scholarly journals Development of a Smart Cyber-Physical Manufacturing System in the Industry 4.0 Context

2019 ◽  
Vol 9 (16) ◽  
pp. 3325 ◽  
Author(s):  
Tran ◽  
Park ◽  
Nguyen ◽  
Hoang
Keyword(s):  
Radio Frequency Identification ◽  
Mass Production ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Shop Floor ◽  
Self Healing ◽  
Manufacturing Environment ◽  
Information And Communication ◽  
Ict Infrastructure

The complexity and dynamic of the manufacturing environment are growing due to the changes of manufacturing demand from mass production to mass customization that require variable product types, small lot sizes, and a short lead-time to market. Currently, the automatic manufacturing systems are suitable for mass production. To cope with the changes of the manufacturing environment, the paper proposes the model and technologies for developing a smart cyber-physical manufacturing system (Smart-CPMS). The transformation of the actual manufacturing systems to the Smart-CPMS is considered as the next generation of manufacturing development in Industry 4.0. The Smart-CPMS has advanced characteristics inspired from biology such as self-organization, self-diagnosis, and self-healing. These characteristics ensure that the Smart-CPMS is able to adapt with continuously changing manufacturing requirements. The model of Smart-CPMS is inherited from the organization of living systems in biology and nature. Consequently, in the Smart-CPMS, each resource on the shop floor such as machines, robots, transporters, and so on, is an autonomous entity, namely a cyber-physical system (CPS) which is equipped with cognitive capabilities such as perception, reasoning, learning, and cooperation. The Smart-CPMS adapts to the changes of manufacturing environment by the interaction among CPSs without external intervention. The CPS implementation uses the cognitive agent technology. Internet of things (IoT) with wireless networks, radio frequency identification (RFID), and sensor networks are used as information and communication technology (ICT) infrastructure for carrying out the Smart-CPMS.

scholarly journals SVM-Based Dynamic Reconfiguration CPS for Manufacturing System in Industry 4.0

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Hyun-Jun Shin ◽  
Kyoung-Woo Cho ◽  
Chang-Heon Oh
Keyword(s):  
Machine Learning ◽  
Industry 4.0 ◽  
Manufacturing System ◽  
Shop Floor ◽  
Learning Technology ◽  
Self Healing ◽  
Management Functions ◽  
Energy Transportation ◽  
Self Protection ◽  
Medical Healthcare

CPS is potential application in various fields, such as medical, healthcare, energy, transportation, and defense, as well as Industry 4.0 in Germany. Although studies on the equipment aging and prediction of problem have been done by combining CPS with Industry 4.0, such studies were based on small numbers and majority of the papers focused primarily on CPS methodology. Therefore, it is necessary to study active self-protection to enable self-management functions, such as self-healing by applying CPS in shop-floor. In this paper, we have proposed modeling of shop-floor and a dynamic reconfigurable CPS scheme that can predict the occurrence of anomalies and self-protection in the model. For this purpose, SVM was used as a machine learning technology and it was possible to restrain overloading in manufacturing process. In addition, we design CPS framework based on machine learning for Industry 4.0, simulate it, and perform. Simulation results show the simulation model autonomously detects the abnormal situation and it is dynamically reconfigured through self-healing.

An RFID-Driven Graphical Formalized Deduction for Describing the Time-Sensitive State and Position Changes of Work-in-Progress Material Flows in a Job-Shop Floor

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Pingyu Jiang ◽  
Wei Cao
Keyword(s):  
Radio Frequency Identification ◽  
Manufacturing Systems ◽  
Job Shop ◽  
Numerical Control ◽  
Shop Floor ◽  
Cnc Milling ◽  
Rfid Technology ◽  
Material Flows ◽  
Work In Progress ◽  
Frequency Identification

As a key advanced manufacturing technology in next generation manufacturing systems, radio frequency identification (RFID) technology is considered to be one of the most promising technological innovations with the potential to increase visibility and improve efficiency. Therefore, research about RFID and its applications are increasing by blasting with all kinds of RFID models in various fields, especially in manufacturing. By introducing RFID technology into the job-shop floor, this paper proposes a systematic RFID-driven graphical formalized deduction model (rfid-GFDM) for describing the time-sensitive state and position changes of work-in-progress (WIP) material flows and guiding where to deploy RFID devices and how to use them for collecting real-time on-site data. Four steps including RFID configuration based on the process flow model, state blocks model, automatic event generation, and extended event-driven model are proposed one by one to support the implementation of rfid-GFDM. The nature of RFID technology is revealed, too. A use case about a computer numerical control (CNC) milling system is studied, and it demonstrates the feasibility of the proposed model. Finally, the possibility of popularizing the model to other field is discussed, too. It is expected to establish a normative RFID modeling method that will facilitate the convenience of RFID applications in a broad scope.

scholarly journals Middleware Application, Suitable to Build an Automated and Connected Smart Manufacturing Environment

2021 ◽  
Author(s):  
Muzaffar Rao ◽  
Thomas Newe
Keyword(s):  
Mobile Robots ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Smart Manufacturing ◽  
Manufacturing Execution System ◽  
Manufacturing Environment ◽  
Industrial Internet ◽  
A Cell ◽  
Smart Industry ◽  
Manufacturing Execution

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.

