Supply-chain networks: a complex adaptive systems perspective
15 Oct 2005-International Journal of Production Research (Taylor & Francis Group)-Vol. 43, Iss: 20, pp 4235-4265
TL;DR: In this paper, the authors look at the impact of information technology and complexity in the context of supply-chain networks, and the challenges that arise from the lack of principles that govern how supply chains with complex organizational structure and function arise and develop, and what organizations and functionality are attainable, given specific kinds of lower-level constituent entities.
Abstract: In this era, information technology is revolutionizing almost every domain of technology and society, whereas the ‘complexity revolution’ is occurring in science at a silent pace. In this paper, we look at the impact of the two, in the context of supply-chain networks. With the advent of information technology, supply chains have acquired a complexity almost equivalent to that of biological systems. However, one of the major challenges that we are facing in supply-chain management is the deployment of coordination strategies that lead to adaptive, flexible and coherent collective behaviour in supply chains. The main hurdle has been the lack of the principles that govern how supply chains with complex organizational structure and function arise and develop, and what organizations and functionality are attainable, given specific kinds of lower-level constituent entities. The study of Complex Adaptive Systems (CAS), has been a research effort attempting to find common characteristics and/or formal distinctio...
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TL;DR: Some of the major results in random graphs and some of the more challenging open problems are reviewed, including those related to the WWW.
Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.
7,116 citations
Hungarian Academy of Sciences1, Budapest University of Technology and Economics2, University of Stuttgart3, Fraunhofer Institute for Manufacturing Engineering and Automation4, National Institute of Advanced Industrial Science and Technology5, Pennsylvania State University6, Technische Universität München7, Fraunhofer Society8, RWTH Aachen University9, University of Tokyo10
TL;DR: There are significant roots in general and in particular to the CIRP community – which point towards CPPS, and expectations towards research in and implementation of CPS and CPPS are outlined.
Abstract: One of the most significant advances in the development of computer science, information and communication technologies is represented by the cyber-physical systems (CPS). They are systems of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using, at the same time, data-accessing and data-processing services available on the Internet. Cyber-physical production systems (CPPS), relying on the latest, and the foreseeable further developments of computer science, information and communication technologies on one hand, and of manufacturing science and technology, on the other, may lead to the 4th industrial revolution, frequently noted as Industrie 4.0. The paper underlines that there are significant roots in general – and in particular to the CIRP community – which point towards CPPS. Expectations towards research in and implementation of CPS and CPPS are outlined and some case studies are introduced. Related new R&D challenges are highlighted.
1,123 citations
TL;DR: An intertwined supply network (ISN) is an entirety of interconnected supply chains (SC) which, in their integrity secure the provision of society and markets with goods and services.
Abstract: An intertwined supply network (ISN) is an entirety of interconnected supply chains (SC) which, in their integrity secure the provision of society and markets with goods and services. The ISNs are o...
863 citations
Cites background from "Supply-chain networks: a complex ad..."
...systems (Choi, Dooley, and Rungtusanatham 2001; Surana et al. 2005) and SC structural dynamics (Ivanov, Sokolov, and Kaeschel 2010)....
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...Other relevant research streams can be found in the theories of complex adaptive systems (Choi, Dooley, and Rungtusanatham 2001; Surana et al. 2005) and SC structural dynamics (Ivanov, Sokolov, and Kaeschel 2010)....
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TL;DR: The evolution of agent technologies and manufacturing will probably proceed hand in hand and the former can receive real challenges from the latter, which will have more and more benefits in applying agent technologies, presumably together with well-established or emerging approaches of other disciplines.
Abstract: The emerging paradigm of agent-based computation has revolutionized the building of intelligent and decentralized systems. The new technologies met well the requirements in all domains of manufacturing where problems of uncertainty and temporal dynamics, information sharing and distributed operation, or coordination and cooperation of autonomous entities had to be tackled. In the paper software agents and multi-agent systems are introduced and through a comprehensive survey, their potential manufacturing applications are outlined. Special emphasis is laid on methodological issues and deployed industrial systems. After discussing open issues and strategic research directions, we conclude that the evolution of agent technologies and manufacturing will probably proceed hand in hand. The former can receive real challenges from the latter, which, in turn, will have more and more benefits in applying agent technologies, presumably together with well-established or emerging approaches of other disciplines.
668 citations
TL;DR: A model of supply chain complexity is put forth and empirically tests it using plant-level data from 209 plants across seven countries and shows that upstream complexity, internal manufacturing complexity, and downstream complexity all have a negative impact on manufacturing plant performance.
