scholarly journals Economic, Social Impacts and Operation of Smart Factories in Industry 4.0 Focusing on Simulation and Artificial Intelligence of Collaborating Robots

2019 ◽  
Vol 8 (5) ◽  
pp. 143 ◽  
Author(s):  
Rabab Benotsmane ◽  
György Kovács ◽  
László Dudás
Keyword(s):  
Artificial Intelligence ◽  
Industry 4.0 ◽  
Optimal Operation ◽  
Added Value ◽  
Smart Factory ◽  
Motion Path ◽  
Robot Arm ◽  
Quantitative Research Methods ◽  
Smart Factories

Smart Factory is a complex system that integrates the main elements of the Industry 4.0 concept (e.g., autonomous robots, Internet of Things, and Big data). In Smart Factories intelligent robots, tools, and smart workpieces communicate and collaborate with each other continuously, which results in self-organizing and self-optimizing production. The significance of Smart Factories is to make production more competitive, efficient, flexible and sustainable. The purpose of the study is not only the introduction of the concept and operation of the Smart Factories, but at the same time to show the application of Simulation and Artificial Intelligence (AI) methods in practice. The significance of the study is that the economic and social operational requirements and impacts of Smart Factories are summarized and the characteristics of the traditional factory and the Smart Factory are compared. The most significant added value of the research is that a real case study is introduced for Simulation of the operation of two collaborating robots applying AI. Quantitative research methods are used, such as numerical and graphical modeling and Simulation, 3D design, furthermore executing Tabu Search in the space of trajectories, but in some aspects the work included fundamental methods, like suggesting an original whip-lashing analog for designing robot trajectories. The conclusion of the case study is that—due to using Simulation and AI methods—the motion path of the robot arm is improved, resulting in more than five percent time-savings, which leads to a significant improvement in productivity. It can be concluded that the establishment of Smart Factories will be essential in the future and the application of Simulation and AI methods for collaborating robots are needed for efficient and optimal operation of production processes.

scholarly journals Tecnologías de Mantenimiento industrial en la industria 4.0

2019 ◽  
pp. 20-24
Author(s):  
Manuel Meraz-Méndez ◽  
Claudia Lerma-Hernández
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Teaching Practices ◽  
Industry 4.0 ◽  
Digital Technologies ◽  
Industrial Maintenance ◽  
Technological University ◽  
Engineering Career ◽  
Smart Factories ◽  
Technical Area

Industry 4.0 is the incorporation of digital technologies in factories such as: artificial intelligence, machine learning, 3D printing, drones, robotics, IOT, big data, virtual reality, automation, among others, which aim to digitalize processes productive in the factories, these are also called smart factories. The objective of this article is to identify the technologies applicable to industrial maintenance in Industry 4.0, the final result of this research determine the teaching practices that must be carried out in the Industrial Maintenance Engineering career at the Technological University of Chihuahua, and how the students must be prepared with the competences and skills necessary to face this challenge, at the same time the new teaching practices and strategies that a teacher in the technical area of Industrial Maintenance must apply in laboratory practices with a focus on Industry 4.0.

scholarly journals An improved cyber-physical systems architecture for Industry 4.0 smart factories

2018 ◽  
Vol 10 (6) ◽  
pp. 168781401878419 ◽  
Author(s):  
Jehn-Ruey Jiang
Keyword(s):  
Vertical Integration ◽  
Physical System ◽  
Industry 4.0 ◽  
Smart Factory ◽  
Cyber Physical System ◽  
Industrial Internet Of Things ◽  
Systems Architecture ◽  
Physical Systems ◽  
Industrial Internet ◽  
Smart Factories

The cyber-physical system is the core concept of Industry 4.0 for building smart factories. We can rely on the ISA-95 architecture or the 5C architecture to build the cyber-physical system for smart factories. However, both architectures emphasize more on vertical integration and less on horizontal integration. This article proposes the 8C architecture by adding 3C facets into the 5C architecture. The 3C facets are coalition, customer, and content. The proposed 8C architecture is a helpful guideline to build the cyber-physical system for smart factories. We show an example of designing and developing, on the basis of the proposed 8C architecture, a smart factory cyber-physical system, including an Industrial Internet of Things gateway and a smart factory data center running in the cloud environment.

scholarly journals La industria 4.0 en el mantenimiento industrial

2019 ◽  
pp. 17-24
Author(s):  
Manuel Meraz-Mendez ◽  
Claudia Lerma-Hernández ◽  
Guadalupe Corral-Ramírez
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Teaching Practices ◽  
Industry 4.0 ◽  
Digital Technologies ◽  
Industrial Maintenance ◽  
Technological University ◽  
Engineering Career ◽  
Smart Factories ◽  
Technical Area

Industry 4.0 is the incorporation of digital technologies in factories such as: artificial intelligence, machine learning, 3D printing, drones, robotics, IOT, big data, virtual reality, automation, among others, which aim to digitalize processes productive in the factories, these are also called smart factories. The objective of this article is to identify the technologies applicable to industrial maintenance in Industry 4.0, the final result of this research determine the teaching practices that must be carried out in the Industrial Maintenance Engineering career at the Technological University of Chihuahua, and how the students must be prepared with the competences and skills necessary to face this challenge, at the same time the new teaching practices and strategies that a teacher in the technical area of Industrial Maintenance must apply in laboratory practices with a focus on Industry 4.0.