A Digital Twin Concept for Manufacturing Systems

2018 ◽  
Author(s):  
Wesley Ellgass ◽  
Nathan Holt ◽  
Hector Saldana-Lemus ◽  
Julian Richmond ◽  
Ali Vatankhah Barenji ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Virtual Space ◽  
Smart Manufacturing ◽  
Shop Floor ◽  
Digital Twin ◽  
Physical Resources ◽  
Virtual Resources

With the developments and applications of the advanced information technologies such as cloud computing, internet of thing, artificial intelligence and virtual reality, industry 4.0 and smart manufacturing era are coming. In this respect, one of the specific challenges is to achieve a connection of physical resources on the shop floor with virtual resources, for real-time response, real time process optimization, and simulation, which is merged by big data problem. In this respect, Digital Twins (DT) concept is introduced as a key technology, which includes physical resources, virtual resources, service system, and digital twin data. DT considers current condition of physical resource and prediction of future events to make a responsive decision. However, due to the complexity of building a digital equivalent in virtual space to its physical counterpart, very little applications have been developed with this purpose, especially in the industrial manufacturing area. Therefore, the types of data and technology required to build the DT for a manufacturing system are presented in this work, trying to develop a framework of DT based manufacturing system, which is supported by the virtual reality for virtualization of physical resources.

scholarly journals Cooperative Product Agents to Improve Manufacturing System Flexibility: A Model-Based Decision Framework

2021 ◽  
Author(s):  
Ilya Kovalenko ◽  
Efe Balta ◽  
Dawn Tilbury ◽  
Kira Barton
Keyword(s):  
Decision Making ◽  
Control Strategy ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Timed Automata ◽  
Shop Floor ◽  
Intelligent Software ◽  
Multi Agent ◽  
Agent Control ◽  
And Performance

Due to the advancements in manufacturing system technology and the ever-increasing demand for personalized products, there is a growing desire to improve the flexibility of manufacturing systems. Multi-agent control is one strategy that has been proposed to address this challenge. The multi-agent control strategy relies on the decision making and cooperation of a number of intelligent software agents to control and coordinate various components on the shop floor. One of the most important agents for this control strategy is the product agent, which is the decision maker for a single part in the manufacturing system. To improve the flexibility and adaptability of the product agent and its control strategy, this work proposes a direct and active cooperation framework for the product agent. The directly and actively cooperating product agent can identify and actively negotiate scheduling constraints with other agents in the system. A new modeling formalism, based on priced timed automata, and an optimization-based decision making strategy are proposed as part of the framework. Two simulation case studies showcase how direct and active cooperation can be used to improve the flexibility and performance of manufacturing systems.

scholarly journals Cooperative Product Agents to Improve Manufacturing System Flexibility: A Model-Based Decision Framework

2021 ◽  
Author(s):  
Ilya Kovalenko ◽  
Efe Balta ◽  
Dawn Tilbury ◽  
Kira Barton
Keyword(s):  
Decision Making ◽  
Control Strategy ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Timed Automata ◽  
Shop Floor ◽  
Intelligent Software ◽  
Multi Agent ◽  
Agent Control ◽  
And Performance

Due to the advancements in manufacturing system technology and the ever-increasing demand for personalized products, there is a growing desire to improve the flexibility of manufacturing systems. Multi-agent control is one strategy that has been proposed to address this challenge. The multi-agent control strategy relies on the decision making and cooperation of a number of intelligent software agents to control and coordinate various components on the shop floor. One of the most important agents for this control strategy is the product agent, which is the decision maker for a single part in the manufacturing system. To improve the flexibility and adaptability of the product agent and its control strategy, this work proposes a direct and active cooperation framework for the product agent. The directly and actively cooperating product agent can identify and actively negotiate scheduling constraints with other agents in the system. A new modeling formalism, based on priced timed automata, and an optimization-based decision making strategy are proposed as part of the framework. Two simulation case studies showcase how direct and active cooperation can be used to improve the flexibility and performance of manufacturing systems.

