Control of Manufacturing Systems by HMS/EPS Paradigms Orchestrating I4.0 Components Based on Capabilities

Veiga, Jackson T.; Pessoa, Marcosiris A. O.; Junqueira, Fabrício; Filho, Diolino José dos Santos

doi:10.1007/978-3-030-78288-7_6

Cited by 2 publications

(9 citation statements)

References 10 publications

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“…Fleischmann et al report that a subjectoriented modeling language, Parallel Activity Specification Schema, is suitable for designing I4C, especially for implementations with OPC UA [42]. Another I4C design framework based on multiple agents with different tasks and optimization has been proposed by Veiga et al [43,44]. These modeling framework studies explore the design purposes and implementation of I4C.…”

Section: B Intelligent Products In Manufacturingmentioning

confidence: 99%

An Intelligent Product-Driven Manufacturing System Using Data Distribution Service

Lin,

2024

IEEE Access

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As key components of smart factories, intelligent production machines are gradually becoming a major capital asset of companies in the market, offering connectivity, interoperability, and services. However, due to commercial and technological constraints, production machines rarely provide enough information for customers to develop data-driven applications. Therefore, this research proposes that intelligence should be built into them to assist in production control and to allow relevant data to be collected and made available for future use. In order to realize this proposal, in this paper, an operational paradigm for such systems is first outlined. Then, the states of workpieces in a production environment are classified, and the methods of generation, operation, and transfer of instances described. The next step is to build an intelligent product-driven manufacturing system using Data Distribution Service (DDS). Intelligent workpieces and machines collaborate to complete production tasks in such a system. In the course of this collaborative process, an intelligent workpiece continuously collects relevant data and packages it together for the customer on its transformation into a final product. The feasibility of this intelligent product-driven manufacturing system is examined by upgrading a classic manufacturing factory. In addition, the study explores the system architecture, the implementation of a classic system upgrade, the production data collection, and the intellectualization of data assets. In conclusion, this study's results will help machine builders expand their business models providing customers with production machines that carry data for advanced data-driven applications.

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Section: B Intelligent Products In Manufacturingmentioning

confidence: 99%

An Intelligent Product-Driven Manufacturing System Using Data Distribution Service

Lin,

2024

IEEE Access

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“…A three-dimensional model, divided into layers for the treatment of information (including the life cycle and hierarchical levels of traditional systems), was introduced by RAMI4.0. This reference architecture standardizes and systematizes virtual resources through technical descriptions in I4.0C [7].…”

Section: Virtual Representation In the I40 Context With Aasmentioning

confidence: 99%

“…The I4.0 Component (I4.0C) is considered a proposal for global standardization, capable of communicating I4.0 assets. The I4.0C is composed of the Asset Administration Shell (AAS), and the Asset [6,7]. The Asset Administration Shell is the digital and active virtual representation of an I4.0C on the I4.0 system (Figure 1).…”

Section: Virtual Representation In the I40 Context With Aasmentioning

confidence: 99%

“…Different works provide ways of contributing to the implementation of the DT [1][2][3]7,11,18]; however, the proposals generally implement specific cases, such as searching for equipment, connecting assets to the cloud [1,23], digitizing PLCs [24] the tractability of assets [25] and, interoperability [26][27][28]. However, it was impossible to notice works that describe a methodology to enable the concept of an active object in AAS, allowing it to understand its attributes and collaborate with the connected components to form societies in the connected world.…”

Section: Related Work About the Researchmentioning

confidence: 99%

“…I4.0 presents a capabilities submodel to specificity the capabilities of the resources [2]. The AAS models, suggest products based on manufacturing processes in which it is possible to choose the resources skills that best meet the product need [7]. However, the I4.0 AAS specifications use passive object concepts requiring a plugin for applications that allow the management of virtual resource capabilities [8].…”

Section: Introductionmentioning

confidence: 99%

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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)

et al. 2021

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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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Control of Manufacturing Systems by HMS/EPS Paradigms Orchestrating I4.0 Components Based on Capabilities

Cited by 2 publications

References 10 publications

An Intelligent Product-Driven Manufacturing System Using Data Distribution Service

An Intelligent Product-Driven Manufacturing System Using Data Distribution Service

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

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