Global Trend of Implementation of Industrial Robots Relating to Industry 4.0

2020 ◽  
pp. 147-155
Author(s):  
Isak Karabegović ◽  
Raul Turmanidze ◽  
Predrag Dašić
Keyword(s):  
Industry 4.0 ◽  
Industrial Robots ◽  
Global Trend

scholarly journals Transitioning of Steel Producers to the Steelworks 4.0 –Literature Review with Case Studies

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4109
Author(s):  
Bożena Gajdzik ◽  
Radosław Wolniak
Keyword(s):  
Literature Review ◽  
Case Studies ◽  
Steel Industry ◽  
Industry 4.0 ◽  
Strong Dependence ◽  
Industrial Robots ◽  
Basic Material ◽  
Sources Of Information ◽  
Important Place ◽  
Steel Mills

The publication presents a picture of modern steelworks that is evolving from steelworks 3.0 to steelworks 4.0. The paper was created on the basis of secondary sources of information (desk research). The entire publication concerns the emerging opportunities for the development of the steel producers to Industry 4.0 and the changes already implemented in the steel plants. The collected information shows the support environment for changes in the steel sector (EU programs), the levels of evolution of steel mills, along with the areas of change in the steel industry and implemented investment projects. The work consists of a theoretical part based on a literature review and a practical part based on case studies. The work ends with a discussion in which the staged and segmented nature of the changes introduced in the analyzed sector is emphasized. Based on the three case studies described in the paper, a comparative analysis was conducted between them. When we tried to compare methods used in the three analyzed steel producers (capital groups): ArcelorMittal, Thyssenkrupp, and Tata Steel Group, it can be seen that in all organizations, the main problem connected with steelworks 4.0 transition is the digitalization of all processes within an organization and in the entire supply chain. This is realized using various tools and methods but they are concentrated on using technologies and methods such as artificial intelligence, drones, virtual reality, full automatization, and industrial robots. The effects are connected to better relations with customers, which leads to an increase in customer satisfaction and the organizations’ profit. The steel industry will undergo further strong changes, bringing it closer to Industry 4.0 because it occupies an important place in the economies of many countries due to the strong dependence of steel producers on the markets of the recipients (steel consumers). Steel is the basic material needed to make many products, and its properties have been valued for centuries. In addition, steel mills with positive economic, social, and environmental aspects are part of the concept of sustainability for industries and economies.

scholarly journals Maximizing the Coverage of Roadmap Graph for Optimal Motion Planning

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
Jae-Han Park ◽  
Tae-Woong Yoon
Keyword(s):  
Motion Planning ◽  
Industry 4.0 ◽  
Industrial Robot ◽  
Efficient Solutions ◽  
Industrial Robots ◽  
Optimal Motion ◽  
Optimal Motion Planning ◽  
Planning Problems ◽  
Complex Planning ◽  
Satisfactory Quality

Automated motion-planning technologies for industrial robots are critical for their application to Industry 4.0. Various sampling-based methods have been studied to generate the collision-free motion of articulated industrial robots. Such sampling-based methods provide efficient solutions to complex planning problems, but their limitations hinder the attainment of optimal results. This paper considers a method to obtain the optimal results in the roadmap algorithm that is representative of the sampling-based method. We define the coverage of a graph as a performance index of its optimality as constructed by a sampling-based algorithm and propose an optimization algorithm that can maximize graph coverage in the configuration space. The proposed method was applied to the model of an industrial robot, and the results of the simulation confirm that the roadmap graph obtained by the proposed algorithm can generate results of satisfactory quality in path-finding tests under various conditions.

INDUSTRY 4.0 AS THE CHALLENGE FOR EMPLOYMENT CHANGE AND FOR RESTRUCTURING PROCESS

2020 ◽  
Vol 21 (2) ◽  
pp. 123-135
Author(s):  
Bożena Gajdzik
Keyword(s):  
Technological Change ◽  
Industry 4.0 ◽  
Industrial Robots ◽  
Technological Changes ◽  
Employment Change ◽  
Literature Study ◽  
Restructuring Process ◽  
Full Automation ◽  
Employment Restructuring

Industry 4.0 is next big technological change. Technological changes always result in employment changes. Industry 4.0 is based on full automation of production and using industrial robots in the production. The publication is the beginning of the discussion on employment restructuring in the Industry 4.0 ( I 4.0). The work was based on a study of literature, including industrial reports. The completed literature study was the basis for scientific dissertation about the place of employment restructuring in the Industry 4.0. The aim of this study is presentation of changes in employment and in the restructuring process in the Industry 4.0.

