Innovation designs of industry 4.0 based solid waste management: Machinery and digital circular economy

Chor Gene Cheah, Wen Yi Chia, Shuet Fen Lai, Kit Wayne Chew*, Shi Reen Chia, Pau Loke Show

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

75 Citations (Scopus)

Abstract

The Industrial Revolution 4.0 (IR 4.0) holds the opportunity to improve the efficiency of managing solid waste through digital and machinery applications, effectively eliminating, recovering, and repurposing waste. This research aims to discover and review the potential of current technologies encompassing innovative Industry 4.0 designs for solid waste management. Machinery and processes emphasizing on circular economy were summarized and evaluated. The application of IR 4.0 technologies shows promising opportunities in improving the management and efficiency in view of solid waste. Machine learning (ML), artificial intelligence (AI), and image recognition can be used to automate the segregation of waste, reducing the risk of exposing labour workers to harmful waste. Radio Frequency Identification (RFID) and wireless communications enable the traceability in materials to better understand the opportunities in circular economy. Additionally, the interconnectivity of systems and automatic transfer of data enable the creation of more complex system that houses a larger solution space that was previously not possible such as centralised cloud computing to reduce the cost by eliminating the need for individual computing systems. Through this comprehensive review-based work, innovative Industry 4.0 components of machinery and processes involving waste management which focuses on circular economy are identified with the critical ones evaluated briefly. It was found that the current research and work done is based on applying Industry 4.0 technologies on individual waste management systems, which lacks the coherency needed to capitalise on technologies such as cloud computing, interconnectivity, big data, etc on a larger scale. Therefore, a real world comprehensive end-to-end integration aimed to optimize every process within the solid waste management chain should be explored.

Original languageEnglish
Article number113619
JournalEnvironmental Research
Volume213
DOIs
Publication statusPublished - Oct 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 Elsevier Inc.

ASJC Scopus Subject Areas

  • Biochemistry
  • General Environmental Science

Keywords

  • Artificial intelligence (AI)
  • Industrial revolution 4.0
  • Internet of things (IoT)
  • Machine learning (ML)
  • Solid waste management

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