, L’approccio sistemico al governo dell’
impresa-L’impresa sistema vitale Vol. 1. CEDAM, Italy,
2000.
[14] A. Koestler, “The ghost in the machine,” Arkana, 1967.
[15] M. Mesarovic, D. Macko, and Y. Takahara, “Theory of
hierarchical, multi-level systems,” Academic Press, 1970.
[16] P. Mella, “La Rivoluzione Olonica: Oloni, olarchie e reti
oloniche,” Il fantasma del kosmos produttivo, FrancoAngeli,
Italy, 2005.
[17] C. Saccani, “Il Sistema Olonico,” Sistemi&Impresa, 2, pp.
29-45,1996.
[18] M. A. Arbib, “The handbook of brain theory and neural
networks,” MIT Press, Boston, 1995.
[19] M. Ulieru and M. Cobzaru, “Building holonic supply
chain management systems: An e-logistics application for
the telephone manufacturing industry, IEEE Transactions
on Industrial Informatics 1 (1), pp. 18-30, 2005.
[20] G. Dominici, “Il contesto istituzionale nipponico e l’evoluzione
della “lean production,” Aracne, Roma, Italy, 2007.
[21] W. Shen, “Distributed manufacturing scheduling using
intelligent agents,” IEEE Intelligent Systems, pp. 88, 2002.
[22] N. R. Jennings and S. Bussmann, “Agent-based control
systems,” Why are they suited to engineering complex
systems?. IEEE Control Systems Magazine, 61, 2003.