Data Driven Die Casting Smart Factory Solution

2018 ◽  
pp. 13-21 ◽  
Author(s):  
Yuanfang Zhao ◽  
Feng Qian ◽  
Yuan Gao
Keyword(s):  
Die Casting ◽  
Data Driven ◽  
Smart Factory

Data-Driven Analysis for RFID-Enabled Smart Factory: A Case Study

2020 ◽  
Vol 50 (1) ◽  
pp. 81-88 ◽  
Author(s):  
Jiqiang Feng ◽  
Feipeng Li ◽  
Chen Xu ◽  
Ray Y. Zhong
Keyword(s):  
Data Driven ◽  
Smart Factory

Smart Production Line: Common Factors and Data-Driven Implementation Method

2017 ◽  
Author(s):  
Yongping Zhang ◽  
Ying Cheng ◽  
Fei Tao
Keyword(s):  
Production Line ◽  
Common Factors ◽  
Development Strategies ◽  
Data Driven ◽  
Evolution Process ◽  
Smart Factory ◽  
Basic Unit ◽  
The Common ◽  
Implementation Method

Smart factory and smart production are the common aims for many countries’ manufacturing development strategies, which have attracted attentions from both academia and industry. Smart production line, which is a basic unit for implementing smart factory and smart production, is emphasized in this paper. The evolution process of production line is summarized first. Then the common factors for smart production line are investigated. Accordingly, a data-driven method for realizing smart production line is proposed. At the same time, the corresponding applications and attainable goals are given. Finally, a case for data-driven energy emulation and analysis in production line is illustrated.

scholarly journals Establishment of an IoT-based smart factory and data analysis model for the quality management of SMEs die-casting companies in Korea

2019 ◽  
Vol 15 (10) ◽  
pp. 155014771987937
Author(s):  
Sangwoo Park ◽  
Kim Changgyun ◽  
Sekyoung Youm
Keyword(s):  
Data Analysis ◽  
Internet Of Things ◽  
Die Casting ◽  
Smart Factory ◽  
Analysis Model ◽  
Data Mining Technique ◽  
Casting Parameter ◽  
The Government ◽  
Casting Industry ◽  
Smart Factories

In this research, an Internet of things–based smart factory was established for a die-casting company that produces automobile parts, and the effect of casting parameters on quality was analyzed using data collected from the system. Most of the die-casting industry in Korea consists of small- and medium-sized enterprises with inferior finances and skeptical views about the establishment of a smart factory. In response, the Korean government is providing various types of support to spread the implementation of smart factories for small- and medium-sized enterprises. Although small- and medium-sized enterprises have become more active in establishing smart factories according to the government policies, the effect of smart factories requires real-time monitoring. A monitoring system has been built but the data collected are not being utilized properly. Therefore, it is necessary to establish a system suitable for the die-casting environment and data analysis purposes and to utilize it to enable the analysis of data. To this end, we established to smart factory that provides data based on the Internet of things. Among the data collected, casting parameter data were analyzed through a data mining technique to establish a relationship between casting parameters and the quality of production. It is expected that a method of systematic implementation will be provided to die-casting companies that want to build smart factories in the future and that a plan for managing casting parameter by-product will be established. In addition, algorithms that can solve the problem of multi-collinearity among the casting parameters and aid in the development of new products are needed to detect optimum casting parameters.

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