An agent-based dynamic information network for supply chain management

One of the main research issues in supply chain management is to improve the global efficiency of supply chains. However, the improvement efforts often fail because supply chains are complex, are subject to frequent changes, and collaboration and information sharing in the supply chains are often infeasible. This paper presents a practical collaboration framework for supply chain management wherein multi-agent systems form dynamic information networks and coordinate their production and order planning according to synchronized estimation of market demands. In the framework, agents employ an iterative relaxation contract net protocol to find the most desirable suppliers by using data envelopment analysis. Furthermore, the chain of buyers and suppliers, from the end markets to raw material suppliers, form dynamic information networks for synchronized planning. This paper presents an agent-based dynamic information network for supply chain management and discusses the associated pros and cons

Influence of the ratio on the mechanical properties of epoxy resin composite with diapers waste as fillers for partition panel application

Materials play significant role in the domestic economy and defense with the fast growth of science and technology field. New materials are the core of fresh technologies and the three pillars of modern science and technology are materials science, power technology and data science. The prior properties of the partition panel by using recycled diapers waste depend on the origin of waste deposits and its chemical constituents. This study presents the influence of the ratio on the mechanical properties of polymer in diapers waste reinforced with binder matrix for partition panel application. The aim of this study was to investigate the influence of different ratio of diapers waste polymer reinforced epoxy-matrix with regards to mechanical properties and morphology analysis. The polymer includes polypropylene, polystyrene, polyethylene and superabsorbent polymer (SAP) were used as reinforcing material. The tensile and bending resistance for ratio of 0.4 diapers waste polymers indicated the optimum ratio for fabricating the partition panel. Samples with 0.4 ratios of diapers waste polymers have highest stiffness of elasticity reading with 76.06 MPa. A correlation between the micro structural analysis using scanning electron microscope (SEM) and the mechanical properties of the material has been discussed

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

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

Workshop on Modelling of Objects, Components, and Agents, Aarhus, Denmark, August 27-28, 2001

This booklet contains the proceedings of the workshop Modelling of Objects, Components, and Agents (MOCA'01), August 27-28, 2001. The workshop is organised by the CPN group at the Department of Computer Science, University of Aarhus, Denmark and the "Theoretical Foundations of Computer Science" Group at the University of Hamburg, Germany. The papers are also available in electronic form via the web pages: http://www.daimi.au.dk/CPnets/workshop01

Ontology-Based Production Simulation with OntologySim

Imagine the possibility to save a simulation at any time, modify or analyze it, and restart again with exactly the same state. The conceptualization and its concrete manifestation in the implementation OntologySim is demonstrated in this paper. The presented approach of a fully ontology-based simulation can solve current challenges in modeling and simulation in production science. Due to the individualization and customization of products and the resulting increase in complexity of production, a need for flexibly adaptable simulations arises. This need is exemplified in the trend towards Digital Twins and Digital Shadows. Their application to production systems, against the background of an ever increasing speed of change in such systems, is arduous. Moreover, missing understandability and human interpretability of current approaches hinders successful, goal oriented applications. The OntologySim can help solving this challenge by providing the ability to generate truly cyber physical systems, both interlocked with reality and providing a simulation framework. In a nutshell, this paper presents a discrete-event-based open-source simulation using multi-agency and ontology

SCS: 60 years and counting! A time to reflect on the Society's scholarly contribution to M&S from the turn of the millennium.

The Society for Modeling and Simulation International (SCS) is celebrating its 60th anniversary this year. Since its inception, the Society has widely disseminated the advancements in the field of modeling and simulation (M&S) through its peer-reviewed journals. In this paper we profile research that has been published in the journal SIMULATION: Transactions of the Society for Modeling and Simulation International from the turn of the millennium to 2010; the objective is to acknowledge the contribution of the authors and their seminal research papers, their respective universities/departments and the geographical diversity of the authors' affiliations. Yet another objective is to contribute towards the understanding of the overall evolution of the discipline of M&S; this is achieved through the classification of M&S techniques and its frequency of use, analysis of the sectors that have seen the predomination application of M&S and the context of its application. It is expected that this paper will lead to further appreciation of the contribution of the Society in influencing the growth of M&S as a discipline and, indeed, in steering its future direction

Distributed Load Testing by Modeling and Simulating User Behavior

Modern human-machine systems such as microservices rely upon agile engineering practices which require changes to be tested and released more frequently than classically engineered systems. A critical step in the testing of such systems is the generation of realistic workloads or load testing. Generated workload emulates the expected behaviors of users and machines within a system under test in order to find potentially unknown failure states. Typical testing tools rely on static testing artifacts to generate realistic workload conditions. Such artifacts can be cumbersome and costly to maintain; however, even model-based alternatives can prevent adaptation to changes in a system or its usage. Lack of adaptation can prevent the integration of load testing into system quality assurance, leading to an incomplete evaluation of system quality. The goal of this research is to improve the state of software engineering by addressing open challenges in load testing of human-machine systems with a novel process that a) models and classifies user behavior from streaming and aggregated log data, b) adapts to changes in system and user behavior, and c) generates distributed workload by realistically simulating user behavior. This research contributes a Learning, Online, Distributed Engine for Simulation and Testing based on the Operational Norms of Entities within a system (LODESTONE): a novel process to distributed load testing by modeling and simulating user behavior. We specify LODESTONE within the context of a human-machine system to illustrate distributed adaptation and execution in load testing processes. LODESTONE uses log data to generate and update user behavior models, cluster them into similar behavior profiles, and instantiate distributed workload on software systems. We analyze user behavioral data having differing characteristics to replicate human-machine interactions in a modern microservice environment. We discuss tools, algorithms, software design, and implementation in two different computational environments: client-server and cloud-based microservices. We illustrate the advantages of LODESTONE through a qualitative comparison of key feature parameters and experimentation based on shared data and models. LODESTONE continuously adapts to changes in the system to be tested which allows for the integration of load testing into the quality assurance process for cloud-based microservices

Engineering framework for service-oriented automation systems

Tese de doutoramento. Engenharia Informática. Universidade do Porto. Faculdade de Engenharia. 201

Towards resilient supply chain networks

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