Additive manufacturing for repairing: from damage identification and modeling to DLD

Abstract

Purpose

This paper aims to decrease the cost of repairing operations, of the damaged mechanical components, by enabling the strong automation of the process and the reduction of manual labor. The main purpose of the hybrid repair process is to restore the original shape of the mechanical parts, by adding and removing material according to the mismatch between the damaged object and the virtual model, to restore its geometrical properties.

Design/methodology/approach

The DUOADD software tool translates the information collected from a 3D scanner into a digital computer aided design solid model, which can be manipulated through Siemens NX computer aided manufacturing (CAM), to obtain the tool paths, for the Direct Laser Deposition (DLD) technology. DUOADD uses octrees to effectively analyze the damaged region of the mechanical part and then to discretize the volume to be added to export CAM-compatible information as a 3D model, for additive operations.

Findings

DUOADD is the missing link between two valuable existing technologies, 3D scan and CAM for additive manufacturing, which can now be connected together, to perform automatic repairing.

Research limitations/implications

A trade-off between resolution and computational effort needs to be achieved.

Practical implications

DUOADD output is a STEP file, transferred to the CAM software to create the additive and the milling tool paths. The maximum deviation was 40 micrometers, as compared with the original solid model.

Originality/value

The paper presents a new procedure and new software tools (DUOADD), for the automation of damaged objects restoration process. DUOADD software provides suitable data for using a 5-axis computer numerical control (CNC) milling machine equipped with a DLD tool.

Citation

Perini, M., Bosetti, P. and Balc, N. (2020), "Additive manufacturing for repairing: from damage identification and modeling to DLD", Rapid Prototyping Journal, Vol. 26 No. 5, pp. 929-940. https://doi.org/10.1108/RPJ-03-2019-0090