Automation platform independent multi-agent system for robust networks of production resources in industry 4.0

AbstractThe Cyber-Physical Production System (CPPS) is a concept derived from software (cyber) and hardware (physical) applications and is based on global information exchange between such systems. The CPPS is known as a trend of Industry 4.0 (I4.0) focusing on flexibility regarding new products and adaptability to new requirements. This paper focuses on two I4.0 scenarios described by the Platform Industrie 4.0 that describe challenges for the industry towards its digital future. First, it looks at the Order Controlled Production (OCP) scenario that deals with flexible and self-configuring production networks. It describes the dynamic organization of production resources required to execute a production order. Second, the Adaptable Factory (AF) application scenario is discussed, which focuses on the configuration of production resources and describes the adaptability of an individual facility through (physical) modification. This paper first provides a detailed analysis of the requirements from these scenarios. Furthermore, it analyses the current Multi-Agent System (MAS) architectures and agent-based planning and decision support systems requirements. MAS can be used to create application-independent I4.0 systems with arbitrary hardware automation platforms. To create a scalable communication network that also supports application independence and enables the semantically machine-readable description of the exchanged data, the OPC UA standard was adopted. As a result of the study, the concept shows how different and independent automation platforms can be seamlessly connected via OPC UA. The proposed MAS concept has been evaluated in different use cases, namely OCP and AF.

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Towards a multi-agent system for regulated information exchange in crime investigations

Artificial Intelligence and Law ◽

10.1007/s10506-006-9005-1 ◽

2005 ◽

Vol 13 (1) ◽

pp. 133-151 ◽

Cited By ~ 3

Author(s):

Pieter Dijkstra ◽

Floris Bex ◽

Henry Prakken ◽

Kees de Vey Mestdagh

Keyword(s):

Information Exchange ◽

Multi Agent System ◽

Agent System ◽

Multi Agent

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Digital Twins: Review and Challenges

Journal of Computing and Information Science in Engineering ◽

10.1115/1.4050244 ◽

2021 ◽

Vol 21 (3) ◽

Author(s):

Maria G. Juarez ◽

Vicente J. Botti ◽

Adriana S. Giret

Keyword(s):

Computer Science ◽

Industry 4.0 ◽

Multi Agent System ◽

Agent System ◽

Digital Twin ◽

Digital Twins ◽

Science Approach ◽

Multi Agent ◽

Current Operating

Abstract With the arises of Industry 4.0, numerous concepts have emerged; one of the main concepts is the digital twin (DT). DT is being widely used nowadays, however, as there are several uses in the existing literature; the understanding of the concept and its functioning can be diffuse. The main goal of this paper is to provide a review of the existing literature to clarify the concept, operation, and main characteristics of DT, to introduce the most current operating, communication, and usage trends related to this technology, and to present the performance of the synergy between DT and multi-agent system (MAS) technologies through a computer science approach.

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A Multi-Agent System for Adaptive Production Networks

Lecture Notes in Computer Science - Multi-Agent-Based Simulation X ◽

10.1007/978-3-642-13553-8_5 ◽

2010 ◽

pp. 49-60 ◽

Cited By ~ 2

Author(s):

Samir Hamichi ◽

David Brée ◽

Zahia Guessoum ◽

Diana Mangalagiu

Keyword(s):

Multi Agent System ◽

Production Networks ◽

Agent System ◽

Multi Agent

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MASPI: A Multi Agent System for Prediction in Industry 4.0 Environment

Advances in Intelligent Systems and Computing - International Joint Conference SOCO’18-CISIS’18-ICEUTE’18 ◽

10.1007/978-3-319-94120-2_19 ◽

2018 ◽

pp. 197-206

Author(s):

Inés Sittón Candanedo ◽

Sara Rodríguez González ◽

Fernando De la Prieta ◽

Angélica González Arrieta

Keyword(s):

Industry 4.0 ◽

Multi Agent System ◽

Agent System ◽

Multi Agent

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Industry 4.0: Development of a multi-agent system for dynamic value stream mapping in SMEs

Journal of Manufacturing Systems ◽

10.1016/j.jmsy.2019.05.001 ◽

2019 ◽

Vol 52 ◽

pp. 1-12 ◽

Cited By ~ 15

Author(s):

Zhuoyu Huang ◽

Jiwon Kim ◽

Alireza Sadri ◽

Steve Dowey ◽

Matthew S. Dargusch

Keyword(s):

Industry 4.0 ◽

Value Stream Mapping ◽

Multi Agent System ◽

Agent System ◽

Value Stream ◽

Multi Agent

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A Framework to Improve the Disaster Response Through a Knowledge-Based Multi-Agent System