scholarly journals Machine Tools and Industrial Robots as Key Technologies to Enable Industry 4.0

2020 ◽  
Vol 32 (2) ◽  
pp. 37-48
Author(s):  
Péter Zentay ◽  
Gerald Mies
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Industrial Revolution ◽  
Industrial Robots ◽  
Global Industry ◽  
Technological Developments ◽  
Holistic Integration ◽  
Key Enabling Technologies ◽  
Industry Sectors ◽  
Efficiency And Productivity

The industrial environment has been changing rapidly over the past few years. Today, the Internet of Things (IoT) is finding its way into the global industry sectors. This ongoing industrial digitisation raises new challenges for the whole manufacturing industry. Smart factories are on the rise and promise higher efficiency and productivity. New technological developments in the field of hardware and software significantly extend today’s possibilities. Cutting- edge digital manufacturing solutions, especially new smart machines and collaborative robots are being promoted as key enabling technologies in this fourth industrial revolution. However, in the era of Industry 4.0 the holistic integration is a matter of great importance. Taking a step towards Industry 4.0, it is crucial to give equal consideration to products, production processes and business activities.

scholarly journals Dynamic Simulation Modeling of Industrial Robot Kinematics in Industry 4.0

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Guang Jin ◽  
Shuai Ma ◽  
Zhenghui Li
Keyword(s):  
Dynamic Simulation ◽  
Trajectory Planning ◽  
Simulation Modeling ◽  
Industry 4.0 ◽  
Industrial Robot ◽  
Error Model ◽  
Position Error ◽  
Industrial Robots ◽  
Robot Kinematics ◽  
Kinetic Characteristics

This paper studies the kinematic dynamic simulation modeling of industrial robots in the Industry 4.0 environment and guides the kinematic dynamic simulation modeling of industrial robots in the Industry 4.0 environment in the context of the research. To address the problem that each parameter error has different degrees of influence on the end position error, a method is proposed to calculate the influence weight of each parameter error on the end position error based on the MD-H error model. The error model is established based on the MD-H method and the principle of differential transformation, and then the function of uniform variation of six joint angles with time t is constructed to ensure that each linkage geometric parameter is involved in the motion causing error accumulation. Through the analysis of the robot marking process, the inverse solution is optimized for multiple solutions, and a unique engineering solution is obtained. Linear interpolation, parabolic interpolation, polynomial interpolation, and spline curve interpolation are performed on the results after multisolution optimization in the joint angle, and the pros and cons of various interpolation results are analyzed. The trajectory planning and simulation of industrial robots in the Industry 4.0 environment are carried out by using a special toolbox. The advantages and disadvantages of the two planning methods are compared, and the joint space trajectory planning method is selected to study the planning of its third and fifth polynomials. The kinetic characteristics of the robot were simulated and tested by experimental methods, and the reliability of the simulation results of the kinetic characteristics was verified. The kinematic solutions of industrial robots and the results of multisolution optimization are simulated. The methods, theories, and strategies studied in this paper are slightly modified to provide theoretical and practical support for another dynamic simulation modeling of industrial robot kinematics with various geometries.

scholarly journals Enabling robotic adaptive behaviour capabilities for new Industry 4.0 automated quality inspection paradigms

2020 ◽  
Vol 62 (6) ◽  
pp. 338-344 ◽  
Author(s):  
C Mineo ◽  
M Vasilev ◽  
B Cowan ◽  
C N MacLeod ◽  
S G Pierce ◽  
...  
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Industry 4.0 ◽  
Industrial Robots ◽  
Adaptive Behaviour ◽  
Full Potential ◽  
Seamless Integration ◽  
Speed Accuracy ◽  
Accuracy And Repeatability ◽  
The Way

The seamless integration of industrial robotic arms with server computers, sensors and actuators can revolutionise the way in which automated non-destructive testing (NDT) is performed and conceived. Achieving effective integration and realising the full potential of robotic systems presents significant challenges, since robots, sensors and end-effector tools are often not necessarily designed to be put together and form a holistic system. This paper presents recent breakthroughs, opening up new scenarios for the inspection of product quality in advanced manufacturing. Many years of research have brought to software platforms the ability to integrate external data acquisition instrumentation with industrial robots to improve the inspection speed, accuracy and repeatability of NDT. Robotic manipulators have typically been operated by predefined tool-paths generated through offline path-planning software applications. Recent developments pave the way to data-driven autonomous robotic inspections, enabling real-time path planning and adaptive control. This paper presents a toolbox with highly efficient algorithms and software functions, developed to be used through high-level programming language platforms (for example MATLAB, LabVIEW and Python) and/ or integrated within low-level language (for example C# and C++) applications. The use of the toolbox can speed up the development and the robust integration of new robotic NDT systems with real-time adaptive capabilities and is compatible with all KUKA robots with six degrees of freedom (DOF), which are equipped with the Robot Sensor Interface (RSI) software add-on. The paper describes the architecture of the toolbox and shows two application examples, where performance results are provided. The concepts described in the paper are aligned with the emerging Industry 4.0 paradigms and have wider applicability beyond NDT.

