Concepedia

TLDR

Experimental work on innovative 3D‑printing‑based rapid casting techniques is scarce in the literature. The study aims to verify the feasibility and dimensional accuracy of two rapid casting solutions—investment casting from 3D‑printed starch patterns and the ZCast process for light‑alloy cavities—using 3D printing technology. Prototypes were produced using benchmark designs, measured with a coordinate‑measuring machine to determine dimensional tolerances, and the predictive performance of CAE software was validated for the ZCast process. Both RC solutions produced cast prototypes quickly and cheaply with dimensional tolerances matching conventional metal casting, and the study provides new data on tolerance determination and CAE predictive performance useful for industrial application.

Abstract

Purpose The purpose of this paper is to verify the feasibility and evaluate the dimensional accuracy of two rapid casting (RC) solutions based on 3D printing technology: investment casting starting from 3D‐printed starch patterns and the ZCast process for the production of cavities for light‐alloys castings. Design/methodology/approach Starting from the identification and design of a benchmark, technological prototypes were produced with the two RC processes. Measurements on a coordinate measuring machine allowed calculating the dimensional tolerances of the proposed technological chains. The predictive performances of computer aided engineering (CAE) software were verified when applied to the ZCast process modelling. Findings The research proved that both the investigated RC solutions are effective in obtaining cast technological prototypes in short times and with low costs, with dimensional tolerances that are completely consistent with metal casting processes. Practical implications The research assessed the feasibility and dimensional performances of two RC solutions, providing data that are extremely useful for the industrial application of the considered technologies. Originality/value The paper deals with experimental work on innovative techniques on which data are still lacking in literature. In particular, an original contribution to the determination of dimensional tolerances and the investigation on the predictive performances of commercial CAE software is provided.

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