Defect-Aware Automation: A Low-Cost IoT Approach to Closed-Loop Control in Additive Manufacturing

Mihai Penica; William O'brien; Adam Dooley; Mangolika Bhattacharya; Vladimir Ghita; Eoin O'connell

doi:10.1109/ISSC67739.2025.11291427

Defect-Aware Automation: A Low-Cost IoT Approach to Closed-Loop Control in Additive Manufacturing

Mihai Penica
, William O'brien
, Adam Dooley
, Mangolika Bhattacharya
, Vladimir Ghita
, Eoin O'connell

Department of Electronics & Computer Engineering

University of Limerick
Illinois State University
University Politehnica of Bucharest

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In the context of Industry 4.0, this study presents a defect-aware, closed-loop manufacturing system that integrates low-cost Internet of Things (IoT) devices with robotic automation to enhance quality control in 3D printing. A custom ESP32-based IoT device continuously monitors environmental and vibrational data to enable early defect detection during the printing process. If the predicted print quality falls below a configurable threshold (60%), the system halts the operation and instructs a UR3 robotic arm to remove the defective part - demonstrating full interoperability within a digital twin framework. The integrated machine learning model provides real-time feedback and autonomous control. More than 50 test scenarios confirmed the system's reliability, with latency remaining well within real-time operational limits. By reducing material waste and energy consumption, the proposed solution offers a scalable and sustainable approach to intelligent additive manufacturing.

Original language	English
Title of host publication	Irish Signals and Systems Conference
Subtitle of host publication	Signalling our Strength, ISSC 2025
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331575939
DOIs	https://doi.org/10.1109/ISSC67739.2025.11291427
Publication status	Published - 2025
Event	35th Irish Signals and Systems Conference, ISSC 2025 - Letterkenny, Ireland Duration: 9 Jun 2025 → 10 Jun 2025

Publication series

Name	Irish Signals and Systems Conference: Signalling our Strength, ISSC 2025

Conference

Conference	35th Irish Signals and Systems Conference, ISSC 2025
Country/Territory	Ireland
City	Letterkenny
Period	9/06/25 → 10/06/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

3D printing
Digital twin
Industrial Internet of Things (IoT)
Industry 4.0
Monitoring system
Sensors
Smart Manufacturing

Access to Document

10.1109/ISSC67739.2025.11291427

Cite this

Penica, M., O'brien, W., Dooley, A., Bhattacharya, M., Ghita, V., & O'connell, E. (2025). Defect-Aware Automation: A Low-Cost IoT Approach to Closed-Loop Control in Additive Manufacturing. In Irish Signals and Systems Conference: Signalling our Strength, ISSC 2025 (Irish Signals and Systems Conference: Signalling our Strength, ISSC 2025). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSC67739.2025.11291427

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title = "Defect-Aware Automation: A Low-Cost IoT Approach to Closed-Loop Control in Additive Manufacturing",

abstract = "In the context of Industry 4.0, this study presents a defect-aware, closed-loop manufacturing system that integrates low-cost Internet of Things (IoT) devices with robotic automation to enhance quality control in 3D printing. A custom ESP32-based IoT device continuously monitors environmental and vibrational data to enable early defect detection during the printing process. If the predicted print quality falls below a configurable threshold (60\%), the system halts the operation and instructs a UR3 robotic arm to remove the defective part - demonstrating full interoperability within a digital twin framework. The integrated machine learning model provides real-time feedback and autonomous control. More than 50 test scenarios confirmed the system's reliability, with latency remaining well within real-time operational limits. By reducing material waste and energy consumption, the proposed solution offers a scalable and sustainable approach to intelligent additive manufacturing.",

keywords = "3D printing, Digital twin, Industrial Internet of Things (IoT), Industry 4.0, Monitoring system, Sensors, Smart Manufacturing",

author = "Mihai Penica and William O'brien and Adam Dooley and Mangolika Bhattacharya and Vladimir Ghita and Eoin O'connell",

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year = "2025",

doi = "10.1109/ISSC67739.2025.11291427",

language = "English",

series = "Irish Signals and Systems Conference: Signalling our Strength, ISSC 2025",