Heterogeneous Connection and Process Anomaly Detection of Industrial Robot in Intelligent Factory

2020 ◽  
Vol 34 (12) ◽  
pp. 2059041
Author(s):  
Xianhe Wen ◽  
Heping Chen
Keyword(s):  
Anomaly Detection ◽  
Industry 4.0 ◽  
Short Term Memory ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Main Research ◽  
Open Platform ◽  
Leading Role ◽  
Unsupervised Anomaly Detection ◽  
Long Short Term Memory

Since the concept of industry 4.0 was proposed in 2011, the trend of industry 4.0 has been surging around the world. Intelligent factory is one of the main research points in the industry 4.0 era. In order to improve the intelligent level of the factory, the connection-and-cognition ability has to be established for the factory and its equipment. Connection builds data pipes among equipment and systems while cognition automatically turns the data into knowledge. In an intelligent factory, industrial robot plays a leading role. Hence, the aim of this paper is to synthetically study connection and cognition of industrial robots in intelligent factories. To be specific, open platform communications unified architecture (OPC UA) is applied to establish heterogeneous connection of industrial robots with factory management software. A long short-term memory (LSTM) joint auto encoder method is proposed to establish the unsupervised anomaly detection cognition ability for industrial robot process (e.g. grinding, welding and assembling). In summary, this study puts OPC UA and LSTM auto encoder technology together to study heterogeneous connection and process anomaly detection of industrial robots in intelligent factory. The experimental results showed that the proposed method successfully realized heterogeneous connection of an industrial robot and detected process anomaly from the robot built-in sensors’ data.

scholarly journals Filtering Touch: An Ethnography of Dirt, Danger, and Industrial Robots

2021 ◽  
pp. 089124162110267
Author(s):  
Ned Barker ◽  
Carey Jewitt
Keyword(s):  
Identity Formation ◽  
Industry 4.0 ◽  
Industrial Robots ◽  
Fourth Generation ◽  
New Wave ◽  
Mediating Effects ◽  
Novel Technologies ◽  
Sensory Experiences ◽  
The Social

“Industry 4.0” marks the advent of a new wave of industrial robotics designed to bring increased automation to “extreme” touch practices and enhance productivity. This article presents an ethnography of touch in two industrial settings using fourth generation industrial robots (a Glass Factory and a Waste Management Center) to critically explore the social and sensorial implications of such technologies for workers. We attend to manifestations of dirt and danger as encountered through describing workers’ sensory experiences and identity formation. The contribution of the article is two-fold. The first is analytical through the development of three “filters” to grasp the complexity of the social and sensorial dynamics of touch in situ while tracing dispersed mediating effects of the introduction of novel technologies. The second is empirical, teasing out themes embedded in the sociosensorial dynamics of touch that intersect with gender, ethnicity, and class and relate to the technological mediation of touch.

scholarly journals Singularity measurement in the Cyber-physical and intelligent robot systems laboratory

2020 ◽  
Vol 11 (2) ◽  
pp. 82-87
Author(s):  
Timotei István Erdei ◽  
Géza Husi
Keyword(s):  
Industry 4.0 ◽  
Industrial Robots ◽  
Manufacturing Industries ◽  
Research Centre ◽  
Intelligent Robot ◽  
Robot Systems ◽  
Material Studies ◽  
Robot Cell

AbstractIn the building mechatronics research centre of University of Debrecen, Faculty of Engineering, a new laboratory has been designed, named “Cyber-physical and intelligent robot systems laboratory”. The possibility to design and test unique and platform-independent systems was among the main goals, hoping that the system itself and its advancements may later be used in manufacturing industries as well.Fulfilling the needs of “Industry 4.0” is a challenging task, as it requires every single device (e.g. industrial robots) to be connected to the same network, where they may be monitored and controlled. However, there are some factors that limit this, such as the periodical “instability” that some machines have, caused by singularity points.The following material studies these so-called singularities of a KUKA KR5 industrial welder robot placed in a robot cell, from an engineering viewpoint.

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