Adaptive neuro-fuzzy and regression models for predicting microhardness and electrical conductivity of solid-state recycled EN AW 6082

Author:

Krolo JureORCID,Lela Branimir,Švagelj Zrinka,Jozić Sonja

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Reference41 articles.

1. Allwood JM, Cullen JM, Carruth MA (2012) Sustainable materials with both eyes open. UIT Cambridge ISBN 190686005X, 9781906860059

2. International Aluminium Institute (2009) Global aluminium recycling: a cornerstone of sustainable development. Online: http://www.world-aluminium.org/publications/ . Accessed 23 August 2017

3. Duflou JR, Tekkaya AE, Haase M, Welo T, Vameemsel K, Kellens K, Dewulf W, Paraskevas D (2015) Environmental assessment of solid state recycling routes for aluminium alloys: can solid state processes significantly reduce the environmental impact of aluminium recycling? CIRP Ann Manuf Technol 64:37–40

4. Gronostajski J, Marciniak H, Matuszak A (2000) New methods of aluminium and aluminium-alloy chips recycling. J Mater Process Technol 106:34–39

5. Paraskevas D et al (2016) 4.10 resource efficiency in manufacturing: identifying low impact paths. The 10th global conference on sustainable manufacturing, pp 271-276

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