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

2020 ◽  
Vol 123 ◽  
pp. 103300 ◽  
Author(s):  
Szilárd Jaskó ◽  
Adrienn Skrop ◽  
Tibor Holczinger ◽  
Tibor Chován ◽  
János Abonyi
Author(s):  
Maria João Lopes ◽  
Duarte Almeida ◽  
Francisco J. A. Cardoso

With Industry 4.0 related initiatives, a brand new array of opportunities has emerged for organizations to face the ordeals that come with managing ever-growing manufacturing needs. The exponential increase in the complexity of supply chain management has put a real strain on manufacturing operations. In order to succeed, organizations must turn to solutions such as manufacturing execution systems (MES) in order to stay competitive. In this research chapter, we discuss the impact of MES in organizations, whilst describing the process for going from a theoretical concept to a hands-on system which runs the shop floor operations.


2016 ◽  
Vol 3 (4) ◽  
pp. 16-21 ◽  
Author(s):  
Francisco Almada-Lobo

Industry 4.0 dictates the end of traditional centralized applications for production control. Its vision of ecosystems of smart factories with intelligent and autonomous shop-floor entities is inherently decentralized. Responding to customer demands for tailored products, these plants fueled by technology enablers such as 3D printing, Internet of Things, Cloud computing, Mobile Devices and Big Data, among others create a totally new environment. The manufacturing systems of the future, including manufacturing execution systems (MES) will have to be built to support this paradigm shift.


2016 ◽  
Vol 70 (9) ◽  
pp. 616-620
Author(s):  
Yannick Gendre ◽  
Gérard Waridel ◽  
Myrtille Guyon ◽  
Jean-François Demuth ◽  
Hervé Guelpa ◽  
...  

2014 ◽  
Vol 590 ◽  
pp. 763-767
Author(s):  
Zhi Hui Huang

This paper aiming at the zero-failure data and uncertain-decision problems exist in the information system reliability growth process, it proposes to build the Bayesian network topology of FMEA. It adopts Leaky Noisy-OR model, and it analyses the probability that the subsystem functional module will go wrong in quantity. It solves the problem of identifying the vague and incomplete information exists in the complex system rapidly and accurately, laying the foundation for further study of the reliability growth comprehensive ability assessment of system based on the Bayesian network. In this paper, on the background of Manufacturing Execution Systems (MES) engineering, aimed at research on models and evaluation methods of reliability growth for MES, enclosing reliability of MES task and design target, reliability growth test and analysis methods, it proposes the goal of MES reliability growth planning.


2015 ◽  
Vol 105 (04) ◽  
pp. 204-208
Author(s):  
D. Kreimeier ◽  
E. Müller ◽  
F. Morlock ◽  
D. Jentsch ◽  
H. Unger ◽  
...  

Kurzfristige sowie ungeplante Änderungen – wie Auftragsschwankungen, Maschinenausfälle oder Krankheitstage der Mitarbeiter – beeinflussen die Produktionsplanung und -steuerung (PPS) von Industriefirmen. Trends wie Globalisierung und erhöhter Marktdruck verstärken diese Probleme. Zur Komplexitätsbewältigung bei der Entscheidungsfindung zur Fertigungssteuerung kommen in der Produktion Werkzeuge der „Digitalen Fabrik“, beispielsweise Simulationsprogramme, oder IT (Informationstechnologie)-Lösungen, wie Manufacturing Execution Systems (MES), zum Einsatz. Eine Verknüpfung dieser Bereiche würde einen echtzeitfähigen Datenaustausch erlauben, der wiederum eine echtzeitfähige Entscheidungsunterstützung bietet. Der Fachbeitrag stellt hierfür einen Lösungsansatz vor.   Sudden and unsystematic changes, such as fluctuations in order flow, machine failures, or employee sick days affect the Production Planning and Control (PPC) activities of industrial companies. Trends like globalization and increased market pressure intensify these problems. To master the complexity of decision-making in production control, tools of the digital factory (e.g. simulation systems) or IT systems (e.g. Manufacturing Execution Systems (MES)) are applied in manufacturing. Combining these areas would enable real-time capable data exchange which, in turn, provides real-time capable decision support. This article presents an approach for solving this problem.


2012 ◽  
Vol 9 (3) ◽  
pp. 1287-1305 ◽  
Author(s):  
Carlos Pascal ◽  
Doru Panescu

One of the key design issues for distributed systems is to find proper planning and coordination mechanisms when knowledge and decision capabilities are spread along the system. This contribution refers holonic manufacturing execution systems and highlights the way a proper modeling method - Petri nets - makes evident certain problems that can appear when agents have to simultaneously treat more goals. According to holonic organization the planning phase is mainly dependent on finding an appropriate resource allocation mechanism. The type of weakness is established by means of the proposed Petri net models and further proved by simulation experiments. A solution to make the holonic scheme avoid a failure in resource allocation is mentioned, too.


2021 ◽  
Author(s):  
Muzaffar Rao ◽  
Thomas Newe

The current manufacturing transformation is represented by using different terms like; Industry 4.0, smart manufacturing, Industrial Internet of Things (IIoTs), and the Model-Based enterprise. This transformation involves integrated and collaborative manufacturing systems. These manufacturing systems should meet the demands changing in real-time in the smart factory environment. Here, this manufacturing transformation is represented by the term ‘Smart Manufacturing’. Smart manufacturing can optimize the manufacturing process using different technologies like IoT, Analytics, Manufacturing Intelligence, Cloud, Supplier Platforms, and Manufacturing Execution System (MES). In the cell-based manufacturing environment of the smart industry, the best way to transfer the goods between cells is through automation (mobile robots). That is why automation is the core of the smart industry i.e. industry 4.0. In a smart industrial environment, mobile-robots can safely operate with repeatability; also can take decisions based on detailed production sequences defined by Manufacturing Execution System (MES). This work focuses on the development of a middleware application using LabVIEW for mobile-robots, in a cell-based manufacturing environment. This application works as middleware to connect mobile robots with the MES system.


2014 ◽  
Vol 2014 (3) ◽  
pp. 156-160
Author(s):  
Игорь Васильев ◽  
Igor Vasilev ◽  
Евгений Фролов ◽  
Evgeniy Frolov

The practice of applying the Russian MES-system at machine-building enterprises is described in this article.


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