Special Issue on Intelligent Manufacturing Systems

1994 ◽  
Vol 6 (6) ◽  
pp. 441-441
Author(s):  
Yoshio Mizugaki
Keyword(s):  
International Trade ◽  
Mass Production ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Intelligent Manufacturing ◽  
Manufacturing Industries ◽  
Special Issue ◽  
Production Engineering ◽  
New Paradigm ◽  
Intelligent Manufacturing Systems

Production engineering and manufacturing industries face difficulties in developing a new paradigm to cope with the post mass-production era. Consumers' preferences change very quickly and vary over a wide range of taste. A product's life cycle becomes shorter than shorter. Thus, rapid prototyping techniques have been requested, and some new concepts on manufacturing have been presented including Flexible Manufacturing System, Factory (or Flexible) Automation, Computer Integrated Manufacturing System, and Concurrent Engineering. After the termination of the cold war, many regional economies combined through international trade and dynamically evolved into global economies. Such change had significant effects on manufacturing industries and consequently on production engineering. As a new paradigm in the post mass-production era, the creation of manufacturing culture has been advocated by Prof. Hiroyuki Yoshikawa, President of University of Tokyo. It contains not only the movement towards standardization of conventional manufacturing knowledge but also the development of a global manufacturing system with use of computerization. At his advocation, the international research project of Intelligent Manufacturing Systems (IMS) was initiated. This bimonthly journal is a special issue on the IMS project and similar topics widely covering intelligent manufacturing systems. The former part of the contents is the description of the IMS project. It consists of the commentary articles quoted from the IMS news and the latest reports of IMS international test cases. The Japan IMS center publishes the IMS news and strongly supports the IMS project itself with collaboration of Ministry of International Trade and Industry of Japan (MITI). The authors of these reports are primarily enrolled in the actual responsibility to promote their projects and newly write the articles for this journal. I would like to thank the IMS center and each author for their contributions to this special issue on the IMS project. The latter part of the contents consists of the articles on the STandard for the Exchange of Product model data (STEP) and some technical papers on manufacturing. A conference report on the 2nd Japan-France Congress on Mechatronics is also provided in this issue. I would like to thank all contributors for their cooperation in creating this special issue. As can be easily seen, this issue focused on the forthcoming advancement on production engineering and manufacturing through the movement of Intelligent Manufacturing Systems. As the editor of this special issue on Intelligent Manufacturing Systems, I hope that the readers pay attention to this new movement and become involved in the near future.

An Intelligent Manufacturing System Based on WSN and RFID in Industrial Plants

2014 ◽  
Vol 513-517 ◽  
pp. 1256-1260 ◽  
Author(s):  
Zhong Wei Cui ◽  
Yong Zhao ◽  
Hui Yuan
Keyword(s):  
Radio Frequency Identification ◽  
Communication Systems ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Performance Testing ◽  
Intelligent Manufacturing ◽  
Industrial Plants ◽  
Intelligent Manufacturing System ◽  
Frequency Identification ◽  
Real Time Information

The intelligent manufacturing systems are in networked framework via a variety of networking communication systems integrating the heterogeneous collections of manufacturing worker, material, devices and real-time information. This paper presents a intelligent manufacturing system that is implemented by Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN). The system monitors and controls with the clear objective of maximizing the Quality of Service (QoS) provided by the manufacturing resources and to analyze and make decision. This study describes the design and implementation of the system developed as well as performance testing and evaluation results, in terms of system transmission delay and energy consumption.

scholarly journals Developing of Industry 4.0 Applications

2017 ◽  
Vol 13 (10) ◽  
pp. 30 ◽  
Author(s):  
Juan David Contreras ◽  
Jose Isidro Garcia ◽  
Juan David Diaz
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Industrial Revolution ◽  
Intelligent Manufacturing ◽  
Reference Architecture ◽  
Physical Systems ◽  
Architecture Model ◽  
Smart Factories ◽  
Correct Implementation

<p class="0papertitle">The fourth industrial revolution or industry 4.0 has become a trend topic nowadays, this standard-based strategy integrates Smart Factories, Cyber-physical systems, Internet of Things, and Internet of Service with the aim of extended the capacities of the manufacturing systems. Although several authors have presented the advantages of this approach, few papers refer to an architecture that allows the correct implementation of industry 4.0 applications using the guidelines of the reference architecture model (RAMI 4.0). In this way, this article exposes the essential characteristics that allow a manufacturing system to be retrofitting as a correct industry 4.0 application. Specifically, an intelligent manufacturing system under a holonic approach was developed and implemented using standards like FDI, AutomationML and OPC UA according to the RAMI 4.0</p>

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