Papanikolaou, MichailPagone, EmanueleSalonitis, KonstantinosJolly, Mark R.Makatsoris, Makatsoris2019-01-022019-01-022018-12-01Papanikolaou M, Pagone E, Salonitis K, et al., (2019) A computational framework towards energy efficient casting processes. In: Dao D., et al., (Eds) Sustainable Design and Manufacturing 2018. KES-SDM 2018. Smart Innovation, Systems and Technologies, Volume 130, pp. 263-276978-3-030-04289-9https://doi.org/10.1007/978-3-030-04290-5_27https://dspace.lib.cranfield.ac.uk/handle/1826/13766Casting is one of the most widely used, challenging and energy intensive manufacturing processes. Due to the complex engineering problems associated with casting, foundry engineers are mainly concerned with the quality of the final casting component. Consequently, energy efficiency is often disregarded and huge amounts of energy are wasted in favor of high quality casting parts. In this paper, a novel computational framework for the constrained minimization of the pouring temperature is presented and applied on the Constrained Rapid Induction Melting Single Shot Up-Casting (CRIMSON) process. Minimizing the value of the pouring temperature can lead to significant energy savings during the melting and holding processes as well as to higher yield rate due to the resulting reduction of the solidification time. Moreover, a multi-objective optimization component has been integrated into our scheme to assist decision makers with estimating the trade-off between process parameters.enAttribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/CRIMSONSustainabilityComputational frameworkSand castingConference paper