scholarly journals IO-Link Wireless enhanced factory automation communication for Industry 4.0 applications

2018 ◽  
Vol 7 (1) ◽  
pp. 131-142 ◽  
Author(s):  
Ralf Heynicke ◽  
Dmytro Krush ◽  
Christoph Cammin ◽  
Gerd Scholl ◽  
Bernd Kaercher ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Control Level ◽  
Vital Role ◽  
Added Value ◽  
Cycle Times ◽  
Wireless Testing ◽  
Coexistence Mechanisms ◽  
Cyber Physical Production Systems

Abstract. In the context of the Industry 4.0 initiative, Cyber-Physical Production Systems (CPPS) or Cyber Manufacturing Systems (CMS) can be characterized as advanced networked mechatronic production systems gaining their added value by interaction with the ambient Industrial Internet of Things (IIoT). In this context appropriate communication technologies and standards play a vital role to realize the manifold potential improvements in the production process. One of these standards is IO-Link. In 2016 more than 5 million IO-Link nodes have been produced and delivered, still gaining increasing acceptance for the communication between sensors, actuators and the control level. The steadily increasing demand for more flexibility in automation solutions can be fulfilled using wireless technologies. With the wireless extension for the IO-Link standard, which will be presented in this article, maximum cycle times of 5 ms can be achieved with a probability that this limit will be exceeded to be at maximum one part per billion. Also roaming capabilities, wireless coexistence mechanisms and the possibility to include battery-powered or energy-harvesting sensors with very limited energy resources in the realtime network were defined. For system planning, setup, operation and maintenance, the standard engineering tools of IO-Link can be employed so that the backward compatibility with wired IO-Link solutions can be guaranteed. Interoperability between manufacturers is a key requirement for any communication standard, thus a procedure for IO-Link Wireless testing is also suggested.

scholarly journals Challenges of Digital Twin System

2019 ◽  
Vol 12 (3) ◽  
pp. 252-267
Author(s):  
Cristina Rosaria Monsone ◽  
János Jósvai
Keyword(s):  
Industry 4.0 ◽  
Production Systems ◽  
Communication Technologies ◽  
Vital Role ◽  
Manufacturing Processes ◽  
Assembly Systems ◽  
Twin System ◽  
Cyber Physical Production Systems ◽  
Learning Analysis ◽  
Manufacturing Science

Today’s manufacturing and assembly systems have to be flexible to adapt quickly to an increasing number and variety of products. The Industry 4.0 conceptualization has several potentials, i.e. flexibility in business and manufacturing processes, where the intelligent and interconnected systems, in particular the Cyber-Physical Production System (CPPS), play a vital role in the whole lifecycle of eco-designed products. In particular, the CPPS represents a suitable way for manufacturers that want to involve their customers, delivering instructions to machines about their specific orders and follow its progress along the production line, in an inversion of normal manufacturing. The development of Info Communication Technologies (ICT) and Manufacturing Science and Technology (MST) enables the innovation of Cyber-Physical Production Systems. However, there are still important challenges that need to be addressed in particular at technological and data analysis level with the implementation of Deep Learning analysis.

scholarly journals Coordination in the age of Industry 4.0: The case of blockchain

2019 ◽  
Vol 52 (3) ◽  
pp. 56-64
Author(s):  
Lesław Pietrewicz
Keyword(s):  
Information And Communication Technologies ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Communication Technologies ◽  
Coordination Mechanism ◽  
Physical Systems ◽  
Challenging Research ◽  
Information And Communication ◽  
Cyber Physical Production Systems

The topic of coordination arises whenever various tasks or resources must be employed together to produce desirable outcomes. Whereas the complexity of tasks and interactions needed to produce results increase coordination needs, advances in information and communication technologies (ICT) dramatically improve its possibilities. Vertically and horizontally integrated Industry 4.0 manufacturing systems, using ICT to interact with and expand the capabilities of the physical systems, both demand enhanced coordination within and between organizations, and are themselves designed to foster coordination, making coordination in the age of Industry 4.0 a particularly timely and challenging research topic. The paper contributes to the emerging stream of literature on coordination in the age of Industry 4.0 by analyzing the characteristics of blockchain as a coordination mechanism and its application to the hybrid cyber-physical production systems.

