Bio-inspired multi-agent systems for reconfigurable manufacturing systems

Manufacturing systems need to meet I4.0 guidelines to deal with uncertainty in scenarios of turbulent demand for products. The engineering concepts to define the service’s resources to manufacture the products will be more flexible, ensuring the possibility of re-planning in operation. These can follow the engineering paradigm based on capabilities. The virtualization of industry components and assets achieves the RAMI 4.0 guidelines and (I4.0C), which describes the Asset Administration Shell (AAS). However, AAS are passive components that provide information about I4.0 assets. The proposal of specific paradigms is exposed for managing these components, as is the case of multi-agent systems (MAS) that attribute intelligence to objects. The implementation of resource coalitions with evolutionary architectures (EAS) applies cooperation and capabilities’ association. Therefore, this work focuses on designing a method for modeling the asset administration shell (AAS) as virtual elements orchestrating intelligent agents (MAS) that attribute cooperation and negotiation through contracts to coalitions based on the engineering capabilities concept. The systematic method suggested in this work is partitioned for the composition of objects, AAS elements, and activities that guarantee the relationship between entities. Finally, Production Flow Schema (PFS) refinements are applied to generate the final Petri net models (PN) and validate them with Snoopy simulations. The results achieved demonstrate the validation of the procedure, eliminating interlocking and enabling liveliness to integrate elements behavior.

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A Systematic Modelling Procedure to Design Agent-Oriented Control to Coalition of Capabilities—In the Context of I4.0 as Virtual Assets (AAS)

Computers ◽

10.3390/computers10120161 ◽

2021 ◽

Vol 10 (12) ◽

pp. 161

Author(s):

Jackson T. Veiga ◽

Marcosiris A. O. Pessoa ◽

Fabrício Junqueira ◽

Paulo E. Miyagi ◽

Diolino J. dos Santos Filho

Keyword(s):

Intelligent Agents ◽

Manufacturing Systems ◽

Multi Agent Systems ◽

Production Flow ◽

Systematic Method ◽

Passive Components ◽

Agent Systems ◽

Modelling Procedure ◽

Multi Agent ◽

The Relationship

Manufacturing systems need to meet Industry 4.0 (I4.0) guidelines to deal with uncertainty in scenarios of turbulent demand for products. The engineering concepts to define the service’s resources to manufacture the products will be more flexible, ensuring the possibility of re-planning in operation. These can follow the engineering paradigm based on capabilities. The virtualization of industry components and assets achieves the RAMI 4.0 guidelines and (I4.0C), which describes the Asset Administration Shell (AAS). However, AAS are passive components that provide information about I4.0 assets. The proposal of specific paradigms is exposed for managing these components, as is the case of multi-agent systems (MAS) that attribute intelligence to objects. The implementation of resource coalitions with evolutionary architectures (EAS) applies cooperation and capabilities’ association. Therefore, this work focuses on designing a method for modeling the asset administration shell (AAS) as virtual elements orchestrating intelligent agents (MAS) that attribute cooperation and negotiation through contracts to coalitions based on the engineering capabilities concept. The systematic method suggested in this work is partitioned for the composition of objects, AAS elements, and activities that guarantee the relationship between entities. Finally, Production Flow Schema (PFS) refinements are applied to generate the final Petri net models (PN) and validate them with Snoopy simulations. The results achieved demonstrate the validation of the procedure, eliminating interlocking and enabling liveliness to integrate elements’ behavior.

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A Systematic Modelling Procedure to Design Agent-Oriented Control to Coalition of Capabilities - In the Context of I4.0 as Virtual Assets (AAS)

10.20944/preprints202111.0083.v2 ◽

2021 ◽

Author(s):

Jackson Tavares Veiga ◽

Marcosiris Amorim de Oliveira Pessoa ◽

Fabrício Junqueira ◽

Paulo Eigi Miyagi ◽

Diolino José Dos Santos Filho

Keyword(s):

Intelligent Agents ◽

Manufacturing Systems ◽

Multi Agent Systems ◽

Production Flow ◽

Systematic Method ◽

Passive Components ◽

Agent Systems ◽

Modelling Procedure ◽

Multi Agent ◽

The Relationship

Manufacturing systems need to meet I4.0 guidelines to deal with uncertainty in scenarios of turbulent demand for products. The engineering concepts to define the service’s resources to manufacture the products will be more flexible, ensuring the possibility of re-planning in operation. These can follow the engineering paradigm based on capabilities. The virtualization of industry components and assets achieves the RAMI 4.0 guidelines and (I4.0C), which describes the Asset Administration Shell (AAS). However, AAS are passive components that provide information about I4.0 assets. The proposal of specific paradigms is exposed for managing these components, as is the case of multi-agent systems (MAS) that attribute intelligence to objects. The implementation of resource coalitions with evolutionary architectures (EAS) applies cooperation and capabilities’ association. Therefore, this work focuses on designing a method for modeling the asset administration shell (AAS) as virtual elements orchestrating intelligent agents (MAS) that attribute cooperation and negotiation through contracts to coalitions based on the engineering capabilities concept. The systematic method suggested in this work is partitioned for the composition of objects, AAS elements, and activities that guarantee the relationship between entities. Finally, Production Flow Schema (PFS) refinements are applied to generate the final Petri net models (PN) and validate them with Snoopy simulations. The results achieved demonstrate the validation of the procedure, eliminating interlocking and enabling liveliness to integrate elements behavior.