659 citations
Cites background from "Supply-chain networks: a complex ad..."
...More recently, Surana et al. (2005) and Pathak et al. (2007) have extended the theory-building work that applies complex adaptive system (CAS) concepts to SCM, the former by suggesting analytical frameworks for applying CAS principles in studying the management and performance improvement of supply…...
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References
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TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Abstract: Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
39,297 citations
"Supply-chain networks: a complex ad..." refers background in this paper
...In order to describe the transition from a regular network to a random network, Watts and Strogatz introduced the so-called small-world graphs as models of social networks (Watts and Strogatz 1998) and (Newman 2000)....
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...Because of the high degree of clustering, the models of dynamical systems with small-world coupling display an enhanced signal-propagation speed, rapid disease propagation, and synchronizability (Watts and Strogatz 1998, Newman 2002)....
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TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
Abstract: The emergence of order in natural systems is a constant source of inspiration for both physical and biological sciences. While the spatial order characterizing for example the crystals has been the basis of many advances in contemporary physics, most complex systems in nature do not offer such high degree of order. Many of these systems form complex networks whose nodes are the elements of the system and edges represent the interactions between them.
Traditionally complex networks have been described by the random graph theory founded in 1959 by Paul Erdohs and Alfred Renyi. One of the defining features of random graphs is that they are statistically homogeneous, and their degree distribution (characterizing the spread in the number of edges starting from a node) is a Poisson distribution. In contrast, recent empirical studies, including the work of our group, indicate that the topology of real networks is much richer than that of random graphs. In particular, the degree distribution of real networks is a power-law, indicating a heterogeneous topology in which the majority of the nodes have a small degree, but there is a significant fraction of highly connected nodes that play an important role in the connectivity of the network.
The scale-free topology of real networks has very important consequences on their functioning. For example, we have discovered that scale-free networks are extremely resilient to the random disruption of their nodes. On the other hand, the selective removal of the nodes with highest degree induces a rapid breakdown of the network to isolated subparts that cannot communicate with each other.
The non-trivial scaling of the degree distribution of real networks is also an indication of their assembly and evolution. Indeed, our modeling studies have shown us that there are general principles governing the evolution of networks. Most networks start from a small seed and grow by the addition of new nodes which attach to the nodes already in the system. This process obeys preferential attachment: the new nodes are more likely to connect to nodes with already high degree. We have proposed a simple model based on these two principles wich was able to reproduce the power-law degree distribution of real networks. Perhaps even more importantly, this model paved the way to a new paradigm of network modeling, trying to capture the evolution of networks, not just their static topology.
18,415 citations
01 Jan 1981
9,756 citations
"Supply-chain networks: a complex ad..." refers background in this paper
...The basis for this is Taken’s Embedding theorem (Takens 1981)....
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TL;DR: It is found that scale-free networks, which include the World-Wide Web, the Internet, social networks and cells, display an unexpected degree of robustness, the ability of their nodes to communicate being unaffected even by unrealistically high failure rates.
Abstract: Many complex systems display a surprising degree of tolerance against errors. For example, relatively simple organisms grow, persist and reproduce despite drastic pharmaceutical or environmental interventions, an error tolerance attributed to the robustness of the underlying metabolic network1. Complex communication networks2 display a surprising degree of robustness: although key components regularly malfunction, local failures rarely lead to the loss of the global information-carrying ability of the network. The stability of these and other complex systems is often attributed to the redundant wiring of the functional web defined by the systems' components. Here we demonstrate that error tolerance is not shared by all redundant systems: it is displayed only by a class of inhomogeneously wired networks, called scale-free networks, which include the World-Wide Web3,4,5, the Internet6, social networks7 and cells8. We find that such networks display an unexpected degree of robustness, the ability of their nodes to communicate being unaffected even by unrealistically high failure rates. However, error tolerance comes at a high price in that these networks are extremely vulnerable to attacks (that is, to the selection and removal of a few nodes that play a vital role in maintaining the network's connectivity). Such error tolerance and attack vulnerability are generic properties of communication networks.
7,697 citations
"Supply-chain networks: a complex ad..." refers background in this paper
...…of large-scale and complex networks, including the WWW, Internet, and metabolic networks, satisfy the power law PðkÞ k , where P(k) is the probability that a node in the network is connected to k other nodes, and is a positive real number (Albert et al. 2000a Barabasi et al. 2000, Barabasi 2001)....
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