Optimal design of deep back relief in ceramic floorings by means of the finite element method

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The ceramic tile industry faces up to a saturated market and needs to offer innovative products constantly, competitive in quality and optimal from the economic and environmental point of view. Ceramic tiles lightened by the execution of a deep back relief could be manufactured with less raw material than the traditional one, which has an effect in the saving of weight and energy. Additionally, a lighter final product improves working conditions on the shopfloor and at the building site. Nevertheless, lightened tiles are structurally different, and so is their mechanical and thermic behaviour. Because it is a constructive element it is necessary to know its response under typical loads and assure fulfilment of the valid standards. This paper aims at the objective of evaluating lightened ceramic floorings employing solid three-dimensional modelling and finite elements method (FEM), establishing an optimal definition of the back relief. In order to achieve this objective, 1 reference model and 56 different relief versions were defined, which underwent 4 structural tests. After deciding that both mass and principal stresses (Rankine criterion), were the magnitudes to consider in the study, the maximal stresses of each version for each test were calculated, as much as their distribution. Next, 4 comparison coefficients were defined and a suitability order was established. Finally, thanks to the collaboration with a ceramic company it was verified that the employed methodology was appropriate. Altogether, it has been concluded that lightened tiles could improve both raw material consumption and structural response simultaneously. A set of fundamental behaviour guidelines has been extracted and could be taken as a basis for the back relief design of any enterprise. Regardless these guidelines, this paper proposes a methodology for the geometric evaluation of floorings that could be extended to other kinds of products and design variables.

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