Multi-scale approach from mechatronic to Cyber-Physical Systems for the design of manufacturing systems

Cyber-physical systems, in which computation and networking technologies interact with physical systems, have made great strides into manufacturing systems. From the early days, when electromechanical relays were used to automate conveyors and machines, through the introduction of programmable logic controllers and computer numerical control, computing and networking have become pervasive in manufacturing systems. By increasing the amount of automation at multiple levels within a factory and across the enterprise, cyber-physical manufacturing systems enable higher productivity and higher quality as well as lower costs.

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Role of Ontologies for CPS Implementation in Manufacturing

Management and Production Engineering Review ◽

10.1515/mper-2015-0033 ◽

2015 ◽

Vol 6 (4) ◽

pp. 26-32 ◽

Cited By ~ 20

Author(s):

Marco Garetti ◽

Luca Fumagalli ◽

Elisa Negri

Keyword(s):

Domain Knowledge ◽

Manufacturing Systems ◽

Manufacturing System ◽

Cyber Physical Systems ◽

Physical Systems ◽

Network Connection ◽

Manufacturing Applications ◽

And Storage ◽

Embedded Intelligence

Abstract Cyber Physical Systems are an evolution of embedded systems featuring a tight combination of collaborating computational elements that control physical entities. CPSs promise a great potential of innovation in many areas including manufacturing and production. This is because we obtain a very powerful, flexible, modular infrastructure allowing easy (re) configurability and fast ramp-up of manufacturing applications by building a manufacturing system with modular mechatronic components (for machining, transportation and storage) and embedded intelligence, by integrating them into a system, through a network connection. However, when building such kind of architectures, the way to supply the needed domain knowledge to real manufacturing applications arises as a problem to solve. In fact, a CPS based architecture for manufacturing is made of smart but independent manufacturing components without any knowledge of the role they have to play together in the real world of manufacturing applications. Ontologies can supply such kind of knowledge, playing a very important role in CPS for manufacturing. The paper deals with this intriguing theme, also presenting an implementation of this approach in a research project for the open automation of manufacturing systems, in which the power of CPS is complemented by the support of an ontology of the manufacturing domain.

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Holonic Reengineering to Foster Sustainable Cyber-Physical Systems Design in Cognitive Manufacturing

Applied Sciences ◽

10.3390/app11072941 ◽

2021 ◽

Vol 11 (7) ◽

pp. 2941

Author(s):

Alejandro Martín-Gómez ◽

María Jesús Ávila-Gutiérrez ◽

Francisco Aguayo-González

Keyword(s):

Value Chain ◽

Manufacturing Systems ◽

Systems Design ◽

Cyber Physical Systems ◽

Multi Agent Systems ◽

Metabolic Rift ◽

Physical Systems ◽

Sustainable Value ◽

A Cell ◽

Nature And Society

Value chain is identified as the generator of the metabolic rift between nature and society. However, the sustainable value chain can mitigate and reverse this rift. In this paper, firstly, a review of the main digital enablers of Industry 4.0 and the current state of cognitive manufacturing is carried out. Secondly, Cyber-Physical Systems are conceived from the holonic paradigm, as an organizational enabler for the whole of enablers. Thirdly, the bijective relationship between holonic paradigm and container-based technology is analyzed. This technology allows mapping the physical and virtual holon as an intelligent agent embodied at the edge, fog and cloud level, with physical and virtual part. Finally, the proposed holonic system based on the cyber-physical holon is developed through multi-agent systems based on container technology. The proposed system allows to model the metabolism of manufacturing systems, from a cell manufacturing to whole value chain, in order to develop, evolve and improve the sustainable value chain.

