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A Framework for Statechart Based Component Reconfiguration
2008
Fifth IEEE Workshop on Engineering of Autonomic and Autonomous Systems (ease 2008)
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In addition to supporting a Model Driven development style, the framework creates a reflective architecture of the component without any involvement from the developer. ...
The latter can also be considered as a support for coping with incomplete or bad specifications due to the lack of exact knowledge of the environment. ...
First of all, following the same philosophy of [5] , it permits a Model Driven style of development. To illustrate this, consider the statechart of Figure 1 . ...
doi:10.1109/ease.2008.11
fatcat:nz7quztpzffptiddmgfsejyede
Reconfigurable Knowledge-based Control Solutions for Responsive Manufacturing Systems
2011
Studies in Informatics and Control
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In such a context, the present paper describes an automation solution based on a modular distributed approach for agile factories integration and reconfiguration, integrating a knowledge based cooperation ...
policy providing self-adaptation to endogenous as well as exogenous events. ...
Such paradigm is oriented to the adoption of machine interpretable information supporting the implementation of intelligent control solutions based on formal knowledge models. ...
doi:10.24846/v20i1y201103
fatcat:d3fmmq3shrcvvhtdgzvgpstb5i
Now That's Smart!
2007
IEEE Industrial Electronics Magazine
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We describe an experiment conducted on a laboratory model of an intelligent manufacturing system with the goal of achieving the PnP configurability and reconfiguration by employing IEC 61499 control. ...
The key enablers of the flexibility in this new standard are: the encapsulation of knowledge into function blocks, the application model as a network of function blocks, the device model providing the ...
doi:10.1109/mie.2007.909540
fatcat:eveyib6ovjdgrmh3ixd4ukezoy
Exploiting Queuing Networks to Model and Assess the Performance of Self-Adaptive Software Systems: A Survey
2020
Procedia Computer Science
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of clarifying the state-of-art in exploiting such a notation to model and assess performance of Self-Adaptive Software Systems. ...
of clarifying the state-of-art in exploiting such a notation to model and assess performance of Self-Adaptive Software Systems. ...
the three systematic studies in the knowledge base, i.e ...
doi:10.1016/j.procs.2020.03.108
fatcat:onohipnsefctdmkagdvxmpyxrq
The challenges, approaches, and used techniques of CPS for manufacturing in Industry 4.0: a literature review
2021
The International Journal of Advanced Manufacturing Technology
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AbstractThis work aims to review literature related to the latest cyber-physical systems (CPS) for manufacturing in the revolutionary Industry 4.0 for a comprehensive understanding of the challenges, approaches ...
Although the key technologies of Industry 4.0 are the CPS, Internet of Things (IoT), and Internet of Services (IoS), the human component (HC), cyber component (CC), physical component (PC), and their HC-CC ...
The first draft of the manuscript was written by the three authors and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. ...
doi:10.1007/s00170-020-06572-4
fatcat:2qo42mk4mjhcricvb6bpy7jizi
Agent and Cyber-Physical System Based Self-Organizing and Self-Adaptive Intelligent Shopfloor
2017
IEEE Transactions on Industrial Informatics
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The task-driven self-organizing model for manufacturing systems is analyzed in Section V, and the real-time information-driven self-adaptive manufacturing model is described in Section VI. ...
Smart Machine Agent (SMA) based on CPS. ...
The Logical Flow of the Self-organizing Model Fig. 4 . Task-driven Self-organizing Model Fig. 4 illustrates the framework of the task-driven selforganizing manufacturing model. ...
doi:10.1109/tii.2016.2618892
fatcat:a4u7n5g64bfuxdgahp3bpcw7lq
Agent-Based, Distributed Diagnosis for Shipboard Systems
[chapter]
2002
Knowledge and Technology Integration in Production and Services
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We describe the agent-based, distributed diagnostic aspects of a distributed control architecture that integrates multiple ship systems and provides resource-and diagnostic-driven reconfiguration at multiple ...
We embed system-and subsystem models in distributed, agent-based components to provide distributed diagnostics. We demonstrate this architecture using a shipboard chilled water system application. ...
A model not only captures an expert's knowledge, but is a rigorous description of how a system works based on first principles. ...
doi:10.1007/978-0-387-35613-6_31
fatcat:k7x7jscsvzag5mo6jyoogy3mwi
A Framework for Constructing Adaptive and Reconfigurable Systems
2008
IEEE Transactions on Nuclear Science
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In this approach, based on the control loop paradigm commonly used in industrial control, self-adaptation is decomposed into observing system events, inferring necessary changes based on a system's functional ...
This paper presents a software approach to augmenting existing real-time systems with self-adaptation capabilities. ...
