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Academic Journal of Architecture and Geotechnical Engineering, 2023, 5(7); doi: 10.25236/AJAGE.2023.050705.

Study on Optimization Strategies for Old Industrial Building Sites—Take Shuguang Machinery Factory (Zhaoqing, China) as an Example

Author(s)

Xueqian He, Mingchen Chen, Guanyu Zhu

Corresponding Author:
Xueqian He
Affiliation(s)

Construction Institute, Guangdong Technology College, Zhaoqing, Guangdong, 526100, China

Abstract

This paper studies the regeneration design of old factory buildings with low production and high consumption which are eliminated under the trend of domestic industrial upgrading, takes the transformation research of old factory buildings under the background of cultural and creative industries as the starting point, combines the relevant information, analyzes the relevant theoretical data on the regeneration design of the old factory buildings concerning the functions, layout, facilities and regeneration forms, etc., and puts forward an optimization strategy suitable for the current trend of regeneration of the old factory buildings based on existing transformation design of the old factory buildings. Regeneration trend optimization strategy. This paper takes Zhaoqing Shuguang Electromechanical Factory as a transformation case, based on adapting to the background of cultural and creative, combining with the demand characteristics of the old factory building transformation, making the optimization design strategy of the old factory building, researching the new scheme suitable for the regeneration design of the old factory building, and solving the problem of the reuse of the old factory building.

Keywords

Old Factory Renovation, Zhaoqing Shuguang Electromechanical Factory, Optimized Design Strategies

Cite This Paper

Xueqian He, Mingchen Chen, Guanyu Zhu. Study on Optimization Strategies for Old Industrial Building Sites—Take Shuguang Machinery Factory (Zhaoqing, China) as an Example. Academic Journal of Architecture and Geotechnical Engineering (2023) Vol. 5, Issue 7: 27-36. https://doi.org/10.25236/AJAGE.2023.050705.

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