kth.sePublications KTH
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Practical Research on Intelligent Upgrading Management of Building Steel Structure Manufacturing Factory
School of Management, University of Science and Technology, Wuhan 430065, China; Center for Service Science and Engineering, Wuhan University of Science and Technology, Wuhan 430065, China.
School of Management, University of Science and Technology, Wuhan 430065, China.
KTH, School of Industrial Engineering and Management (ITM), Production engineering. School of Management, University of Science and Technology, Wuhan 430065, China; Center for Service Science and Engineering, Wuhan University of Science and Technology, Wuhan 430065, China.ORCID iD: 0000-0001-7585-4674
2025 (English)In: Proceedings of the 14th International Conference on Logistics and Systems Engineering, Curran Associates, Inc. , 2025, p. 268-278Conference paper, Published paper (Refereed)
Abstract [en]

With the advancement of intelligent transformation in the manufacturing industry, the building steel structure industry is also facing an urgent need to enhance its intelligent manufacturing level. This article takes the building steel structure manufacturing factory of China Construction Steel Structure Guangdong Co., Ltd. as the research object and deeply explores its management practice of intelligent upgrading. The traditional discrete intelligent manufacturing model of steel structures has many problems, such as low production efficiency, insufficient flexibility of the production line, and backward manufacturing technology. To address these issues, the factory has innovated in multiple key processes. In terms of equipment upgrading, a high-power laser cutting machine is introduced in the blanking process, significantly improving cutting quality and speed; advanced 3D visual recognition technology and cutting robots are adopted in the bevel cutting process, enhancing precision and efficiency; the welding process is optimized with laser rust removal and the application of new technologies to expand the use of welding robots; the grinding process utilizes large-format laser rust removal equipment to improve the rust removal effect of small steel structure components; at the same time, the processes of steel structure turning and transportation are optimized to ensure safety and improve efficiency. Based on the standardized intelligent units of each process, the factory actively constructs intelligent production lines, including intelligent H-shaped steel production lines and intelligent box-shaped production lines, realizing the interconnection and interoperability of equipment and integrated analysis of data, optimizing resource allocation and quality control. In addition, the factory uses technologies such as industrial PON networks to build intelligent manufacturing systems and big data platforms, improving the digital management level. Through these intelligent upgrading measures, the production capacity of the factory's equipment is fully released, the manufacturing efficiency and product quality of steel structures are improved, costs are reduced, benefits are increased, and the employee structure is optimized. This practice not only provides valuable experience for the steel structure industry but also has important reference value for the transformation and upgrading of the entire discrete manufacturing industry in dealing with complex order production modes, helping enterprises closely follow the development trend of intelligent manufacturing and enhance market competitiveness.

Place, publisher, year, edition, pages
Curran Associates, Inc. , 2025. p. 268-278
Keywords [en]
building steel structure, equipment upgrading, process optimization, production line construction
National Category
Production Engineering, Human Work Science and Ergonomics Manufacturing, Surface and Joining Technology
Identifiers
URN: urn:nbn:se:kth:diva-361431DOI: 10.52202/078960-0027Scopus ID: 2-s2.0-86000247843OAI: oai:DiVA.org:kth-361431DiVA, id: diva2:1945861
Conference
14th International Conference on Logistics and Systems Engineering, Hengyang, China, December 13-14, 2024
Note

Part of ISBN 9798331314347

QC 20250325

Available from: 2025-03-19 Created: 2025-03-19 Last updated: 2025-03-25Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Wang, Yong

Search in DiVA

By author/editor
Wang, Yong
By organisation
Production engineering
Production Engineering, Human Work Science and ErgonomicsManufacturing, Surface and Joining Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 133 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf