Implementation of Industry 4.0 and Industrial Robots in the Manufacturing Processes

2019 ◽  
pp. 3-14 ◽  
Author(s):  
Isak Karabegović ◽  
Edina Karabegović ◽  
Mehmed Mahmić ◽  
Ermin Husak
Keyword(s):  
Industry 4.0 ◽  
Industrial Robots ◽  
Manufacturing Processes

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.

Business process management for Industry 4.0 – Three application cases in the DFKI-Smart-Lego-Factory

2018 ◽  
Vol 60 (3) ◽  
pp. 133-141 ◽  
Author(s):  
Jana-Rebecca Rehse ◽  
Sharam Dadashnia ◽  
Peter Fettke
Keyword(s):  
Business Process ◽  
Industry 4.0 ◽  
Business Process Management ◽  
Manufacturing Industry ◽  
Process Management ◽  
Process Mining ◽  
Smart Factory ◽  
Manufacturing Processes ◽  
Planning And Control ◽  
And Control

Abstract The advent of Industry 4.0 is expected to dramatically change the manufacturing industry as we know it today. Highly standardized, rigid manufacturing processes need to become self-organizing and decentralized. This flexibility leads to new challenges to the management of smart factories in general and production planning and control in particular. In this contribution, we illustrate how established techniques from Business Process Management (BPM) hold great potential to conquer challenges in Industry 4.0. Therefore, we show three application cases based on the DFKI-Smart-Lego-Factory, a fully automated “smart factory” built out of LEGO® bricks, which demonstrates the potentials of BPM methodology for Industry 4.0 in an innovative, yet easily accessible way. For each application case (model-based management, process mining, prediction of manufacturing processes) in a smart factory, we describe the specific challenges of Industry 4.0, how BPM can be used to address these challenges, and, their realization within the DFKI-Smart-Lego-Factory.

Digital Twin: Collaborative Virtual Reality Environment for Multi-Purpose Industrial Applications

2020 ◽  
Author(s):  
Vladimir Kuts ◽  
Tauno Otto ◽  
Yevhen Bondarenko ◽  
Fei Yu
Keyword(s):  
Virtual Reality ◽  
Augmented Reality ◽  
Mobile Robot ◽  
Industrial Robots ◽  
Use Cases ◽  
System Level ◽  
Manufacturing Processes ◽  
Remote Locations ◽  
System Level Simulation ◽  
Smart Healthcare

Abstract Industrial Digital Twins (DT) is the precise virtual representation of the manufacturing environment and mainly consists of the system-level simulation, which combines both manufacturing processes and parametric models of the product. As being one of the pillars of the Industry 4.0 paradigm, DT-s are widely integrated into the existing factories, enhancing the concept of the virtual factories. View from the research perspective is that experiments on the Internet of Things, data acquisition, cybersecurity, telemetry synchronization with physical factories, etc. are being executed in those virtual simulations. Moreover, new ways of interactions and interface to oversee, interact and learn are being developed via the assistance of Virtual Reality (VR) and Augmented Reality (AR) technologies, which are already widely spread on the consumer market. However, already, VR is being used widely in existing commercial software packages and toolboxes to provide students, teachers, operators, engineers, production managers, and researchers with an immersive way of interacting with the factory while the manufacturing simulation is running. This gives a better understanding and more in-depth knowledge of the actual manufacturing processes, not being directly accessing those. However, the virtual presence mentioned above experience is limited to a single person. It does not enable additional functionalities for the simulations, which can be re-planning or even re-programming of the physical factory in an online connection by using VR or AR interfaces. The main aim of the related research paper is to enhance already existing fully synchronized with physical world DT-s with multi-user experience, enabling factory operators to work with and re-program the real machinery from remote locations in a more intuitive way instead thinking about final aim than about the process itself. Moreover, being developed using real-time platform Unity3D, this multiplayer solution gives opportunities for training and educational purposes and is connecting people from remote locations of the world. Use-cases exploits industrial robots placed in the Industrial Virtual and Augmented Reality Laboratory environment of Tallinn University of Technology and a mobile robot solution developed based on a collaboration between the University of Southern Denmark and a Danish company. Experiments are being performed on the connection between Estonia and Denmark while performing reprogramming tasks of the physical heavy industrial robots. Furthermore, the mobile robot solution is demonstrated in a virtual warehouse environment. Developed methods and environments together with the collected data will enable us to widen the use-cases with non-manufacturing scenarios, i.e., smart city and smart healthcare domains, for the creation of a set of new interfaces and multiplayer experiences.

scholarly journals Special Issue on New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes

2019 ◽  
Vol 9 (20) ◽  
pp. 4323 ◽  
Author(s):  
López de Lacalle ◽  
Posada
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Research Community ◽  
Manufacturing Processes ◽  
Special Issue ◽  
Industrial Internet Of Things ◽  
Visual Computing ◽  
Industrial Internet ◽  
Industrial Iot ◽  
New Industry

The new advances of IIOT (Industrial Internet of Things), together with the progress in visual computing technologies, are being addressed by the research community with interesting approaches and results in the Industry 4.0 domain[...]

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.

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.

Industry 4.0: examples of the use of the robotic arm for digital manufacturing processes

2020 ◽  
Vol 14 (4) ◽  
pp. 1569-1575
Author(s):  
William S. Barbosa ◽  
Mariana M. Gioia ◽  
Veronica G. Natividade ◽  
Renan F. F. Wanderley ◽  
Marcelo R. Chaves ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Robotic Arm ◽  
Digital Manufacturing ◽  
Manufacturing Processes
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