832 research outputs found
Agent-based asset administration shell approach for digitizing industrial assets
Modern manufacturing systems are facing new challenges related to the fast-changing market conditions, increased global competition and rapid technological developments, imposing strong requirements in terms of flexibility, robustness and reconfigurability. In this context, the Industry 4.0 (I4.0) paradigm relies on digitizing industrial assets to fulfil these requirements. The implementation of this digitization process is being promoted by the so-called Asset Administration Shell (AAS), a digital representation of an asset that complies with standardization and interoperability strategies. At this moment, a significant part of the AAS developments is more focused on the information management of the asset along its lifecycle and not concerned with aspects of intelligence and collaboration, which are fundamental aspects to develop I4.0 compliant solutions. In this sense, this paper presents an agent-based AAS approach for enhancing the digitization process of assets, considering agents to embed distributed intelligence and collaborative functions, service orientation to support interoperability, and holonic principles to provide the system organization. The proposed agent-based AAS was implemented in an industrial automation system aiming to analyze its applicability.info:eu-repo/semantics/publishedVersio
Multi-agent systems to implement industry 4.0 components
The fast-changing market conditions, the increased global competition and the rapid technological developments demand flexible, adaptable and reconfigurable manufacturing systems based on Cyber-Physical Systems (CPS). Aligned with CPS, the adoption of production system architectures is suitable to reduce complexity and achieve interoperability in the industrial applications. In this context, the Reference Architecture Model for Industry 4.0 (RAMI4.0) provides the guidelines to develop Industry 4.0 (I4.0) compliant solutions, considering the existing industrial standards. The so-called I4.0 components implement this model in practice, combining the physical asset with its digital representation, named Asset Administration Shell (AAS). This paper explores the use of Multi-Agent Systems (MAS) to implement the AAS functionalities, taking advantage of their inherits characteristics, e.g., autonomy, intelligence, decentralization and reconfigurability. In this context, the mapping between AAS functionalities and MAS characteristics is provided, as well as the challenges for this implementation. The applicability is illustrated by digitalizing an inspection cell comprising an UR3 robot and several console products by using MAS technology.info:eu-repo/semantics/publishedVersio
Towards the digitization using asset administration shells
Industry 4.0 (I4.0) is promoting the digitization
of traditional manufacturing systems towards flexible, reconfigurable
and intelligent factories based on Cyber-Physical Systems
(CPS). In this context, the Reference Architecture Model
Industrie 4.0 (RAMI4.0) provides guidelines to develop I4.0
compliant solutions based on industrial standards. As the main
RAMI4.0 specification, the Asset Administration Shell (AAS) is
a standard digital representation of an industrial asset that plays
a pivotal role in enabling interoperable communication among
I4.0 components across the value chain. This paper provides an
analysis of the current state-of-the-art of implementing AAS,
discussing, amongst others, the key enabling technologies used
to implement the AAS and the alignment of the research works
found in the literature with the I4.0 components criteria.This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020. The author Lucas Sakurada thanks the FCT - Fundação para a Ciência e Tecnologia, Portugal, for the PhD Grant DFA/BD/9234/2020.info:eu-repo/semantics/publishedVersio
Specification of the PERFoRM architecture for the seamless production system reconfiguration
The world is assisting to the fourth industrial revolution, with several domains of science and technology being strongly developed and, specially, being integrated with each other, allowing to build evolvable complex systems. Data digitization, big-data analysis, distributed control, Industrial Internet of Things, Cyber-Physical Systems and self-organization, amongst others, are playing an important role in this journey. This paper considers the best practices from previous successful European projects addressing distributed control systems to develop an innovative architecture that can be industrially deployed. For this purpose, a particular design process has to be addressed in order to consider the requirements and functionalities from various use cases. To investigate the known practices, four use cases are enlighted in this paper, which cover a wide spectrum of the European industrial force, as well as industrial standards to support a smooth migration from traditional systems to the emergent distributed systems.info:eu-repo/semantics/publishedVersio
DIN Spec 91345 RAMI 4.0 compliant data pipelining: An approach to support data understanding and data acquisition in smart manufacturing environments
Today, data scientists in the manufacturing domain are confronted with a set of challenges associated to data acquisition as well as data processing including the extraction of valuable in-formation to support both, the work of the manufacturing equipment as well as the manufacturing processes behind it.
One essential aspect related to data acquisition is the pipelining, including various commu-nication standards, protocols and technologies to save and transfer heterogenous data. These circumstances make it hard to understand, find, access and extract data from the sources depend-ing on use cases and applications.
