scholarly journals Application of Mathematical Economic Model in Financial System in Manufacturing Industry

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Boqi Tang
Keyword(s):  
Manufacturing Industry ◽  
Manufacturing System ◽  
High Efficiency ◽  
Simulation Experiment ◽  
Model Simulation ◽  
Intelligent Manufacturing ◽  
Normal Operation ◽  
Economic Research ◽  
Intelligent Computing ◽  
Intelligent Manufacturing System

In the field of economic research, most of the sample data is not obtained based on controllable experiments but generated during the normal operation of the economic system. Therefore, the change of an economic variable is usually not caused by a single change of a cause variable. It is the result of a combination of multiple factors. Therefore, it is necessary to study the application of mathematical intelligent computing in computer intelligent manufacturing system. The purpose of this paper is to explore the application of mathematical intelligent computing in computer intelligent manufacturing system. For this reason, this paper uses the furnace temperature control model to carry out simulation experiment. In this simulation experiment, three algorithms of mathematical intelligent computing are mainly used, including BPES intelligent computing method, genetic algorithm, and MARS algorithm. The research results show that the superparameter optimization based on MARS has high efficiency, and the best result, the worst result, the average result, the variance, and the average time of multiple independent runs are controlled below 0.03 s. In this experiment, when the hidden layer node is 9, the prediction error value is the smallest, and the model simulation curve is basically consistent with the measured curve trend. In the simulation experiment of this paper, these three algorithms have shown good results in their respective links.

Knowledge Protocols

2011 ◽  
pp. 304-323 ◽  
Author(s):  
Ercan Oztemel ◽  
Esra Kurt Tekez
Keyword(s):  
Manufacturing Industry ◽  
Manufacturing System ◽  
Knowledge Exchange ◽  
International Competitiveness ◽  
Intelligent Manufacturing ◽  
Intelligent Manufacturing System ◽  
Manufacturing Enterprises ◽  
Industrial Organizations ◽  
Basic Features

Manufacturing enterprises continuously have to cope with changing markets that are unpredictable and diverse; manufacturing industry is facing international competitiveness and globalization. This obviously requires industrial organizations to manage different components of their organizations by integrating and coordinating them into a highly efficient, effective, and responsive system in order to maintain and improve their competitiveness. This chapter presents a knowledge exchange procedure for creating an integrated intelligent manufacturing system. The basic features of proposed scheme are introduced and the approach is supported through a case study.

An EDM Multi-Agent Collaborative Manufacturing System Based on Petri Net

2012 ◽  
Vol 457-458 ◽  
pp. 921-926
Author(s):  
Jin Zhi Zhao ◽  
Yuan Tao Liu ◽  
Hui Ying Zhao
Keyword(s):  
Petri Net ◽  
Manufacturing System ◽  
Intelligent Manufacturing ◽  
Agent Technology ◽  
Manufacturing Processes ◽  
Intelligent Manufacturing System ◽  
Collaborative Manufacturing ◽  
Model Based ◽  
Support Organizations ◽  
Multi Agent

A framework for building EDM collaborative manufacturing system using multi-agent technology to support organizations characterized by physically distributed, enterprise-wide, heterogeneous intelligent manufacturing system over Internet is proposed. According to the characteristics of agile EDM collaborative manufacturing system(AEDMCMS), the agent technology is combined with Petri net in order to analyze the model. Based on the basic Petri Net, the definition is extended and the Agent-oriented Petri net (APN) is proposed. AEDMCM is turned into the model of Petri Net which is suitable to the analysis and optimization of manufacturing processes.

Design and Algorithm of Intelligent Manufacturing Evaluation Model Based on Machine Learning

2021 ◽  
Author(s):  
Xianwang Li ◽  
Zhongxiang Huang ◽  
Wenhui Ning
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Manufacturing System ◽  
Learning Algorithm ◽  
Intelligent Manufacturing ◽  
System Model ◽  
Machine Learning Algorithm ◽  
Model Design ◽  
Bp Network ◽  
Intelligent Manufacturing System

Abstract Machine learning is gradually developed and applied to more and more fields. Intelligent manufacturing system is also an important system model that many companies and enterprises are designing and implementing. The purpose of this study is to evaluate and analyze the model design of Intelligent Manufacturing System Based on machine learning algorithm. The method of this study is to first obtain all the relevant attributes of the intelligent manufacturing system model, and then use machine learning algorithm to delete irrelevant attributes to prevent redundancy and deviation of neural network fitting, make the original probability distribution as close as possible to the distribution when using the selected attributes, and use the ratio of industry average to quantitative expression for measurable and obvious data indicators. As a result, the average running time of the intelligent manufacturing system is 17.35 seconds, and the genetic algorithm occupies 15.63 seconds. The machine learning network takes up 1.72 seconds. Under the machine learning algorithm, the training speed is very high, obviously higher than that of the genetic algorithm, and the BP network is 2.1% higher than the Elman algorithm. The evaluation running speed of the system model design is fast and the accuracy is high. This study provides a certain value for the model design evaluation and algorithm of various systems in the intelligent era.

Augmented Technology for Safety and Maintenance in Industry 4.0

2021 ◽  
pp. 495-502
Author(s):  
Vikas Kukshal ◽  
Amar Patnaik ◽  
Sarbjeet Singh
Keyword(s):  
Industry 4.0 ◽  
Manufacturing System ◽  
Industrial Revolution ◽  
Intelligent Manufacturing ◽  
Skilled Workers ◽  
New Era ◽  
Intelligent Manufacturing System ◽  
Traditional Manufacturing ◽  
Area Of Concern ◽  
Rapid Transformation

The traditional manufacturing system is going through a rapid transformation and has brought a revolution in the industries. Industry 4.0 is considered to be a new era of the industrial revolution in which all the processes are integrated with a product to achieve higher efficiency. Digitization and automation have changed the nature of work resulting in an intelligent manufacturing system. The benefits of Industry 4.0 include higher productivity and increased flexibility. However, the implementation of the new processes and methods comes along with a lot of challenges. Industry 4.0. requires more skilled workers to handle the operations of the digitalized manufacturing system. The fourth industrial revolution or Industry 4.0 has become the absolute reality and will undoubtedly have an impact on safety and maintenance. Hence, to tackle the issues arising due to digitization is an area of concern and has to be dealt with using the innovative technologies in the manufacturing industries.

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