Reverse logistics optimisation model for end-of-life wind turbine blades waste composites
Rentizelas, A and Trivyza, NL and Lichtenegger, G (2019) Reverse logistics optimisation model for end-of-life wind turbine blades waste composites. In: 25th International Joint Conference on Industrial Engineering and Operations Management, 2019-07-15 - 2019-07-17.
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Abstract
Wind power is a promising renewable source of energy that has been experiencing significant growth over the last decades. The estimated life of the wind turbine blades is approximately 20 years and the first wind farm generations are approaching their end of life, leading to a considerable amount of waste materials from blades in the next years. Most of this material is currently landfilled or incinerated, thus not following a circular economy approach. In order to support more circular economy-oriented solutions, this work proposes a mixed integer linear programming model to optimise the reverse supply network design, from the wind turbine blades location to the end consumer of the recycled product. The developed model is applied on a case study in Europe, by employing data for wind farms from European databases. The output of the case study application is the most cost-efficient network design of the reverse logistics supply chain in Europe. Finally, the benefits of the proposed optimisation model for decision making of the logistics network configuration in a circular economy perspective are discussed.
ORCID iDs
Rentizelas, A ORCID: https://orcid.org/0000-0002-5110-2467, Trivyza, NL ORCID: https://orcid.org/0000-0002-9503-3731 and Lichtenegger, G;-
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Item type: Conference or Workshop Item(Paper) ID code: 69530 Dates: DateEvent15 July 2019Published15 April 2019AcceptedSubjects: Technology > Engineering (General). Civil engineering (General) > Engineering design Department: Strategic Research Themes > Advanced Manufacturing and Materials
Faculty of Engineering > Design, Manufacture and Engineering ManagementDepositing user: Pure Administrator Date deposited: 29 Aug 2019 11:27 Last modified: 12 Dec 2024 16:30 URI: https://strathprints.strath.ac.uk/id/eprint/69530