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Securing Real-Time Internet-of-Things

Sensors ◽

10.3390/s18124356 ◽

2018 ◽

Vol 18 (12) ◽

pp. 4356 ◽

Cited By ~ 5

Author(s):

Chien-Ying Chen ◽

Monowar Hasan ◽

Sibin Mohan

Keyword(s):

Internet Of Things ◽

Real Time ◽

Manufacturing Systems ◽

Cyber Physical Systems ◽

Cyber Attacks ◽

Power Grids ◽

Embedded Devices ◽

Industrial Control Systems ◽

Physical Systems ◽

Recent Developments

Modern embedded and cyber-physical systems are ubiquitous. Many critical cyber-physical systems have real-time requirements (e.g., avionics, automobiles, power grids, manufacturing systems, industrial control systems, etc.). Recent developments and new functionality require real-time embedded devices to be connected to the Internet. This gives rise to the real-time Internet-of-things (RT-IoT) that promises a better user experience through stronger connectivity and efficient use of next-generation embedded devices. However, RT-IoT are also increasingly becoming targets for cyber-attacks, which is exacerbated by this increased connectivity. This paper gives an introduction to RT-IoT systems, an outlook of current approaches and possible research challenges towards secure RT-IoT frameworks.

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Cloud-based cyber-physical systems and quality of services

The TQM Journal ◽

10.1108/tqm-10-2015-0133 ◽

2016 ◽

Vol 28 (5) ◽

pp. 704-733 ◽

Cited By ~ 42

Author(s):

Dimitris Mourtzis ◽

Ekaterini Vlachou

Keyword(s):

Cloud Computing ◽

Manufacturing Systems ◽

Big Data Analytics ◽

Cloud Manufacturing ◽

Cyber Physical Systems ◽

Quality Of Services ◽

Content Type ◽

Physical Systems ◽

Security Issues

Purpose – The purpose of this paper is to review and explore the evolution, advances and future trends of cloud manufacturing, placing the focus on the quality of services. Moreover, moving toward the new trend of cyber-physical systems (CPS), a cloud-based cyber-physical system (CBCPS) is proposed combining the key enabling techniques of this decade, namely Internet of Things (IoT), cloud computing, Big Data analytics and CPS. Design/methodology/approach – First, an extensive review is made on cloud computing and its applications in manufacturing sectors, namely product development, manufacturing processes and manufacturing systems management. Second, a conceptual CBCPS which combines key enabling techniques including cloud computing, CPS and IoT is proposed. Finally, a review on the quality of the services (QoS) presented in the second step, along with the main security issues of cloud manufacturing, is conducted. Findings – The findings of this review indicate that the combination of the key enabling techniques presented in the CBCPS will lead to a new manufacturing paradigm capable of facing the new challenges and trends. The opportunities, as well as the challenges and barriers of the proposed framework are presented, concluding that the transition into this whole new era of networked computing and manufacturing has a valuable impact, but also generates several security and quality issues. Originality/value – The paper is the first to specifically study the QoS as a factor in the proposed manufacturing paradigm.

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Cyber-physical Systems as Part of Frugal Manufacturing Systems

Procedia CIRP ◽

10.1016/j.procir.2019.03.046 ◽

2019 ◽

Vol 81 ◽

pp. 264-269 ◽

Cited By ~ 4

Author(s):

Uwe Schleinkofer ◽

Kevin Klöpfer ◽

Marco Schneider ◽

Thomas Bauernhansl

Keyword(s):

Manufacturing Systems ◽

Cyber Physical Systems ◽

Physical Systems

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Orchestrated Platform for Cyber-Physical Systems

Complexity ◽

10.1155/2018/8281079 ◽

2018 ◽

Vol 2018 ◽

pp. 1-16 ◽

Cited By ~ 7

Author(s):

Róbert Lovas ◽

Attila Farkas ◽

Attila Csaba Marosi ◽

Sándor Ács ◽

József Kovács ◽

...

Keyword(s):

Sensor Networks ◽

Precision Agriculture ◽

Manufacturing Systems ◽

Driving Forces ◽

Discrete Event ◽

Cyber Physical Systems ◽

Sensor Data ◽

Simulation Tool ◽

Physical Systems ◽

Server Side

One of the main driving forces in the era of cyber-physical systems (CPSs) is the introduction of massive sensor networks (or nowadays various Internet of things solutions as well) into manufacturing processes, connected cars, precision agriculture, and so on. Therefore, large amounts of sensor data have to be ingested at the server side in order to generate and make the “twin digital model” or virtual factory of the existing physical processes for (among others) predictive simulation and scheduling purposes usable. In this paper, we focus on our ultimate goal, a novel software container-based approach with cloud agnostic orchestration facilities that enable the system operators in the industry to create and manage scalable, virtual IT platforms on-demand for these two typical major pillars of CPS: (1) server-side (i.e., back-end) framework for sensor networks and (2) configurable simulation tool for predicting the behavior of manufacturing systems. The paper discusses the scalability of the applied discrete-event simulation tool and the layered back-end framework starting from simple virtual machine-level to sophisticated multilevel autoscaling use case scenario. The presented achievements and evaluations leverage on (among others) the synergy of the existing EasySim simulator, our new CQueue software container manager, the continuously developed Occopus cloud orchestrator tool, and the latest version of the evolving MiCADO framework for integrating such tools into a unified platform.

