---
title: "Singapore 3D Printing Centre launches AI platform project to cut PBF parameter development costs"
url: https://www.voxelmatters.com/singapore-3d-printing-centre-launches-ai-platform-project-to-cut-pbf-parameter-development-costs/
date: 2026-03-02
modified: 2026-03-02
lang: en
author: "Davide Sher"
description: "The Singapore Centre for 3D Printing, in collaboration with Fehrmann MaterialsX APAC, launched a research project to reduce the cost and complexity of parameter development for laser powder bed fusion..."
categories:
  - "AM Powders"
  - "AM Research"
  - "Materials"
  - "Metals"
  - "Research & Education"
tags:
  - "future"
image: https://www.voxelmatters.com/wp-content/uploads/2026/03/Fehrman-640x480.jpg
word_count: 287
---

# Singapore 3D Printing Centre launches AI platform project to cut PBF parameter development costs

The [Singapore Centre for 3D Printing](https://www.voxelmatters.directory/company/singapore-centre-3d-printing/), in collaboration with [Fehrmann MaterialsX APAC](https://www.voxelmatters.directory/company/fehrmann-alloys/), launched a research project to reduce the cost and complexity of parameter development for laser powder bed fusion (LPBF), a metal additive manufacturing process in which a laser selectively melts layers of metal powder to build parts. The initiative is funded by NAMIC Singapore, the national additive manufacturing industry body.

The Singapore Centre for 3D Printing, also knows as SC3DP, commenced in December 2014. The Centre is funded by National Research Foundation (NRF), and supported by Nanyang Technological University, Singapore (NTU, Singapore), Economic Development Board (EDB) and external industry partners.

![Explore the SC£DP and Fehrmann partnership for advancing laser powder bed fusion in metal additive manufacturing.](https://www.voxelmatters.com/wp-content/uploads/2026/03/sc3dp-scaled.jpg)

SC3DP aims to become a world leader in 3D Printing and a wellspring of knowledge by attracting leading researchers to the Centre and nurturing a skilled talent pool, establishing strong linkages with and delivering state of the art and innovative solutions to the industry.

Parameter development—the process of identifying the optimal machine settings for a given material and part geometry—can account for up to 15% of overall LPBF production costs, representing a significant barrier to broader industrial adoption. The project will develop a machine-agnostic, cloud-based artificial intelligence platform capable of generating optimized parameter sets tailored to the intended end-use application of a given part.

Unlike conventional parameter selection approaches, the platform will incorporate thermodynamic and process variables that are typically overlooked in standard workflows. The initiative targets industrially relevant alloy classes and is designed to improve print reliability and part consistency across different machine types and production environments.

The stated objectives are to reduce trial-and-error in process setup, lower development costs, improve the mechanical and structural properties of LPBF parts, and accelerate the transition of the technology from a specialist capability to scalable industrial manufacturing.