In order to support this data pipelining process, this thesis proposes the use of the semantic model. The selected semantic model should be able to describe smart manufacturing assets them-selves as well as to access their data along their life-cycle.
As a matter of fact, there are many research contributions in smart manufacturing, which already came out with reference architectures or standards for semantic-based meta data descrip-tion or asset classification. This research builds upon these outcomes and introduces a novel se-mantic model-based data pipelining approach using as a basis the Reference Architecture Model for Industry 4.0 (RAMI 4.0).Hoje em dia, os cientistas de dados no domÃnio da manufatura são confrontados com várias normas, protocolos e tecnologias de comunicação para gravar, processar e transferir vários tipos de dados. Estas circunstâncias tornam difÃcil compreender, encontrar, aceder e extrair dados necessários para aplicações dependentes de casos de utilização, desde os equipamentos aos respectivos processos de manufatura.
Um aspecto essencial poderia ser um processo de canalisação de dados incluindo vários normas de comunicação, protocolos e tecnologias para gravar e transferir dados. Uma solução para suporte deste processo, proposto por esta tese, é a aplicação de um modelo semântico que descreva os próprios recursos de manufactura inteligente e o acesso aos seus dados ao longo do seu ciclo de vida.
Muitas das contribuições de investigação em manufatura inteligente já produziram arquitecturas de referência como a RAMI 4.0 ou normas para a descrição semântica de meta dados ou classificação de recursos. Esta investigação baseia-se nestas fontes externas e introduz um novo modelo semântico baseado no Modelo de Arquitectura de Referência para Indústria 4.0 (RAMI 4.0), em conformidade com a abordagem de canalisação de dados no domÃnio da produção inteligente como caso exemplar de utilização para permitir uma fácil exploração, compreensão, descoberta, selecção e extracção de dados
Digitization of industrial environments through an industry 4.0 compliant approach
About a decade after the introduction of Industry
4.0 (I4.0) as a paradigm oriented towards the digitization
of industrial environments, centered on the concept of industrial
Cyber-physical Systems (CPS) to enable the development of
intelligent and distributed industrial systems, many companies
around the world are still not immersed in this digital
transformation era. This transition is not straightforward and
requires the aligned with the novel technologies, architectures
and standards to migrate entire traditional systems into I4.0
systems. In this context, this paper presents an approach to
perform the digitization of non-I4.0 components/systems into I4.0
through an approach based on the Asset Administration Shell
(AAS), which is a standardized digital representation of an asset.
This approach enables to hold the asset information throughout
its lifecycle, provides a standard communication interface with
the asset, and is based on a set of modules that are combined
with the AAS to provide novel functionalities for the asset, e.g.,
monitoring, diagnosis and optimization. Moreover, this approach
adopts Multi-agent Systems (MAS) to provide mainly autonomy
and collaborative capabilities to the system. The agents are able to
get information from the AASs, making intelligent decisions and
perform distributed tasks following interaction strategies, e.g.,
collaboration, negotiation and self-organization. The feasibility
of the proposed approach was tested by digitizing a small-scale
production system comprising several assets.The authors are grateful to the Foundation for Science
and Technology (FCT), Portugal, for financial support
through national funds FCT/MCTES (PIDDAC) to CeDRI
(UIDB/05757/2020 and UIDP/05757/2020) and SusTEC
(LA/P/0007/2021). The author Lucas Sakurada thanks the FCT
for the PhD Grant 2020.09234.BD.info:eu-repo/semantics/publishedVersio
A Framework for Industry 4.0
The potential of the Industry 4.0 will allow the national industry to develop all kinds of
procedures, especially in terms of competitive differentiation. The prospects and motivations
behind Industry 4.0 are related to the management that is essentially geared towards industrial
internet, to the integrated analysis and use of data, to the digitalization of products and services,
to new disruptive business models and to the cooperation within the value chain. It is through
the integration of Cyber-Physical Systems (CPS), into the maintenance process that it is
possible to carry out a continuous monitoring of industrial machines, as well as to apply
advanced techniques for predictive and proactive maintenance.
The present work is based on the MANTIS project, aiming to construct a specific
platform for the proactive maintenance of industrial machines, targeting particularly the case
of GreenBender ADIRA Steel Sheet. In other words, the aim is to reduce maintenance costs,
increase the efficiency of the process and consequently the profit. Essentially, the MANTIS
project is a multinational research project, where the CISTER Research Unit plays a key role,
particularly in providing the communications infrastructure for one MANTIS Pilot.
