A data-driven approach for improving sustainability assessment in advanced manufacturing

Liu, Yunpeng; Zhang, Heng; Roy, Utpal; Lee, Y. Tina

doi:10.1109/bigdata.2017.8258116

Cited by 19 publications

(17 citation statements)

References 24 publications

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“…The design and production of products has been analyzed. For this purpose, LCA was obtained from the data generated in the conceptual design [64] or by analyzing sustainability in manufacturing [65].…”

Section: Applicationsmentioning

confidence: 99%

“…In some investigations, data come from simulations. For example, in Sharif and Hammad [68] extensive data is collected on existing buildings related to several factors including TEC, outside temperature, building envelope components, HVAC and lighting systems; in other occasions the data are obtained using a data generator these data are later validated with experimental data [65].…”

Section: Datamentioning

confidence: 99%

“…The conceptual design of products [64] or the early design stage of building [71] are a source of data that can be used in the environmental assessment of products [64] or buildings [65].…”

Section: Datamentioning

confidence: 99%

“…For example, several of these works [63,66,68,69,71] use the LCA life cycle analysis technique to improve the design. There are also works that focus on the exploitation phase [67,70,72,73], while others focus on the study of the methodology followed in the LCA [61,62,65].…”

Section: Approachesmentioning

confidence: 99%

“…Another similar tool is the Extreme Machine Learning (feedforward neural networks), that together with fuzzy C-means clustering was used to valuate environmental impact in early building design stage. Bayesian Network Models were used too in several applications [63,65]. Linear regression was used to estimate normalization LCA factors [62].…”

Section: Toolsmentioning

confidence: 99%

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ADAPTS: An Intelligent Sustainable Conceptual Framework for Engineering Projects

Sendra

Heras

Ávila-Gutiérrez

et al. 2020

Sensors

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This paper presents a conceptual framework for the optimization of environmental sustainability in engineering projects, both for products and industrial facilities or processes. The main objective of this work is to propose a conceptual framework to help researchers to approach optimization under the criteria of sustainability of engineering projects, making use of current Machine Learning techniques. For the development of this conceptual framework, a bibliographic search has been carried out on the Web of Science. From the selected documents and through a hermeneutic procedure the texts have been analyzed and the conceptual framework has been carried out. A graphic representation pyramid shape is shown to clearly define the variables of the proposed conceptual framework and their relationships. The conceptual framework consists of 5 dimensions; its acronym is ADAPTS. In the base are: (1) the Application to which it is intended, (2) the available DAta, (3) the APproach under which it is operated, and (4) the machine learning Tool used. At the top of the pyramid, (5) the necessary Sensing. A study case is proposed to show its applicability. This work is part of a broader line of research, in terms of optimization under sustainability criteria.

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Section: Applicationsmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

“…The conceptual design of products [64] or the early design stage of building [71] are a source of data that can be used in the environmental assessment of products [64] or buildings [65].…”

Section: Datamentioning

confidence: 99%