scholarly journals Application of Industrial Robots in Automated Production Lines under the Background of Intelligent Manufacturing

2021 ◽  
Vol 1992 (4) ◽  
pp. 042050
Author(s):  
Lianyang Zhou ◽  
Fei Wang ◽  
Ningwei Wang ◽  
Tongwen Yuan
2021 ◽  
Vol 8 (1) ◽  
pp. 11-18
Author(s):  
Darina Hroncová ◽  
Ingrid Delyová ◽  
Peter Frankovský

Different types of robots are used in many areas of industry. Industrial manipulators are used to ensure productivity and flexibility in automated production lines. Most of them is used for tasks that automatically repeat the same operation in a familiar environment. The key element in the development and analysis of industrial robots is their kinematic analysis. The article deals with the kinematic analysis of this positioning equipment. Individual relations of kinematic quantities are plotted graphically. Matrix methods were used for the analysis.


2011 ◽  
Vol 47 (3-4) ◽  
pp. 167-172
Author(s):  
S. V. Teplishchev ◽  
V. Yu. Arkhangelskii

Digital Twin ◽  
2021 ◽  
Vol 1 ◽  
pp. 9
Author(s):  
Yuchen Wang ◽  
Xingzhi Wang ◽  
Fei Tao ◽  
Ang Liu

Complexity management is one of the most crucial and challenging issues in manufacturing. As an emerging technology, digital twin provides an innovative approach to manage complexity in a more autonomous, analytical and comprehensive manner. This paper proposes an innovative framework of digital twin-driven complexity management in intelligent manufacturing. The framework will cover three sources of manufacturing complexity, including product design, production lines and supply chains. Digital twin provides three services to manage complexity: (1) real-time monitors and data collections; (2) identifications, diagnoses and predictions of manufacturing complexity; (3) fortification of human-machine interaction. A case study of airplane manufacturing is presented to illustrate the proposed framework.


2013 ◽  
Vol 311 ◽  
pp. 226-231
Author(s):  
Ming Guo Her ◽  
Wen Jinn Liang ◽  
Kuan Wei Wu ◽  
Chun Chi Peng ◽  
Kuei Shu Hsu ◽  
...  

This research developed a vision navigation autonomous mobile robot and combined it with industrial automated production line. Due to traditional TFT-LCD production lines, the load/unload depends on Manual Guided Vehicle (MGV) or Automated Guided Vehicle (AGV). However, it needed to construct many tracks so that the MGV or AGV can move. The track is high cost and is not easy to adjust. Hence, our research developed an autonomous mobile robot with vision navigation technology to determine the location of TFT-LCD panel and the obstruction in the moving process. Furthermore, we successfully developed an intelligent vision navigation autonomous mobile robot in this research. It not only improved the shortcoming of setting up a lot of tracks, but also avoided the obstructions automatically to enhance the safety.


2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jiali Qiu ◽  
Lianghua Ma

With the upgrading of intelligent manufacturing, industrial robots will play an important role in the garment industry. The purpose of this article was to study the pattern and style based on the integration of artificial intelligence and clothing design. In this article, the digital modeling of clothing design and the case analysis of intelligent clothing design are described using the method of comparative experiment. The experimental results are obtained from the analysis of fuzzy number of clothing design language evaluation, three-dimensional human body construction clothing size, clothing design elements and auxiliary functions, and the analysis of the advantages and disadvantages of clothing design system. The popular clothing sample is D4 (0.4862), which is 20% higher than other products. It can be concluded that the model proposed in this article can grasp the needs of consumers and select the right one according to the market positioning. The fabric mass production fashion brand can significantly improve the efficiency and satisfaction of the fabric selection decision-making process. It provides enough technical support and style model for intelligent clothing design.


Author(s):  
Hind Bril El-Haouzi ◽  
Etienne Valette ◽  
Bettina-Johanna Krings ◽  
António Brandão Moniz

Since the 1970s, the application of microprocessor in industrial machinery and the development of computer systems have transformed the manufacturing landscape. The rapid integration and automation of production systems have outpaced the development of suitable human design criteria, creating a deepening gap where human factor was seen as an important source of errors and disruptions. Today the situation seems different: the scientific and public debate about the concept of Industry 4.0 has raised the awareness about the central role humans have to play in manufacturing systems, to the design of which they must be considered from the very beginning. The future of industrial systems, as represented by Industry 4.0, will rely on the convergence of several research fields such as Intelligent Manufacturing Systems (IMS), Cyber-Physical Systems (CPS), Internet of things (IoT), but also socio-technical fields such as social approaches within technical systems. This article deals with different Human dimensions associated with CPS and IoT and focuses on their conceptual evolution of automatization to improve the sociability of such automated production systems and consequently puts again the human in the loop. Hereby, our aim is to take stock of current research trends, and to show the importance of integrating human operators as a part of a socio-technical system based autonomous and intelligent products or resources. As results, different models of sociability as way to integrate human into the broad sense and/or the development of future automated production systems, were identified from the literature and analysed.


Proceedings ◽  
2020 ◽  
Vol 63 (1) ◽  
pp. 13
Author(s):  
Ana María Valdeón Junquera ◽  
Javier García González ◽  
Joaquín Manuel Villanueva Balsera ◽  
Vicente Rodríguez Montequín

Smart Manufacturing is a goal to be achieved, and the most advanced manufacturing approaches are being used to pursue this objective. Within this context, industry development aims to attain an intelligent manufacturing using, for example, virtual models that simulate production lines. This paper presents the architecture of a Digital Twin for emulating the rolls replacement process within a wire rod rolling mill. The model is developed in Python, using a backtracking algorithm to select the suitable set of rolls as a first basic approach for the validation of the system. It may be used in the future to improve the production system automating the decision for the replacement of rolls as alternative to the current human-decision process.


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