11,931 research outputs found

    Performance modeling of e-procurement workflow using Generalised Stochastic Petri net (GSPN)

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    This paper proposes a Generalised Stochastic Petri net (GSPN) model representing a generic e-procurement workflow process. The model displays the dynamic behaviour of the system and shows the inter relationship of process activities. An analysis based on matrix equation approach enabled users to analyse the critical system's states, and thus justify the process performance. The results obtained allow users for better decision making in improving e-procurement workflow performance

    Enhancing the Supply Chain Performance by Integrating Simulated and Physical Agents into Organizational Information Systems

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    As the business environment gets more complicated, organizations must be able to respond to the business changes and adjust themselves quickly to gain their competitive advantages. This study proposes an integrated agent system, called SPA, which coordinates simulated and physical agents to provide an efficient way for organizations to meet the challenges in managing supply chains. In the integrated framework, physical agents coordinate with inter-organizations\' physical agents to form workable business processes and detect the variations occurring in the outside world, whereas simulated agents model and analyze the what-if scenarios to support physical agents in making decisions. This study uses a supply chain that produces digital still cameras as an example to demonstrate how the SPA works. In this example, individual information systems of the involved companies equip with the SPA and the entire supply chain is modeled as a hierarchical object oriented Petri nets. The SPA here applies the modified AGNES data clustering technique and the moving average approach to help each firm generalize customers\' past demand patterns and forecast their future demands. The amplitude of forecasting errors caused by bullwhip effects is used as a metric to evaluate the degree that the SPA affects the supply chain performance. The experimental results show that the SPA benefits the entire supply chain by reducing the bullwhip effects and forecasting errors in a dynamic environment.Supply Chain Performance Enhancement; Bullwhip Effects; Simulated Agents; Physical Agents; Dynamic Customer Demand Pattern Discovery

    A framework for smart production-logistics systems based on CPS and industrial IoT

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    Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

    Open semantic service networks

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    Online service marketplaces will soon be part of the economy to scale the provision of specialized multi-party services through automation and standardization. Current research, such as the *-USDL service description language family, is already defining the basic building blocks to model the next generation of business services. Nonetheless, the developments being made do not target to interconnect services via service relationships. Without the concept of relationship, marketplaces will be seen as mere functional silos containing service descriptions. Yet, in real economies, all services are related and connected. Therefore, to address this gap we introduce the concept of open semantic service network (OSSN), concerned with the establishment of rich relationships between services. These networks will provide valuable knowledge on the global service economy, which can be exploited for many socio-economic and scientific purposes such as service network analysis, management, and control

    Towards resilient supply chain networks

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    In the past decade, events like 9/11 terror attacks, the recent financial crisis and other major crisis has proved that there is strong interaction and interdependency of a supply chain network with its external environments in various channels and thus a need to focus on building resiliency (in short, the ability of the system to recover from damage or disruption) of the entire network system. Although literature has discussed some way of improving resiliency of an individual firm which is a member of the network system, it lacked to capture a holistic view of the supply chain network. Pertaining to this observation, this work proposes to improve resiliency of a supply chain network from a system’s perspective rather concentrate on an individual firm. For this purpose, this thesis proposes a conceptual framework to promote early identification and timely information of the disruptions arising in a supply chain network and timely sharing of this information among all the members of the network. The key principle emphasized in this thesis is that recovery from an inevitable disruption has a better possibility if a member of the supply chain network has an early indication or knowledge of the upcoming disruption. A discrete event dynamic system simulation tool called Petri nets is utilized to realize the proposed conceptual framework. Furthermore, the practical benefits and implications of the proposed model and tool are demonstrated with help of two case studies. This thesis has several contributions to the field of operation management and supply chain. First, a new paradigm for supply chain management to avoid large scale failures such as financial crisis is available to the field, which may be applied by governments or regulatory bodies. Second, a new framework which allows for a quantitative analysis of failures of an entire supply chain network is available to the field, which is easy to be used. Third, a novel application of Petri nets to this new problem in supply chain management is available

    Toward a Resilient Holistic Supply Chain Network System: Concept, Review and Future Direction

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    The recent financial crisis and other major crises have suggested that there are some strong interactions and interdependence between several supply chains and their external environments in various ways. A set of supply chains that are interdependent is called a holistic supply chain network (H-SCN) in this paper. There is a need to focus on building the resilience (in short, the ability of a system to recover from damage or disruption) of an entire H-SCN as it is believed that such a network system is strongly relevant to the recent economic recession that is triggered by financial crises. The objectives of this paper are to provide a classification of different SCNs in literature, leading to the identification of a new type of SCN system, i.e., an H-SCN, and to discuss the state of knowledge on the resilience of SCNs, particularly of an H-SCN. A systematic review approach is applied in this paper. Another contribution of this paper is the provision of a more comprehensive definition and description of resilient systems, including SCN systems. A final contribution of this paper is the proposal of the future directions of research on resilient SCN systems, particularly resilient H-SCN systems.postprin
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