One-of-a-kind Production in Cyber-Physical Production Systems Considering Machine Failures

2021 ◽  
pp. 1-20
Author(s):  
Guido Vinci Carlavan ◽  
Daniel Alejandro Rossit
Keyword(s):  
Industry 4.0 ◽  
Information Technologies ◽  
Job Shop ◽  
Production Systems ◽  
Dispatching Rules ◽  
Shop Floor ◽  
Due Dates ◽  
Efficient Manner ◽  
Large Variability ◽  
Cyber Physical Production Systems

Industry 4.0 proposes the incorporation of information technologies at all levels of the production process. By incorporating these technologies, Industry 4.0 provides new tools for production planning processes, allowing to address problems in an innovative and efficient manner. From these technologies and tools, it is that in this work a One-of-a-Kind Production (OKP) process is approached, where the products tend to be highly customized. OKP implies working with a very large variability within production, demanding very efficient planning systems. For this, a planning model based on CONWIP-type strategies was proposed, which seeks to level the production of a shop floor configured in the form of a job shop. Even more, for having a more realistic shop-floor representation, machine failures have been included in the model. In turn, different dispatching rules were proposed to study the performance and analyze the behaviour of the system. From the results obtained, it is observed that, when the production demand is very exigent in relation with the capacity of the system, the dispatching rules that analyze the workload generated by each job tend to perform better. However, when the demand on the capacity of the production system is less intense, the rules associated with due dates are the ones that obtain the best results.

scholarly journals Simulation von Cyber-Physischen Produktionssystemen in einer Forschungsinfrastruktur

2020 ◽  
Author(s):  
Iris Gräßler
Keyword(s):  
Communication Technology ◽  
Information Acquisition ◽  
Industry 4.0 ◽  
Production Control ◽  
Production Systems ◽  
General Concept ◽  
Radio Network ◽  
Systems Research ◽  
Digital Twins ◽  
Cyber Physical Production Systems

The article describes the setup of an experimentation and validation environment by extending a production laboratory: All relevant elements of the production laboratory were equipped with computer systems, so-called "industry 4.0 boxes", and interconnected via a peer-to-peer radio network. The "industry 4.0 boxes" are used to upgrade dedicated sensors for recording machine behaviour and communication technology to be integrated into decentralized production control. In addition, digital twins were implemented to map machine and user behaviour, enable control and support information acquisition and processing. Thereby, a research infrastructure is created for research on potentials of cyber-physical production systems. Research outcomes will be used as a decision basis for companies and for validation of production optimizations. This paper describes the concept and implementation of industry 4.0 functionalities and derives a general concept of simulation platforms for CPPS.

scholarly journals QHAR: Q-Holonic-Based ARchitecture for Self-Configuration of Cyber–Physical Production Systems

2021 ◽  
Vol 11 (19) ◽  
pp. 9013
Author(s):  
Douha Macherki ◽  
Thierno M. L. Diallo ◽  
Jean-Yves Choley ◽  
Amir Guizani ◽  
Maher Barkallah ◽  
...  
Keyword(s):  
Decentralized Control ◽  
System Performance ◽  
Production Systems ◽  
Control Level ◽  
Centralized Control ◽  
Four Dimensions ◽  
Potential Capacity ◽  
Heterarchical Control ◽  
Cyber Physical Production Systems

Production systems must be able to adapt to increasingly frequent internal and external changes. Cyber-Physical Production Systems (CPPS), thanks to their potential capacity for self-reconfiguration, can cope with this need for adaptation. To implement the self-reconfiguration functionality in economical and safe conditions, CPPS must have appropriate tools and contextualized information. This information can be organized in the form of an architecture. In this paper, after the analysis of several holonic and nonholonic architectures, we propose a holonic architecture that allows for reliable and efficient reconfiguration. We call this architecture QHAR (Q-Holonic-based ARchitecture). QHAR is constructed based on the idea of a Q-holon, which has four dimensions (physical, cyber, human, and energy) and can exchange three flows (energy, data, and materials). It is a generic Holon that can represent any entity or actor of the supply chain. The QHAR is structured in three levels: centralized control level, decentralized control level, and execution level. QHAR implements the principle of an oligarchical control architecture by deploying both hierarchical and heterarchical control approaches. This ensures the overall system performance and reactivity to hazards. The proposed architecture is tested and validated on a case study.

Integration of Cutting-Edge Interoperability Approaches in Cyber-Physical Production Systems and Industry 4.0

2021 ◽  
pp. 144-172
Author(s):  
Luis Alberto Estrada-Jimenez ◽  
Terrin Pulikottil ◽  
Nguyen Ngoc Hien ◽  
Agajan Torayev ◽  
Hamood Ur Rehman ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Production Systems ◽  
Heterogeneous Systems ◽  
Smart Manufacturing ◽  
Use Case ◽  
Integrative Framework ◽  
Data Formats ◽  
Exchange Information ◽  
Cyber Physical Production Systems ◽  
Physical Components

Interoperability in smart manufacturing refers to how interconnected cyber-physical components exchange information and interact. This is still an exploratory topic, and despite the increasing number of applications, many challenges remain open. This chapter presents an integrative framework to understand common practices, concepts, and technologies used in trending research to achieve interoperability in production systems. The chapter starts with the question of what interoperability is and provides an alternative answer based on influential works in the field, followed by the presentation of important reference models and their relation to smart manufacturing. It continues by discussing different types of interoperability, data formats, and common ontologies necessary for the integration of heterogeneous systems and the contribution of emerging technologies in achieving interoperability. This chapter ends with a discussion of a recent use case and final remarks.