Semantische Kommunikationsschnittstellen zur Zustandsüberwachung im Karosseriebau/Standardised I4.0 communication interfaces – Requirements and measures to establish I4.0 principles in modern production systems

2016 ◽  
Vol 106 (10) ◽  
pp. 699-704
Author(s):  
H. Fleischmann ◽  
J. Kohl ◽  
A. Blank ◽  
M. Schacht ◽  
J. Fuchs ◽  
...  
Keyword(s):  
Communication Networks ◽  
Industry 4.0 ◽  
Production Systems ◽  
Industrie 4.0 ◽  
Efficient Implementation ◽  
Smart Factory ◽  
Vehicle Body ◽  
Body Construction ◽  
Semantic Communication ◽  
Smart Factories

Industrie 4.0-Technologie verspricht Unterstützung bei der Erfüllung komplexer Produktionsaufgaben. Bisher verhindern jedoch historisch gewachsene, industrielle Kommunikationsnetze durch die oft wenig semantische, strikte Kommunikation entlang der bestehenden Ebenen der Automatisierungspyramide eine effiziente Umsetzung der Prinzipien von „Smart Factories“. Diese Veröffentlichung thematisiert die Entwicklung semantischer Kommunikationsschnittstellen am Beispiel des Karosseriebaus der Audi AG.   Industry 4.0 technology promises to support the fulfillment of complex production tasks. Even today, historically grown industrial communication networks prevent an efficient implementation of smart factory principles, especially due to a lack of semantics and the strict communication along the existing layers of the automation pyramid. This publication focuses on the development of semantic communication interfaces using the example of the digitalization of the vehicle body construction at the Audi AG.

scholarly journals Trajectory Optimization of Industrial Robot Arms Using a Newly Elaborated “Whip-Lashing” Method

2020 ◽  
Vol 10 (23) ◽  
pp. 8666
Author(s):  
Rabab Benotsmane ◽  
László Dudás ◽  
György Kovács
Keyword(s):  
Trajectory Optimization ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Added Value ◽  
Robot Arm ◽  
Manufacturing Companies ◽  
Time Saving ◽  
Cycle Times ◽  
Robot Arms

The application of the Industry 4.0′s elements—e.g., industrial robots—has a key role in the efficiency improvement of manufacturing companies. In order to reduce cycle times and increase productivity, the trajectory optimization of robot arms is essential. The purpose of the study is the elaboration of a new “whip-lashing” method, which, based on the motion of a robot arm, is similar to the motion of a whip. It results in achieving the optimized trajectory of the robot arms in order to increase velocity of the robot arm’s parts, thereby minimizing motion cycle times and to utilize the torque of the joints more effectively. The efficiency of the method was confirmed by a case study, which is relating to the trajectory planning of a five-degree-of-freedom RV-2AJ manipulator arm using SolidWorks and MATLAB software applications. The robot was modelled and two trajectories were created: the original path and path investigate the effects of using the whip-lashing induced robot motion. The application of the method’s algorithm resulted in a cycle time saving of 33% compared to the original path of RV-2AJ robot arm. The main added value of the study is the elaboration and implementation of the newly elaborated “whip-lashing” method which results in minimization of torque consumed; furthermore, there was a reduction of cycle times of manipulator arms’ motion, thus increasing the productivity significantly. The efficiency of the new “whip-lashing” method was confirmed by a simulation case study.

scholarly journals Conception of Logistics Management System for Smart Factory

2018 ◽  
Vol 7 (4.27) ◽  
pp. 126 ◽  
Author(s):  
Zhen Quan Chong ◽  
Cheng Yee Low ◽  
Ubaidullah Mohammad ◽  
Ramhuzaini Abd Rahman ◽  
Mohd Saiful Bahari Shaari
Keyword(s):  
Management System ◽  
Industry 4.0 ◽  
Logistics Management ◽  
Smart Factory ◽  
Logistics System ◽  
Related Data ◽  
Smart Logistics ◽  
Logistic Management ◽  
Logistics Management System ◽  
Smart Factories