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Reconfigurable Manufacturing Systems Design for a Contract Manufacturer Using a Co-operative Co-evolutionary Multi-agent Approach

Collaborative Design and Planning for Digital Manufacturing ◽

10.1007/978-1-84882-287-0_5 ◽

2009 ◽

pp. 117-136

Author(s):

Nathan Young ◽

Mervyn Fathianathan

Keyword(s):

Manufacturing Systems ◽

Systems Design ◽

Reconfigurable Manufacturing Systems ◽

Reconfigurable Manufacturing ◽

Multi Agent ◽

Manufacturing Systems Design

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Production degrees of freedom as manufacturing system reconfiguration potential measures

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture ◽

10.1243/09544054jem1056 ◽

2008 ◽

Vol 222 (10) ◽

pp. 1301-1314 ◽

Cited By ~ 29

Author(s):

A M Farid ◽

D C McFarlane

Keyword(s):

Manufacturing Systems ◽

Degrees Of Freedom ◽

Manufacturing System ◽

Automated Manufacturing ◽

Reconfigurable Manufacturing ◽

Multi Agent Systems ◽

Automated Manufacturing Systems ◽

System Reconfiguration ◽

Multi Agent ◽

Changes Over Time

In recent years, many design approaches have been developed for automated manufacturing systems in the fields of reconfigurable manufacturing systems (RMSs), holonic manufacturing systems (HMSs), and multi-agent systems (MASs). One of the principle reasons for these developments has been to enhance the reconfigurability of a manufacturing system, allowing it to adapt readily to changes over time. However, to date, reconfigurability assessment has been limited. Hence, the efficacy of these design approaches remains inconclusive. This paper is the first of two in this issue to address reconfigurability measurement. Specifically, it seeks to address ‘reconfiguration potential’ by analogy. Mechanical degrees of freedom have been used in the field of mechanics as a means of determining the independent directions of motion of a mechanical system. By analogy, manufacturing degrees of freedom can be used to determine independent ways of production. Furthermore, manufacturing degrees of freedom can be classified into their production and product varieties. This paper specifically focuses on the former to measure the product-independent aspects of manufacturing system ‘reconfiguration potential’. This approach will be added to complementary work on the measurement of ‘reconfiguration ease’ so as to form an integrated reconfigurability measurement process described elsewhere [1—5].

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Multi-agent systems applications in manufacturing systems and supply chain management: a review paper

International Journal of Production Research ◽

10.1080/00207540701441921 ◽

2007 ◽

Vol 46 (1) ◽

pp. 233-265 ◽

Cited By ~ 93

Author(s):

J.-H. Lee ◽

C.-O. Kim

Keyword(s):

Supply Chain ◽

Supply Chain Management ◽

Manufacturing Systems ◽

Review Paper ◽

Multi Agent Systems ◽

Chain Management ◽

Agent Systems ◽

Multi Agent

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Intelligent Agents and Multi-Agent Systems

Manufacturing Intelligence for Industrial Engineering - Advances in Civil and Industrial Engineering ◽

10.4018/978-1-60566-864-2.ch003 ◽

2010 ◽

pp. 47-83

Author(s):

Zude Zhou ◽

Huaiqing Wang ◽

Ping Lou

Keyword(s):

Intelligent Agents ◽

Manufacturing Systems ◽

Manufacturing Industry ◽

Intelligent Manufacturing ◽

Agent Technology ◽

Multi Agent Systems ◽

Global Competitiveness ◽

Agent Systems ◽

Market Responsiveness ◽

Multi Agent

Multi-Agent systems (MAS) are typical KBS and intelligent agents are viewed as extensions of KBS. Originating from the field of Distributed Artificial Intelligence (DAI), agent and Multi-Agent (MA) technology has been at the forefront of research in the last decade (Nilsson, 1998). Since the late 1980s, researchers have applied agent technology to perform tasks, and it is considered a promising paradigm for intelligent manufacturing (Shen & Norrie, 2001). In the 21st century especially, the manufacturing industry has become more and more competitive in a market that is frequently changing. Manufacturing systems should therefore move to support product innovation, global competitiveness and rapid market responsiveness. Recent new developments in agent and MA technology have brought new and interesting possibilities (Jennings & Wooldridge, 1998), researchers have been trying to develop and apply agent technology for supporting intelligent manufacturing, and there have been many projects in agent-based intelligent manufacturing. The basic theory and applications of agent and MAS are introduced in this chapter. The recent development of agent and MAS is reviewed, and the current research level of MAS is also summarized. Finally, the fundamentals of agent technology including communication and interaction, collaboration and behavior coordination, are presented.

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