Smart Industrial Internet of Things Framework for Composites Manufacturing

Author:

Chai Boon Xian1ORCID,Gunaratne Maheshi1,Ravandi Mohammad1,Wang Jinze1ORCID,Dharmawickrema Tharun1ORCID,Di Pietro Adriano1,Jin Jiong2ORCID,Georgakopoulos Dimitrios3ORCID

Affiliation:

1. Aerostructures Innovation Research Hub (AIR Hub), Swinburne University of Technology, Hawthorn, VIC 3122, Australia

2. School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC 3122, Australia

3. ARC Industrial Transformation Research Hub for Future Digital Manufacturing, Swinburne University of Technology, Hawthorn, VIC 3122, Australia

Abstract

Composite materials are increasingly important in making high-performance products. However, contemporary composites manufacturing processes still encounter significant challenges that range from inherent material stochasticity to manufacturing process variabilities. This paper proposes a novel smart Industrial Internet of Things framework, which is also referred to as an Artificial Intelligence of Things (AIoT) framework for composites manufacturing. This framework improves production performance through real-time process monitoring and AI-based forecasting. It comprises three main components: (i) an array of temperature, heat flux, dielectric, and flow sensors for data acquisition from production machines and products being made, (ii) an IoT-based platform for instantaneous sensor data integration and visualisation, and (iii) an AI-based model for production process forecasting. Via these components, the framework performs real-time production process monitoring, visualisation, and prediction of future process states. This paper also presents a proof-of-concept implementation of the framework and a real-world composites manufacturing case study that showcases its benefits.

Funder

Victorian Higher Education State Investment Fund

Publisher

MDPI AG

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