CoChat
Sign Up
Cited by 113BIM and Construction IntegrationSustainable Supply Chain ManagementSustainable Design and Development

Smart steel: new paradigms for the reuse of steel enabled by digital tracking and modelling

Ness, David, Swift, John, Ranasinghe, Damith C., Xing, Ke, Soebarto, Veronica·2015·Journal of Cleaner Production
DOI 10.1016/j.jclepro.2014.08.055
Open this paper in CoChat — free account

Integrity signals

Registry

Crossref · 10.1016/j.jclepro.2014.08.055

Cites

48 of 48 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Ness et al. (2015) estimate that embodied energy savings of 9.98 MJ/kg of steel are possible by reusing rather than recycling, based on a case study of a former manufacturing plant.

    “They argue that improved traceability of steel and the storage of key data over the building lifetime will unlock the residual steel at end-of-life, and estimate that embodied energy savings of 9.98 MJ/kg of steel are possible by reusing rather than recycling, based on a case study of a former manufacturing plant.”

    From Understanding and overcoming the barriers to structural steel reuse, a UK perspective (2017) · cites this paper as Ness et al. (2015)

  • High costs involved in maintaining RFID readability or a BIM model over the life of a building may prevent the uptake of this strategy, given a visual inspection and creation of a deconstruction plan is a potentially low cost option.

    “However, the high costs involved in maintaining a RFID readability or a BIM model over the life of a building, may prevent the uptake of this strategy, given a visual inspection and creation of a deconstruction plan is a potentially low cost option.”

    From Understanding and overcoming the barriers to structural steel reuse, a UK perspective (2017) · cites this paper as Ness et al. (2015)

  • Ness et al suggest the use of radio frequency tagging of components and the use of building information modeling to track components and assemblies and import them into building design software at the design stage.

    “Ness et al [94] suggest the use of radio frequency tagging of components and the use of building information modeling to track components and assemblies and import them into building design software at the design stage.”

    From Material efficiency strategies to reducing greenhouse gas emissions associated with buildings, vehicles, and electronics—a review (2019) · cites this paper as [94]

  • Digital tracking and modelling devices, sensors, sensing devices and programmable logic controllers, hybrid genetic algorithms, and automated optical sorting are already utilized in recycling and reuse circular approaches.

    “digital tracking and modelling devices used in the steel industry [121], sensors employed for thin-film photovoltaic (PV) technologies [122] and on buildings [123], sensing devices and programmable logic controllers for a steel industrial complex for water [124], hybrid genetic algorithms employed on household appliances [125], and automated optical sorting for recycled glass [126].”

    From Digitisation and the Circular Economy: A Review of Current Research and Future Trends (2018) · cites this paper as [121]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Ness, D., Swift, J., Ranasinghe, D. C., Xing, K., & Soebarto, V.
Affiliations
  • University of South Australia (AU)
  • The University of Adelaide (AU)
Corresponding author
Ness, David
ORCID
Venue
Journal of Cleaner Production
Publisher
Elsevier BV
Published
2015-07
Volume
98
Pages
292-303
ISSN
0959-6526 (ISSN-L)
DOI
10.1016/j.jclepro.2014.08.055
OpenAlex
W2073536397
Cited by
113
References
48
Citations by year
2026: 4 · 2025: 9 · 2024: 10 · 2023: 7 · 2022: 12 · 2021: 15 · 2020: 14 · 2019: 15 · 2018: 13 · 2017: 2 · 2016: 7 · 2015: 4 · 2014: 1
FWCI
6.92
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Journal of Cleaner Production (publishedVersion)
  • Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
Topics
  • Physical Sciences › Engineering › Building and Construction › BIM and Construction Integration
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Sustainable Supply Chain Management
  • Physical Sciences › Engineering › Building and Construction › Sustainable Design and Development
Keywords
disassembly, take-back, RFID, building information modeling, stress sensors, resource efficiency, industrial buildings, greenhouse gas emissions, energy consumption, steel recycling, business models, digital tracking

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review