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Healthy Operator 4.0: A Human Cyber–Physical System Architecture for Smart Workplaces

Sensors ◽

10.3390/s20072011 ◽

2020 ◽

Vol 20 (7) ◽

pp. 2011 ◽

Cited By ~ 5

Author(s):

Shengjing Sun ◽

Xiaochen Zheng ◽

Bing Gong ◽

Jorge García Paredes ◽

Joaquín Ordieres-Meré

Keyword(s):

System Architecture ◽

Manufacturing Systems ◽

Cyber Physical Systems ◽

Smart Manufacturing ◽

Prototype System ◽

Implementation Framework ◽

Widespread Application ◽

Physical Systems ◽

Enabling Technologies ◽

Smart Manufacturing Systems

Recent advances in technology have empowered the widespread application of cyber–physical systems in manufacturing and fostered the Industry 4.0 paradigm. In the factories of the future, it is possible that all items, including operators, will be equipped with integrated communication and data processing capabilities. Operators can become part of the smart manufacturing systems, and this fosters a paradigm shift from independent automated and human activities to human–cyber–physical systems (HCPSs). In this context, a Healthy Operator 4.0 (HO4.0) concept was proposed, based on a systemic view of the Industrial Internet of Things (IIoT) and wearable technology. For the implementation of this relatively new concept, we constructed a unified architecture to support the integration of different enabling technologies. We designed an implementation model to facilitate the practical application of this concept in industry. The main enabling technologies of the model are introduced afterward. In addition, a prototype system was developed, and relevant experiments were conducted to demonstrate the feasibility of the proposed system architecture and the implementation framework, as well as some of the derived benefits.

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Engineering of machine tools and manufacturing systems using cyber-physical systems

2017 Winter Simulation Conference (WSC) ◽

10.1109/wsc.2017.8247892 ◽

2017 ◽

Cited By ~ 4

Author(s):

Stefan Scheifele ◽

Oliver Riedel ◽

Gunter Pritschow

Keyword(s):

Machine Tools ◽

Manufacturing Systems ◽

Cyber Physical Systems ◽

Physical Systems

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Challenges of additive manufacturing in production systems

MATEC Web of Conferences ◽

10.1051/matecconf/201929901003 ◽

2019 ◽

Vol 299 ◽

pp. 01003

Author(s):

Angela Luft ◽

Andreas Gebhardt ◽

Nicolae Balc

Keyword(s):

Additive Manufacturing ◽

Cost Efficiency ◽

Manufacturing Systems ◽

Production Systems ◽

Cyber Physical Systems ◽

Current Approach ◽

Physical Systems ◽

Interdisciplinary Approaches ◽

Wide Adaptation ◽

Modern Manufacturing

Additive Manufacturing (AM) has become indispensable in the context of digitalization and Industry 4.0 and is said to be a mega trend of the 21st century. The technology offers immense opportunities to revolutionize the production of parts and components in all industries. Despite of the outstanding technical possibilities, the industry-wide adaptation rate is low. The current approach of looking at AM from a mostly technological view is a major reason for this. The challenge is to efficiently integrate 3D printing and other additive processes into existing manufacturing processes and systems. AM must be perceived as a multidimensional topic and viewed from different perspectives, two of which are the AM technology and the planning and management of production systems. These two perspectives have to be addressed simultaneously and cross-linked. In order to use AM to tackle some of the most challenging problems in modern manufacturing systems like increasing variant diversity, shorter product lifecycles, the demand for digitized processes and cyber-physical systems, it is necessary to develop interdisciplinary approaches and solutions, because none of the disciplines can reach the necessary performance and cost-efficiency alone.

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