International Journal of Information Systems for Crisis Response and Management ◽

10.4018/ijiscram.2017070106 ◽

2017 ◽

Vol 9 (3) ◽

pp. 96-109

Author(s):

Claire Prudhomme ◽

Christophe Cruz ◽

Ana Roxin ◽

Frank Boochs

Keyword(s):

Decision Making ◽

Information Exchange ◽

Disaster Response ◽

Explicit Representation ◽

Multi Agent System ◽

Agent System ◽

Knowledge Based ◽

Testing Strategies ◽

Generic Agent ◽

Multi Agent

The disaster response still faces problems of collaboration due to lack of policies concerning the information exchange during the response. Moreover, plans are prepared to respond to a disaster, but drills to apply them are limited and do not allow to determine their efficiency and conflicts with other organizations. This paper presents a framework allowing for different organizations involving in the disaster response to assess their collaboration through its simulation using an explicit representation of their knowledge. This framework is based on a multi-agent system composed of three generic agent models to represent the organizational structure of disaster response. The decision-making about response actions is done through task decomposition and repartition. It is based reasoning on ontologies which provides an explicit trace of the response plans design and their execution. Such framework aims at identifying cooperation problems and testing strategies of information exchange to support the preparation of disaster response.

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Multi-agent system for anomaly detection in Industry 4.0 using Machine Learning techniques

ADCAIJ ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL ◽

10.14201/adcaij2019843340 ◽

2019 ◽

Vol 8 (4) ◽

pp. 33

Author(s):

Nuria MATEOS GARCÍA

Keyword(s):

Machine Learning ◽

Anomaly Detection ◽

Industry 4.0 ◽

Machine Learning Techniques ◽

Multi Agent System ◽

Agent System ◽

Learning Techniques ◽

Multi Agent

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Industry 4.0 Multi-agent System Based Knowledge Representation Through Blockchain

Advances in Intelligent Systems and Computing - Ambient Intelligence – Software and Applications –, 9th International Symposium on Ambient Intelligence ◽

10.1007/978-3-030-01746-0_39 ◽

2018 ◽

pp. 331-337

Author(s):

Pedro Pinheiro ◽

Ricardo Santos ◽

Ricardo Barbosa

Keyword(s):

Knowledge Representation ◽

Industry 4.0 ◽

Multi Agent System ◽

Agent System ◽

Multi Agent

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Automatic Construction of Virtual Supply Chain as Multi-Agent System Using Enterprise E-Catalogues

International Journal of Automation Technology ◽

10.20965/ijat.2020.p0713 ◽

2020 ◽

Vol 14 (5) ◽

pp. 713-722

Author(s):

Tatsushi Nishi ◽

Michiko Matsuda ◽

Mao Hasegawa ◽

Roghayyeh Alizadeh ◽

Ziang Liu ◽

...

Keyword(s):

Supply Chain ◽

Industry 4.0 ◽

Chain Model ◽

Multi Agent System ◽

Agent System ◽

Automatic Construction ◽

Enterprise Model ◽

Enterprise Models ◽

Multi Agent ◽

Construction System

In Industry 4.0, a network of enterprises and factories is constructed collaboratively and dynamically according to the cyber physical system (CPS) paradigm. It is necessary to build smart supply chains according to this concept. A network of component enterprises in a supply chain would be modeled as a virtual supply chain in the cyber world. From the viewpoint of Industry 4.0, virtualizing a supply chain is the foundation for constructing a CPS for a supply chain. The virtualization of a supply chain makes it easier for companies to study their integrating and expanding opportunities. By using this CPS, comprehensive and autonomous optimization of the supply chain can be achieved. This virtual supply chain can be used to simulate the planning phase with negotiation, as well as the production phase. In this paper, instead of specific mathematical modeling for each supply chain, a general configuration method of a virtual supply chain is proposed. The configuration method of a supply chain model is proposed as a virtual supply chain using enterprise e-catalogues. A virtual supply chain is constructed as a multi-agent system, which is connections of software agents that are automatically created from each selected enterprise model in the e-catalogues. Three types of component enterprise models are provided: manufacturer model, part/material supplier model, and retailer model. Modeling templates for these three types of enterprises are prepared, and each template is a nominal model in terms of enterprise’s behavior. Specific component-enterprise models are prepared by filling the appropriate template. Each component enterprise agent is implemented using the enterprise model selected from the catalogues. Manufacturer, retailer, and supplier e-catalogues, as well as an automatic construction system of a virtual supply chain, are implemented. Methods for developing templates for the manufacturer, retailer and supplier were provided, and the construction system for specific enterprise models (as e-catalogues) is implemented as a trial.

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