An interconnected, data driven smart logistics management system is crucial in a smart factory in context of Industry 4.0. Applying the concept of cyber-physical systems (CPSs) and Internet of Things (IoT) will create a standardized logistics system. This system can be applied across the supply chain to enable the sharing of information in real-time which consequently optimize logistics processes. In this project, a conceptual model of a smart logistics management system between a supplier and a manufacturer using NFC smart tags technology is developed and its application is shown using prototype demonstrator. The system is equipped with functions to monitor and manage logistic related data. The interface is built using windows form application and android phone application. The developed model’s abilities and specifications in context of industry 4.0 is evaluated using the VDMA Toolbox Industry 4.0. In the end this system achieved an average of level 4 in the Industry 4.0 evaluation and this system provides a concept on applying a smart logistic management system for manufacturers as a key step in transforming into smart factories.  

Automation 4.0

2021 ◽  
pp. 29-49
Author(s):  
Craig Eric Seidelson
Keyword(s):  
Artificial Intelligence ◽  
Industry 4.0 ◽  
Industrial Robots ◽  
The Other ◽  
Intelligent Machines ◽  
Level Of Automation ◽  
Other Hand ◽  
The World ◽  
The One ◽  
Smart Factories

Factories have employed automation for nearly 100 years. With the launch of Industry 4.0 in 2011, operations have expanded their use of robots on an unprecedented scale. As of 2017, there were roughly 2 million industrial robots in use globally. By 2030, it's estimated that 20 million manufacturing jobs around the world could be replaced by robots. Yet, substantial hurdles remain before predicted level of automation can be realized. On the one hand, smart factories are almost exclusively multibillion-dollar enterprises. Their costs are simply too high for most manufacturers. On the other hand, intelligent machines are limited in what they can do because so many of the engineering tasks required to support them are still being done by people. Widespread use of automation requires expanding the use of artificial intelligence to manage data, create drawings, evaluate designs, and program machines.

MANUFACTURING PROCESSES TRANSFORMATION IN AERONAUTICAL SECTOR IN AN INDUSTRY 4.0 CONTEXT

10.6036/9938 ◽  
2021 ◽  
Vol 96 (3) ◽  
pp. 233-234
Author(s):  
LEANDRO RUIZ ◽  
MANUEL TORRES ◽  
ALEJANDRO GOMEZ VILANOVA ◽  
SEBASTIAN DIAZ DIAZ ◽  
FRANCISCO CAVAS MARTINEZ
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Industry 4.0 ◽  
Added Value ◽  
Manufacturing Processes ◽  
Production Chain ◽  
High Productivity ◽  
Robotic Cells ◽  
Major Transformation ◽  
The Creation

Adoption by the aeronautical sector of developments and technologies of the so-called Industry 4.0 is a major transformation, due to the added value that these new processes bring to the production chain. It is in this context, in which the relevance of the digitalization and automation of all manufacturing processes is observed, with the increasingly widespread implantation of robotic cells and other technologies such as systems of vision and artificial intelligence, will lead to a new digital scenario that will allow the creation in real time of reconfigurable and sustainable spaces with high productivity and reliability.

scholarly journals Advances in Sensor Technologies in the Era of Smart Factory and Industry 4.0

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6783
Author(s):  
Tahera Kalsoom ◽  
Naeem Ramzan ◽  
Shehzad Ahmed ◽  
Masood Ur-Rehman
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Low Cost ◽  
Intelligent Manufacturing ◽  
Smart Factory ◽  
Future Research ◽  
Manufacturing Processes ◽  
Manufacturing Companies ◽  
Different Types ◽  
Smart Factories

The evolution of intelligent manufacturing has had a profound and lasting effect on the future of global manufacturing. Industry 4.0 based smart factories merge physical and cyber technologies, making the involved technologies more intricate and accurate; improving the performance, quality, controllability, management, and transparency of manufacturing processes in the era of the internet-of-things (IoT). Advanced low-cost sensor technologies are essential for gathering data and utilizing it for effective performance by manufacturing companies and supply chains. Different types of low power/low cost sensors allow for greatly expanded data collection on different devices across the manufacturing processes. While a lot of research has been carried out with a focus on analyzing the performance, processes, and implementation of smart factories, most firms still lack in-depth insight into the difference between traditional and smart factory systems, as well as the wide set of different sensor technologies associated with Industry 4.0. This paper identifies the different available sensor technologies of Industry 4.0, and identifies the differences between traditional and smart factories. In addition, this paper reviews existing research that has been done on the smart factory; and therefore provides a broad overview of the extant literature on smart factories, summarizes the variations between traditional and smart factories, outlines different types of sensors used in a smart factory, and creates an agenda for future research that encompasses the vigorous evolution of Industry 4.0 based smart factories.

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