Vision-based automated waste audits: a use case from the window manufacturing industry

Pablo Martinez, Osama Mohsen, Mohamed Al-Hussein, Rafiq Ahmad*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Waste auditing is one of the tools used to quantify waste generation in construction processes, especially in industrialized building construction facilities that aim to reduce waste. These audits are organized following a regular schedule to monitor manufacturing activities with respect to the waste generated. However, the identification and quantification of waste through occasional audits of activities at any particular workstation remains a biased, manual, error-prone, and monotonous task. This paper proposes the automation of waste auditing in industrialized construction facilities, using as a case study a cutting station on a window manufacturing line. The waste generated during the cutting process is quantified using contour-based image processing algorithms, and the identification of the material is determined by optimized deep learning classification models. This approach allows the continuous acquisition of waste generation data at the workstation level and enables data-driven waste management decision-making that has the potential to support the reduction of waste in industrialized building construction facilities.

Original languageEnglish
Pages (from-to)7735-7749
Number of pages15
JournalInternational Journal of Advanced Manufacturing Technology
Issue number11-12
StatePublished - Apr 2022
Externally publishedYes

Bibliographical note

Funding Information:
The authors gratefully acknowledge the financial support from the Natural Sciences and Engineering Research Council of Canada (File No. IRCPJ 419145–15).

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.


  • Construction waste
  • Deep learning
  • Machine vision
  • Waste management
  • Window manufacturing

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering


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