Process Data-Based Knowledge Discovery in Additive Manufacturing of Ceramic Materials by Multi-Material Jetting (CerAM MMJ)

Valentin Lang,Robert Johne,Steffen Ihlenfeldt,Hajo Wiemer,Alexander Michaelis,Felix Glausch,Steven Weingarten,Uwe Scheithauer

doi:10.3390/jmmp4030074

Abstract

Multi-material jetting (CerAM MMJ, previously T3DP) enables the additive manufacturing of ceramics, metals, glass and hardmetals, demonstrating comparatively high solid contents of the processed materials. The material is applied drop by drop onto a substrate. The droplets can be adapted to the component to be produced by a large degree of freedom in parameterization. Thus, large volumes can be processed quickly and fine structures can be displayed in detail, based on the droplet size. Data-driven methods are applied to build process knowledge and to contribute to the optimization of CerAM MMJ manufacturing processes. As a basis for the computational exploitation of mass sensor data from the technological process chain for manufacturing a component with CerAM MMJ, a data management plan was developed with the help of an engineering workflow. Focusing on the process step of green part production, droplet structures as intermediate products of 3D generation were described by means of droplet height, droplet circularity, the number of ambient satellite particles, as well as the associated standard deviations. First of all, the weighting of the factors influencing the droplet geometry was determined by means of single factor preliminary tests, in order to be able to reduce the number of factors to be considered in the detailed test series. The identification of key influences (falling time, needle lift, rising time, air supply pressure) permitted an optimization of the droplet geometry according to the introduced target characteristics by means of a design of experiments.

Highlights

Producing businesses participate in a global supply market and deal with a dynamization in manufacturing associated with personalized products through shorter product cycles and smaller quantities of individual product variants [1,2,3]
The DMAIC methodology proposes in the first phase the definition of the target condition [43]
A holistic approach to process data management was applied to assist an analysis of multi-material jetting (CerAM MMJ), whereby the quality descriptive target characteristics and suitable measuring equipment for recording them were assigned to the steps of the manufacturing process

Summary

Introduction

Producing businesses participate in a global supply market and deal with a dynamization in manufacturing associated with personalized products through shorter product cycles and smaller quantities of individual product variants [1,2,3]. The technology enables design optimization combined with the ability to produce custom parts on demand. This has led to an increasing number of single parts and small batches of complex components, often with functional integration, being produced using 3D printing [5]. Suspension, paste or feedstock-based processes are used to produce components with high density. In these processes, the powdered raw materials are first homogeneously dispersed in a binder system, since these dispersions can be applied very well, despite a high packing density. It is possible to deposit droplets of different materials side by side and manufacture multi-material components [15,16]

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Conclusion