Development of manufacturing execution systems in accordance with Industry 4.0 requirements: A review of standard- and ontology-based methodologies and tools

Jaskó, Szilárd; Skrop, Adrienn; Holczinger, Tibor; Chován, Tibor; Abonyi, János

doi:10.1016/j.compind.2020.103300

Cited by 133 publications

(63 citation statements)

References 30 publications

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“…In the paper, the authors identified, investigated, and reviewed the major issues connected to MESs back then. As the authors of literature review paper [ 14 ] mentioned, Industry 4.0 solutions has a significant influence on the development of MESs. This statement resulted as a consequence of their recently published revision of standards, ontology-based methodologies, and tools dedicated to development of MESs.…”

Section: Literature Reviewmentioning

confidence: 99%

Personalization of the MES System to the Needs of Highly Variable Production

Zwolińska

Tubis

Chamier-Gliszczyński

et al. 2020

Sensors

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The new generation Manufacturing Executions System (MES) is considered as one of the most important solutions supporting the idea of Industry 4.0. This is confirmed by research conducted among companies interested in the implementation of the Industry 4.0 concept, as well as the publications of researchers who study this issue. However, if MES software is a link that connects the world of machines and business systems, it must take into account the specifics of the supported production systems. This is especially true in case of production systems with a high level of automation, which are characterised by flexibility and agility at the operational level. Therefore, personalization of the MES software is proposed for this class of production systems. The aim of the article is to present the MES system personalization method for a selected production system. The proposed approach uses the rules of Bayesian inference and the area of customisation is the technological structure of production, taking into account the required flexibility of the processes. As part of the developed approach, the variability index was proposed as a parameter evaluating the effectiveness of the production system. Then, the results of evaluation of the current system effectiveness by use of this index are presented. The authors also present the assumptions for the developed MES personalization algorithm. The algorithm uses the rules of Bayesian inference, which enable multiple adjustments of the model to the existing environmental conditions without the need to formulate a new description of reality. The application of the presented solution in a real facility allowed for determining production areas which are the determinants of system instability. The implementation of the developed algorithm enabled control of the generated variability in real time. The proposed approach to personalization of MES software for a selected class of production systems is the main novelty of the presented research and contributes to the development of the described area of research.

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Section: Literature Reviewmentioning

confidence: 99%

Personalization of the MES System to the Needs of Highly Variable Production

Zwolińska

Tubis

Chamier-Gliszczyński

et al. 2020

Sensors

View full text Add to dashboard Cite

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“…Managing information and data from production systems is critical for digital transformation, especially in Industry 4.0 applications, where the horizontal and vertical integration of systems requires more efficient data processing. More efforts have been made to standardize this area, such as the ANSI/ ISA-95 international standard or RAMI 4.0 (Reference Architectural Model Industrie 4.0) [1]. Furthermore, there are ongoing studies in the field of different methodologies and data structurization that aim to support productionrelated decision-making processes [2] or create models without simulation software-specific knowledge [3].…”

Section: Introductionmentioning

confidence: 99%

“…Because of the importance of horizontal and vertical integration in Industry 4.0, ontologies are being used in production systems to share information over an increasingly wide range [1]. Manufacturing companies are faced with many information sharing tasks such as B2M, M2M, and B2B (communication channels between business (B) and/or machine (M) units) [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…e information has to be transferred between information systems, optimization methods, or digital twin simulators [12]. Due to the growing demand, the previously proposed developments for ISA-95, ISA-88, AutomationML (Automation Markup Language), and B2MML (Business to Manufacturing Markup Language) industry standards as well as frameworks have intensified [1]; moreover, these are based on knowledge graphs or ontologies.…”

Section: Introductionmentioning

confidence: 99%

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Ontology-Based Analysis of Manufacturing Processes: Lessons Learned from the Case Study of Wire Harness Production

2021

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Effective information management is critical for the development of manufacturing processes. This paper aims to provide an overview of ontologies that can be utilized in building Industry 4.0 applications. The main contributions of the work are that it highlights ontologies that are suitable for manufacturing management and recommends the multilayer-network-based interpretation and analysis of ontology-based databases. This article not only serves as a reference for engineers and researchers on ontologies but also presents a reproducible industrial case study that describes the ontology-based model of a wire harness assembly manufacturing process.

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“…The applications of the fourth industrial revolution require great flexibility on the part of industrial cyber-physical systems (ICPS) to achieve optimal operating points that integrate the entire value chain of a process. This requires the capture of new data that are subsequently processed at different levels of the hierarchy of automation processes, with requirements and technologies according to each level [2][3][4][5]. This presents challenges related to the incorporation of new functionalities in the processes and the interoperability between them with the collaboration between distributed nodes.…”

Section: Introductionmentioning

confidence: 99%

Software Components for Smart Industry Based on Microservices: A Case Study in pH Control Process for the Beverage Industry

et al. 2021

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Modern industries require constant adaptation to new trends. Thus, they seek greater flexibility and agility to cope with disruptions, as well as to solve needs or meet the demand for growth. Therefore, smart industrial applications require a lot of flexibility to be able to react more quickly to continuous market changes, offer more personalized products, increase operational efficiency, and achieve optimum operating points that integrate the entire value chain of a process. This requires the capture of new data that are subsequently processed at different levels of the hierarchy of automation processes, with requirements and technologies according to each level. The result is a new challenge related to the addition of new functionalities in the processes and the interoperability between them. This paper proposes a distributed computational component-based framework that integrates communication, computation, and storage resources and real-time capabilities through container technology, microservices, and the publish/subscribe paradigm, as well as contributing to the development and implementation of industrial automation applications by bridging the gap between generic architectures and physical realizations. The main idea is to enable plug-and-play software components, from predefined components with their interrelationships, to achieve industrial applications without losing or degrading the robustness from previous developments. This paper presents the process of design and implementation with the proposed framework through the implementation of a complex pH control process, ranging from the simulation part to its scaling and implementation to an industrial level, showing the plug-and-play assembly from a definition of components with their relationships to the implementation process with the respective technologies involved. The effectiveness of the proposed framework was experimentally verified in a real production process, showing that the results scaled to an industrial scale comply with the simulated design process. A qualitative comparison with traditional industrial implementations, based on the implementation requirements, was carried out. The implementation was developed in the beverage production plant “Punta Delicia”, located in Colima, Mexico. Finally, the results showed that the platform provided a high-fidelity design, analysis, and testing environment for cyber information flow and their effect on the physical operation of the pH control.

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Development of manufacturing execution systems in accordance with Industry 4.0 requirements: A review of standard- and ontology-based methodologies and tools

Cited by 133 publications

References 30 publications

Personalization of the MES System to the Needs of Highly Variable Production

Personalization of the MES System to the Needs of Highly Variable Production

Ontology-Based Analysis of Manufacturing Processes: Lessons Learned from the Case Study of Wire Harness Production

Software Components for Smart Industry Based on Microservices: A Case Study in pH Control Process for the Beverage Industry

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