The digital twin of a warehouse robot for Industry 4.0

Федотов, А. А.; Сергеев, С. М.; Provotorova, E N; Prozhogina, T V; Zaslavskaya, O Yu

doi:10.1088/1757-899x/862/3/032061

Cited by 8 publications

(3 citation statements)

References 19 publications

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“…Many have used traditional simulation/cloud framework to attempt robot DT implementations, such as the ones shown in Figure 7 and Figure 8 . Other examples could be found in kinematics [ 232 ], communication [ 233 , 234 ], control [ 235 , 236 , 237 ], planning [ 238 ], and industrial robot energy modeling [ 239 ], in use cases like welding [ 240 ], cleaning [ 241 ], pick-and-place [ 242 ], assembly [ 243 , 244 , 245 , 246 ], manufacturing [ 247 ], warehouse [ 248 , 249 ], maintenance [ 250 ], and construction [ 251 ]. Some well-known robotics simulation tools are Gazebo [ 252 ], MuJoCo [ 253 ], and CoppeliaSim (aka V-REP) [ 254 ].…”

Section: Advanced Roboticsmentioning

confidence: 99%

A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

Huang

Shen²,

et al. 2021

Sensors

158

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Digital twin (DT) and artificial intelligence (AI) technologies have grown rapidly in recent years and are considered by both academia and industry to be key enablers for Industry 4.0. As a digital replica of a physical entity, the basis of DT is the infrastructure and data, the core is the algorithm and model, and the application is the software and service. The grounding of DT and AI in industrial sectors is even more dependent on the systematic and in-depth integration of domain-specific expertise. This survey comprehensively reviews over 300 manuscripts on AI-driven DT technologies of Industry 4.0 used over the past five years and summarizes their general developments and the current state of AI-integration in the fields of smart manufacturing and advanced robotics. These cover conventional sophisticated metal machining and industrial automation as well as emerging techniques, such as 3D printing and human–robot interaction/cooperation. Furthermore, advantages of AI-driven DTs in the context of sustainable development are elaborated. Practical challenges and development prospects of AI-driven DTs are discussed with a respective focus on different levels. A route for AI-integration in multiscale/fidelity DTs with multiscale/fidelity data sources in Industry 4.0 is outlined.

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Section: Advanced Roboticsmentioning

confidence: 99%

A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

Huang

Shen²,

et al. 2021

Sensors

158

View full text Add to dashboard Cite

show abstract

“…n n W  − relevant characteristics n-th room used in the educational process, research activities [28] for administrative and engineering purposes. However, since the optimization problem requires relative values rather than absolute values [29], the problem is simplified and the desired characteristics can be obtained by examining the premises using time slices of temperatures determined by digital sensors, followed by processing on a computer [30]. Figure 1,2 shows the results of computer simulation of the process of changing the temperature in the room.…”

Section: Mathematical Modelmentioning

confidence: 99%

Optimizing the energy efficiency of higher education institutions

et al. 2021

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The article presents the results of research conducted at the St. Petersburg Polytechnic University within the framework of the innovative business incubator and aimed at forming a cross-system approach to energy consumption management. The authors consider the features being typical for most educational institutions, regardless of the profile and specifics. Constant components of energy consumption are taken into account, such as outdoor lighting, scientific equipment, security systems, fire extinguishing systems, equipment of the dining room and buffet, and engineering services. The basis is a mathematical model that allows not only to describe the processes, but also to apply the methods of optimization theory and develop software for effective management of engineering equipment. The authors have used a search method based on the analysis of nonlinear functions. With the purpose of the research, an application with an extension for finding solutions to optimization problems was used in the free software package with the Linux kernel.

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“…The decrease in the removal of mineral and organic fertilizers led to a drop in soil fertility. To determine the optimal mode of energy consumption [26], it was necessary to solve the problem of using a limited natural resource for the needs of the agro-industrial complex.…”

Section: Problem Statementmentioning

confidence: 99%

Solving the problem of energy efficiency of remote agricultural farms

et al. 2021

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The research focuses on the viability of a mathematical model of energy efficiency of agricultural sector for the case of Russia. The article describes the methodology and results of research aimed at improving energy efficiency in the activities of remote farms of the agro-industrial complex. The emphasis is placed on the application of a scientific approach based on mathematical modeling of work on a limited resource. For this purpose, the most common solutions are SAN (Storage Area Network), while the programs that are common for enterprises of the network are located on cloud servers. The results of the research were applied in a joint project with the Catalan Polytechnic University (Polytechnic University of Catalonia).

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The digital twin of a warehouse robot for Industry 4.0

Cited by 8 publications

References 19 publications

A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

Optimizing the energy efficiency of higher education institutions

Solving the problem of energy efficiency of remote agricultural farms

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