Achieving Cognitive Intelligence for Sustainable Advanced Manufacturing

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Sustainable manufacturing is a global imperative, requiring the convergence of materials, manufacturing processes, and engineering design. Manufacturing plays a vital role in the global economy; however, it contributes detrimentally to 20% of carbon emissions. Laser-based advanced manufacturing, primarily additive manufacturing (AM), holds promise for sustainable production despite challenges like cost-effectiveness, energy efficiency, and process stability. The challenge lies in effectively studying critical parameters and incorporating new materials, sensing technologies, advanced modeling, and prediction methods into the manufacturing process’s waste-free and defect-free monitoring and optimization. This research focuses on developing research recommendations in three areas. First, (i) justifying the importance of developing Free and Open-Source Hardware (FOSH) laser-based AM infrastructure to facilitate research exploration, data-sharing, and open research. Second, (ii) exploring the concepts and theories towards integrated data-driven “perceptual intelligence,” model-driven “computational intelligence,” and integrated artificial intelligence methods to achieve cognitive capabilities with explainability and generalizability. Third, (iii) one case study on melt pool monitoring in metal-based AM showcases novel capabilities and limitations in real-time process monitoring using data-driven modeling. Regardless of the complexity and multidisciplinary nature of achieving cognitive intelligence in manufacturing processes, this endeavor will revolutionize advanced manufacturing process modeling and optimization, enabling more sustainable manufacturing processes.

Original languageEnglish
Title of host publicationFlexible Automation and Intelligent Manufacturing
Subtitle of host publicationManufacturing Innovation and Preparedness for the Changing World Order - Proceedings of FAIM 2024
EditorsYi-Chi Wang, Siu Hang Chan, Zih-Huei Wang
PublisherSpringer
Pages28-39
Number of pages12
ISBN (Electronic)978-3-031-74485-3
ISBN (Print)9783031744846
DOIs
Publication statusE-pub ahead of print - 2024
Publication typeA4 Article in conference proceedings
EventInternational Conference on Flexible Automation and Intelligent Manufacturing - Taichung, Taiwan, Province of China
Duration: 23 Jun 202426 Jun 2024

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364

Conference

ConferenceInternational Conference on Flexible Automation and Intelligent Manufacturing
Abbreviated titleFAIM
Country/TerritoryTaiwan, Province of China
CityTaichung
Period23/06/2426/06/24

Keywords

  • Additive Manufacturing
  • Artificial Intelligence
  • Sustainable Manufacturing

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes

Fingerprint

Dive into the research topics of 'Achieving Cognitive Intelligence for Sustainable Advanced Manufacturing'. Together they form a unique fingerprint.

Cite this