The methodology is based on a follow-up study, which is jointly carried with the client,
as well as within the scope of the implementation of the ADIRA Pilot. The macro phases that
are followed in the present work are: 1) detailed analysis of the business needs; 2) preparation
of the architecture specification; 3) implementation/development; 4) tests and validation; 5)
support; 6) stabilization; 7) corrective and evolutionary maintenance; and 8) final project
analysis and corrective measures to be applied in future projects.
The expected results of the development of such project are related to the integration of
the industrial maintenance process, to the continuous monitoring of the machines and to the
application of advanced techniques of preventive and proactive maintenance of industrial
machines, particularly based on techniques and good practices of the Software Engineering area
and on the integration of Cyber-Physical Systems.O potencial desenvolvido pela Indústria 4.0 dotará a indústria nacional de capacidades
para desenvolver todo o tipo de procedimentos, especialmente a nÃvel da diferenciação
competitiva. As perspetivas e as motivações por detrás da Indústria 4.0 estão relacionadas com
uma gestão essencialmente direcionada para a internet industrial, com uma análise integrada e
utilização de dados, com a digitalização de produtos e de serviços, com novos modelos
disruptivos de negócio e com uma cooperação horizontal no âmbito da cadeia de valor. É
através da integração dos sistemas ciber-fÃsicos no processo de manutenção que é possÃvel
proceder a um monitoramento contÃnuo das máquinas, tal como à aplicação de técnicas
avançadas para a manutenção preditiva e pró-ativa das mesmas.
O presente trabalho é baseado no projeto MANTIS, objetivando, portanto, a construção
de uma plataforma especÃfica para a manutenção pró-ativa das máquinas industriais, neste caso
em concreto das prensas, que serão as máquinas industriais analisadas ao longo do presente
trabalho. Dito de um outro modo, objetiva-se, através de uma plataforma em especÃfico, reduzir
todos os custos da sua manutenção, aumentando, portanto, os lucros industriais advindos da
produção. Resumidamente, o projeto MANTIS consiste num projeto de investigação
multinacional, onde a Unidade de Investigação CISTER desenvolve um papel fundamental,
particularmente no fornecimento da infraestrutura de comunicação no Piloto MANTIS.
A metodologia adotada é baseada num estudo de acompanhamento, realizado em
conjunto com o cliente, e no âmbito da implementação do Piloto da ADIRA. As macro fases
que são compreendidas por esta metodologia, e as quais serão seguidas, são: 1) análise
detalhada das necessidades de negócio; 2) preparação da especificação da arquitetura; 3)
implementação/desenvolvimento; 4) testes e validação; 5) suporte; 6) estabilização; 7)
manutenção corretiva e evolutiva; e 8) análise final do projeto e medidas corretivas a aplicar
em projetos futuros.
Os resultados esperados com o desenvolvimento do projeto estão relacionados com a
integração do processo de manutenção industrial, a monitorização contÃnua das máquinas e a
aplicação de técnicas avançadas de manutenção preventiva e pós-ativa das máquinas,
especialmente com base em técnicas e boas práticas da área de Engenharia de Software
Semantic Asset Administration Shells in Industry 4.0: A Survey
The Asset Administration Shell (AAS) is a fundamental concept in the Reference Architecture Model for Industry 4.0 (RAMI 4.0), that provides a virtual and digital representation of all information and functions of a physical asset in a manufacturing environment. Recently, Semantic AASs have emerged that add knowledge representation formalisms to enhance the digital representation of physical assets. In this paper, we provide a comprehensive survey of the scientific contributions to Semantic AASs that model the Information and Communication Layer within RAMI 4.0, and summarise and demonstrate their structure, communication, functionalities, and use cases. We also highlight the challenges of future development of Semantic AASs
Asset Administration Shell in Manufacturing: Applications and Relationship with Digital Twin
Within Industry 4.0 the communication between the physical and the cyber part of manufacturing system faces an ever-growing rise in complexity. The Asset Administration Shell (AAS) is an information framework, within Industry 4.0, that describes the technological features of an asset. It was created to present data and information in a structured and semantically defined format, allowing for interoperability. The work addresses the industrial implementation of AAS, where a systematic literature review has been carried out to investigate the features of the implemented AAS metamodel, and the tools used for the realization of the models. A study of the convergence present in literature between the AAS and Digital Twin (DT) has also been carried out. This paper presents a reference of AAS tools and information for industry practitioners, as well as suggestions for research gaps in the standardization of AAS information modelling. Copyright (C) 2022 The Authors
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