Movement Tracking-Based In-Situ Monitoring System for Additive Manufacturing

Vasantha, Gokula; Aslan, Ayse; Lapok, Paul; Lawson, Alistair; Thomas, Stuart

doi:10.1007/978-3-031-38241-3_44

Movement Tracking-Based In-Situ Monitoring System for Additive Manufacturing

Vasantha, Gokula; Aslan, Ayse; Lapok, Paul; Lawson, Alistair; Thomas, Stuart

Authors

Dr Gokula Vasantha G.Vasantha@napier.ac.uk
Associate Professor

Ayse Aslan

Dr Paul Lapok P.Lapok@napier.ac.uk
Zero Hour Lecturer

Alistair Lawson A.Lawson@napier.ac.uk
Associate Professor

Stuart Thomas

Abstract

Monitoring and identification of defects during additive manufacturing is mostly done by bespoke optical or acoustic measurement systems. These in-situ monitoring technologies are either intrusive or sensitive to noisy manufacturing environments. We propose a movement tracking-based in-situ monitoring system for additive manufacturing, which is non-intrusive, less sensitive to environmental factors, and easier to operate and maintain. It evaluates the hypothesis that extruder nozzle temperature can be predicted from printer head movement, since temperature and acceleration are correlated due to the printers control unit. Subsequently, this provides an indication of print quality as the extruder temperature plays a vital role. We collected data from experiments using the MakerBot Replicator to examine the hypothesis. Results show that a Random Forest algorithm is more accurate in predicting the temperature variation using head acceleration and time lag temperature data as input parameters, and outperforms a k-Nearest Neighbors and a Vector Autoregression algorithm.

Presentation Conference Type	Conference Paper (Published)
Conference Name	FAIM 2023: Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems
Start Date	Jun 18, 2023
Acceptance Date	Feb 18, 2023
Online Publication Date	Aug 24, 2023
Publication Date	2024
Deposit Date	Mar 21, 2023
Publicly Available Date	Aug 25, 2024
Publisher	Springer
Pages	388-398
Series Title	Lecture Notes in Mechanical Engineering
Series ISSN	2195-4364
Book Title	Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems. Proceedings of FAIM 2023, June 18–22, 2023, Porto, Portugal, Volume 1: Modern Manufacturing
ISBN	9783031382406
DOI	https://doi.org/10.1007/978-3-031-38241-3_44
Keywords	In-process monitoring, 3D Printer, Prediction Modelling, Machine Learning, Fault Detection
Related Public URLs	https://www.faimconference.org/