A big data analytics approach to develop industrial symbioses in large cities

被引：35

作者：

Bin, Song ^{[1
]}

Zhiquan, Yeo ^{[1
]}

Jonathan, Low Sze Choong ^{[1
]}

Jiewei, Derek Koh ^{[1
]}

Kurle, Denis ^{[2
]}

Cerdas, Felipe ^{[2
]}

Herrmann, Christoph ^{[2
]}

机构：

[1] Singapore Inst Mfg Technol, Singapore, Singapore

[2] Tech Univ Carolo Wilhelmina Braunschweig, Inst Machine Tools & Prod Technol IWF, Sustainable Mfg & Life Cycle Engn Res Grp, Braunschweig, Germany

来源：

22ND CIRP CONFERENCE ON LIFE CYCLE ENGINEERING | 2015年 / 29卷

关键词：

Big data analytics; Industrial symbiosis; Waste management;

D O I：

10.1016/j.procir.2015.01.066

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

A big problem for industry and large cities is the increasing waste streams from households as well as industries and their impacts to the environment. Treatment of the waste is expensive, and cities face challenges on waste disposal sites. A sustainable solution would be to realize industrial symbioses. The typical approach is to design and develop industrial parks each of which is aimed to be an industrial symbiosis. This approach is proven by successful cases, but is constrained by land scarce cities as well as the limited types and scales of the companies that can be included in an industrial park. The paper proposes a big data analytics approach to realize industrial symbioses among the industries in a city's close proximity. The waste streams and resource requirements of existing companies are identified and matched with resources needs directly or indirectly through conversion processes. The viability, critical elements and technical challenges of the approach are discussed. (C) 2015 The Authors. Published by Elsevier B.V.

引用

页码：450 / 455

页数：6

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