Training for smart manufacturing using a mobile robot-based production line

Wang, Zhen; Jiang, Laizhu; Meng, Jie; Xie, Yuanlong; Ding, Han

doi:10.1007/s11465-020-0625-z

Cited by 25 publications

(2 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The main features of the electrical engineering major are the combination of strong and weak electricity, electromechanical integration, and the combination of software and hardware, which reflects the nature and characteristics of interdisciplinary. Graduates have strong adaptability and belong to "wide-caliber" majors [6].…”

Section: Introductionmentioning

confidence: 99%

A Talent Training Model for Electrical Courses considering Diverse Constraint Models and Knowledge Recognition Algorithms

Min

2022

Advances in Multimedia

View full text Add to dashboard Cite

In order to improve the talent training effect of electrical courses, this paper proposes a talent training model for electrical courses considering diverse constraint models and knowledge recognition algorithms. In order to obtain better performance of traditional deep learning models, it is usually necessary to increase the parameter scale of traditional deep learning models. Pretrained language models can be trained unsupervised directly using unlabeled corpora to learn vector representations of words without using labeled datasets. In addition, this paper uses the knowledge base and alias dictionary to build a knowledge graph and constructs a teaching model for electrical courses considering diverse constraint models and knowledge recognition algorithms. Through the research, it can be seen that the experimental teaching model of electrical courses proposed in this paper considering diverse constraint models and knowledge recognition algorithms has a very good effect on talent training.

show abstract

Section: Introductionmentioning

confidence: 99%

A Talent Training Model for Electrical Courses considering Diverse Constraint Models and Knowledge Recognition Algorithms

Min

2022

Advances in Multimedia

View full text Add to dashboard Cite

show abstract

“…The literature expounds that using facility location redescription and single commodity flow constraint to eliminate subsequences, effective formulas that can provide high-quality solutions for largescale instances can be obtained from classical models by making binary production variables explicit [11]. Literature research puts forward a reference practice system for practical training of key progress of SM and systematically constructs a mobile robot-based production line (MRPL) to improve participants' interest in theoretical study and professional skills [12]. A numerical example based on the information collected from the engine crankshaft leasing batch production line shows that the R and OM policy can effectively maximize the leasing profit, reduce the complexity of joint decision-making, and extend the OM theory [13].…”

Section: Introductionmentioning

confidence: 99%

Optimization and Design of General Machinery Production Line Management Process Based on Intelligent Computing Model

Zeng

et al. 2022

Journal of Sensors

View full text Add to dashboard Cite

Machinery is the most important basic tool for modern times, and it is also an indispensable sharp weapon for creating big country projects. The production line management of general machinery is particularly important. Traditional production line management causes a lot of labor waste, time waste, and low production efficiency, so the efficiency of production line management also determines the quality and output of general machinery. Therefore, it has become an industry consensus to realize intelligent management in the manufacturing process of general machinery. General machinery is not only a complex industrial structure but also has a series of preconditions that are not conducive to production, such as the diversity of parts and the low precision of preparation in the early stage. Therefore, to realize automation in the field of construction machinery manufacturing, it usually faces more challenges. Whether it is traditional production process or automatic production process, the realization of intelligent production line is the primary problem, because both production efficiency and product quality are determined by the efficient production line management efficiency and exquisite process. The workload of production line management is heavy, which is time-consuming, labor-consuming, and expensive. Adhere to the goal of quality first, and how to improve the efficiency of the production line has become the biggest problem at present. Based on the above problems, this paper adopts intelligent computing model to improve the efficiency of production line management and optimize the process. A series of tedious processes from product adoption to final shipment of production lines need intelligent technology to simplify the process, which can effectively improve the production efficiency of general machinery, reduce production costs, and improve the production quality of machinery. Supply chain management theory is used to manage suppliers’ production behavior, so as to reduce costs and improve quality and service, thus improving the competitiveness of batch production lines and enterprises. Advanced manufacturing technology is used to realize automation and flexible production of batch production lines, thus improving the rapid response ability of production lines to market demand.

show abstract