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Penica, M, O'brien, W, Dooley, A, Bhattacharya, M, Ghita, V & O'connell, E 2025, Defect-Aware Automation: A Low-Cost IoT Approach to Closed-Loop Control in Additive Manufacturing. in Irish Signals and Systems Conference: Signalling our Strength, ISSC 2025. Irish Signals and Systems Conference: Signalling our Strength, ISSC 2025, Institute of Electrical and Electronics Engineers Inc., 35th Irish Signals and Systems Conference, ISSC 2025, Letterkenny, Ireland, 9/06/25. https://doi.org/10.1109/ISSC67739.2025.11291427

Defect-Aware Automation: A Low-Cost IoT Approach to Closed-Loop Control in Additive Manufacturing. / Penica, Mihai; O'brien, William; Dooley, Adam et al.
Irish Signals and Systems Conference: Signalling our Strength, ISSC 2025. Institute of Electrical and Electronics Engineers Inc., 2025. (Irish Signals and Systems Conference: Signalling our Strength, ISSC 2025).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Defect-Aware Automation

T2 - 35th Irish Signals and Systems Conference, ISSC 2025

AU - Penica, Mihai

AU - O'brien, William

AU - Dooley, Adam

AU - Bhattacharya, Mangolika

AU - Ghita, Vladimir

AU - O'connell, Eoin

PY - 2025

Y1 - 2025

N2 - In the context of Industry 4.0, this study presents a defect-aware, closed-loop manufacturing system that integrates low-cost Internet of Things (IoT) devices with robotic automation to enhance quality control in 3D printing. A custom ESP32-based IoT device continuously monitors environmental and vibrational data to enable early defect detection during the printing process. If the predicted print quality falls below a configurable threshold (60%), the system halts the operation and instructs a UR3 robotic arm to remove the defective part - demonstrating full interoperability within a digital twin framework. The integrated machine learning model provides real-time feedback and autonomous control. More than 50 test scenarios confirmed the system's reliability, with latency remaining well within real-time operational limits. By reducing material waste and energy consumption, the proposed solution offers a scalable and sustainable approach to intelligent additive manufacturing.

AB - In the context of Industry 4.0, this study presents a defect-aware, closed-loop manufacturing system that integrates low-cost Internet of Things (IoT) devices with robotic automation to enhance quality control in 3D printing. A custom ESP32-based IoT device continuously monitors environmental and vibrational data to enable early defect detection during the printing process. If the predicted print quality falls below a configurable threshold (60%), the system halts the operation and instructs a UR3 robotic arm to remove the defective part - demonstrating full interoperability within a digital twin framework. The integrated machine learning model provides real-time feedback and autonomous control. More than 50 test scenarios confirmed the system's reliability, with latency remaining well within real-time operational limits. By reducing material waste and energy consumption, the proposed solution offers a scalable and sustainable approach to intelligent additive manufacturing.

KW - 3D printing

KW - Digital twin

KW - Industrial Internet of Things (IoT)

KW - Industry 4.0

KW - Monitoring system

KW - Sensors

KW - Smart Manufacturing

UR - https://www.scopus.com/pages/publications/105032409549

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DO - 10.1109/ISSC67739.2025.11291427

M3 - Conference contribution

AN - SCOPUS:105032409549

T3 - Irish Signals and Systems Conference: Signalling our Strength, ISSC 2025

BT - Irish Signals and Systems Conference

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 9 June 2025 through 10 June 2025

ER -

Penica M, O'brien W, Dooley A, Bhattacharya M, Ghita V, O'connell E. Defect-Aware Automation: A Low-Cost IoT Approach to Closed-Loop Control in Additive Manufacturing. In Irish Signals and Systems Conference: Signalling our Strength, ISSC 2025. Institute of Electrical and Electronics Engineers Inc. 2025. (Irish Signals and Systems Conference: Signalling our Strength, ISSC 2025). doi: 10.1109/ISSC67739.2025.11291427

Defect-Aware Automation: A Low-Cost IoT Approach to Closed-Loop Control in Additive Manufacturing

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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