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Smart Grid and Internet of Things. 6th EAI International Conference, SGIoT 2022, TaiChung, Taiwan, November 19-20, 2022, Proceedings

Research Article

Digital Transformation Application of Precision Industrial Quotation System

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BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-31275-5_8,
        author={Wen-Hsing Kao and Yi-Mei Zeng and Zi-Ying Nian and Rung-Shiang Cheng},
        title={Digital Transformation Application of Precision Industrial Quotation System},
        proceedings={Smart Grid and Internet of Things. 6th EAI International Conference, SGIoT 2022, TaiChung, Taiwan, November 19-20, 2022, Proceedings},
        proceedings_a={SGIOT},
        year={2023},
        month={5},
        keywords={Digital Transformation Quotation Data Mining},
        doi={10.1007/978-3-031-31275-5_8}
    }
    
  • Wen-Hsing Kao
    Yi-Mei Zeng
    Zi-Ying Nian
    Rung-Shiang Cheng
    Year: 2023
    Digital Transformation Application of Precision Industrial Quotation System
    SGIOT
    Springer
    DOI: 10.1007/978-3-031-31275-5_8
Wen-Hsing Kao1, Yi-Mei Zeng2, Zi-Ying Nian2, Rung-Shiang Cheng1,*
  • 1: Department of Information Technology
  • 2: Department of Business Administration
*Contact email: rscheng@ocu.edu.tw

Abstract

The digital era is coming. In recent years, due to the continuous improvement of information technology, Artificial Intelligence, Big Data, Cloud Computing and IoT related technology has flourished. For traditional industries, demand is gradually changing from less diverse product to more diverse product. And most of them are customized orders, so the change of production mode has also become an opportunity for the digital transformation of enterprises. In addition, under the impact of the epidemic at the end of 2019, enterprises pay more attention to digital transformation.

This study cooperates with a precision industrial company in Taichung. The company used to record all the data in the quotation process in paper. In addition to the difficulty of data backtracking, quotation data such as cost, delivery period, production process, outsourced manufacturers and prices are also difficult to compare with the actual order data. Also, departments often affect the quotation time due to the cumbersome communication process. In order to solve the above problems and improve the quotation process, this study is discussed in a faster, more accurate, more effective and profitable way.

By building a digital quotation system, digitally optimize the difficulties encountered by quotations, and finally solve the problem to make the quotation system successfully digitally transformed.

Keywords
Digital Transformation Quotation Data Mining
Published
2023-05-01
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-31275-5_8
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