By Subramanian Senthilkannan Muthu, Monica Mahesh Savalani

This booklet highlights the sustainability points of additive production (AM) in separate volumes. It describes the main points of this expertise and its implications at the whole product existence cycle sustainability, in addition to embedded carbon and the additional study had to stream this expertise in the direction of sustainable, mainstream construction. Sustainability isn't new for any region of undefined, together with additive production, and there are at the moment a few ongoing study tasks, either in and in educational associations, which are investigating sustainability, embedded carbon and examine actions which might have to be performed sooner or later to maneuver this know-how in the direction of sustainable mainstream production.

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S. M. 1007/978-981-10-0549-7_4 51 52 J. Loy et al. 1 Introduction Product design definitions of sustainability have developed over the last 20 years to encompass an understanding of production systems which track and evaluate the environmental impact of even the smallest manufactured items. In addition, with the widespread adoption of triple-bottom-line accounting as discussed in Cannibals with Forks (Elkington 1999), definitions of sustainability now encompass wide-ranging considerations beyond the environmental impact of products.

6 Parameter settings for CN-GP framework A. Garg et al.  2) in the prediction of TAS and laser energy consumption of the SLS process. The four models (two GP and two CNGP, (7)–(10) in Appendix) are selected.  4.  7 and 8) in prediction of TAS and laser energy consumption of the SLS processes. Predictions obtained are compared to those of the actual data obtained from Nancharaiah et al. (2013). Five statistical metrics (the coefficient of determination (R2), the mean absolute percentage error (MAPE), RMSE, the relative error (%), and the multiobjective error (MO)) are chosen to determine the method that gives the best generalization ability.

A survey study conducted on applications of empirical modeling of 3D printing processes by Garg et al. (2014a) reveals that most attention was paid to improving the product quality/productivity of 3D printing processes (Yang et al. 2002; Chatterjee et al. 2003; Kruth and Kumar 2005; Liao and Shie 2007; Beal et al. 2009; Savalani et al. 2012). Some of the work on the environmental issues in supply chains and logistics has been conducted and solved using multi-criteria decision methods such as Analytic Network Process (Lam 2015; Lam and Lai 2015; Lam and Dai 2015).

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