scholarly journals Energy Efficiency in Industry 4.0: The Case of Batch Production Processes

2020 ◽  
Vol 12 (16) ◽  
pp. 6631 ◽  
Author(s):  
Giancarlo Nota ◽  
Francesco David Nota ◽  
Domenico Peluso ◽  
Alonso Toro Lazo
Keyword(s):  
Energy Consumption ◽  
Industry 4.0 ◽  
Production Systems ◽  
Decision Makers ◽  
Batch Processes ◽  
Energy Losses ◽  
Manufacturing Processes ◽  
Batch Production ◽  
Production Processes ◽  
Cyber Physical Production Systems

We derived a promising approach to reducing the energy consumption necessary in manufacturing processes from the combination of management methodologies and Industry 4.0 technologies. Based on a literature review and experts’ opinions, this work contributes to the efficient use of energy in batch production processes combining the analysis of the overall equipment effectiveness with the study of variables managed by cyber-physical production systems. Starting from the analysis of loss cause identification, we propose a method that obtains quantitative data about energy losses during the execution of batch processes. The contributions of this research include the acquisition of precise information about energy losses and the improvement of value co-creation practices so that energy consumption can be reduced in manufacturing processes. Decision-makers can use the findings to start a virtuous process aiming at carbon footprint and energy costs reductions while ensuring production goals are met.

Proposal of an Architecture based on RAMI 4.0 Layers for Flexible Manufacturing in Industry 4.0

2020 ◽  
Author(s):  
José Z. Neto ◽  
Joel Ravelli Jr ◽  
Eduardo P. Godoy
Keyword(s):  
Flexible Manufacturing ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Three Dimensional ◽  
Reference Architecture ◽  
Architecture Model ◽  
Industrial Internet ◽  
Integration Architecture ◽  
Rapid Changes

The Industry 4.0 (I4.0) together with the Industrial Internet of Things (IIoT) enable business productivity to be improved through rapid changes in production scope in an increasingly volatile market. This technology innovation is perceived by integrating manufacturing systems, managing business rules, and decentralizing computing resources, enabling rapid changes in production systems. The Reference Architecture Model for Industry 4.0 (RAMI 4.0) is a three-dimensional layer model to support I4.0 applications. One of the major challenges for adopting RAMI 4.0 is the development of solutions that support the functionality of each layer and the necessary interactions between the elements of each layer. This paper focuses on the proposal of architecture for flexible manufacturing in I4.0 using all the Information Technology (IT) Layers of the RAMI 4.0. In order to enable a standardized and interoperable communication, the architecture used the OPC-UA protocol to connect the low layers elements in the factory perspective and REST APIs to connect the high layers in the business perspective. The integration architecture creates an online interface to provide the client the ability to enter, view, and even modify an order based on their needs and priorities, enabling the industry to implement rapid changes to adapt to the marketplace.

scholarly journals TEACHING NETWORK TECHNOLOGIES THAT SUPPORT INDUSTRY 4.0

2015 ◽  
Author(s):  
Ishwar Singh ◽  
Nafia Al-Mutawaly ◽  
Tom Wanyama
Keyword(s):  
Industry 4.0 ◽  
Production Systems ◽  
Manufacturing Plants ◽  
Electrical Grid ◽  
Distributed Intelligence ◽  
Industrial Networks ◽  
Manufacturing Competitiveness ◽  
Manufacturing Productivity ◽  
Cyber Physical Production Systems ◽  
Network Technologies

Industry 4.0 is a combination of many elements, including distributed intelligence, network security, massive data, cloud computing, and analytics, among other things. Such elements are critical to the “Digital Factory”, a term that has been recently introduced by many companies indicating a comprehensive portfolio of seamlessly integrated hardware, software and technology-based services, with the aim to enhance manufacturing productivity and improving efficiency. Typically, industrial networks enable the gathering of extensive data from productionlines and plants, which are increasingly becoming distributed. The gathered data is transmitted to analysis centers where it is transformed into information and used to make better informed decisions. In addition, modern industrial networks allow plant data to be automatically filtered and transmitted to various production controllers. Ultimately, industrial networks enable Industry 4.0 to have the following benefits: improved safety, increase uptime, lower energy costs, and improved maintenance;all of which lead to manufacturing competitiveness in cyber-physical production systems supported by Smart Grid implementations. This paper presents the extent to which industrial networks are taught at the School ofEngineering Technology at McMaster University. Further, the paper covers teaching methods of industrial networks and their related applications within manufacturing plants and electrical grid.

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