The framework includes an inference module based on Jess, a sophisticated knowledge engine developed at Sandia Lab [11] , an event-driven FSM module to represent the system as a state machine, and a multithreaded ...
doi:10.1109/tns.2007.913488
fatcat:jkmsqxiiqbcf5msvg36vm5cd4i
A framework for constructing adaptive and reconfigurable systems
2007
2007 15th IEEE-NPSS Real-Time Conference
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In this approach, based on the control loop paradigm commonly used in industrial control, self-adaptation is decomposed into observing system events, inferring necessary changes based on a system's functional ...
This paper presents a software approach to augmenting existing real-time systems with self-adaptation capabilities. ...
The framework includes an inference module based on Jess, a sophisticated knowledge engine developed at Sandia Lab [11] , an event-driven FSM module to represent the system as a state machine, and a multithreaded ...
doi:10.1109/rtc.2007.4382751
fatcat:cyv6jy4lz5e3lgohecvznoraom
Integrating Semantic Run-Time Modelsfor Adaptive Software Systems
2019
Journal of Web Engineering
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An architecture-based approach to self-adaptation was first developed in [5] , exploiting architectural models to represent complex systems in terms of components, relations, and properties. ...
More recently, the emerging field of Model Driven Engineering (MDE) [8] called Models@Run.time [4] extended this approach, investigating the use of different models to represent the knowledge required ...
Another example is FRAMESELF [34] , an ontology-based framework designed for the self-configuration of Machine-to-machine (M2M) architectures and communications. ...
doi:10.13052/jwe1540-9589.18131
fatcat:hz3ox762ojfwrkpnxhxnmt6up4
Information Modeling and Knowledge Management Approach to Reconfiguring Manufacturing Enterprises
2011
International Journal of Advanced Information Technology
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A methodology is developed to facilitate Ford Company to quickly model and re-configure new/changed assembly line for building new/changed engine. ...
The focus remained on the real industrial challenge of rapid constraint evaluation for designing and/or reconfiguration of Powertrain assembly lines to cater for a new/changed product. ...
ACKNOWLEDGEMENTS The authors gratefully acknowledge the support of UK EPSRC and Loughborough University's IMCRC through Business Driven Automation (BDA) project. ...
doi:10.5121/ijait.2011.1301
fatcat:obo5ldntpbcplbuy4jkmh65kbu
Usability of Multi-agent Based Control Systems in Industrial Automation
[chapter]
2009
Lecture Notes in Computer Science
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of user acceptance and understanding of such highly intelligent reconfigurable systems. ...
The design and development of both the architecture for simplifying of development of such systems and the advanced diagnostic, monitoring, and humaninteraction system will provide an easy maintenance ...
In order to increase the machine utilization, the agent-based control system was developed for dynamic selection and configuration of production resources. ...
doi:10.1007/978-3-642-03668-2_3
fatcat:iw2hdreq4fe4nlhmmz4xcgvnn4
Artificial Intelligence-Based Decision-Making Algorithms, Internet of Things Sensing Networks, and Deep Learning-Assisted Smart Process Management in Cyber-Physical Production Systems
2021
Electronics
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processes", and "sustainable Internet of Things-based manufacturing systems". ...
Subsequent analyses should develop on real-time sensor networks, so as to configure the importance of artificial intelligence-driven big data analytics by use of cyber-physical production networks. ...
Self-adaptive reconfigurable manufacturing systems are crucial in the operational modeling design, where the processes have to be assimilated into the system monitoring behavior. ...
doi:10.3390/electronics10202497
fatcat:rryhw72fhvalloix23qkxwh4ca
Improved Resilience Controllers Using Cognitive Patterns
2014
IFAC Proceedings Volumes
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A reference architecture for self-aware autonomous systems is synthesised from these patterns and demonstrated in the control of an autonomous mobile robot. ...
The term "autonomous" gains a deeper significance in this context of reflective, pattern based controllers. ...
This Functional Metamodel has to be machine readable to be usable by a model-based controller. ...
doi:10.3182/20140824-6-za-1003.02433
fatcat:ywjjkx5bzfbz5per62d5eakpk4
CAMeL: A Self-Adaptive Framework for Enriching Context-Aware Middlewares with Machine Learning Capabilities
2019
Mobile Information Systems
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The framework is focused on acquiring contextual information from sensors providing loosely structured data without the need for developers of implementing dedicated application code or making use of external ...
We show with experiments and case studies how the CAMeL framework can (i) promote code reuse and reduce the complexity of context-aware applications by natively supporting machine learning capabilities ...
Although the model is event-driven and based on finite-state machines, adaptation is provided for a given scene and not for an event. ese state machines are predefined and cannot be customised dynamically ...
doi:10.1155/2019/1209850
fatcat:w66pp2fjardi5oflte5n3d7tvm
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