Innovative clearance data model for demining operational data collection: insights from field trials in Zimbabwe

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dc.contributor.authorEvans, Roly
dc.contributor.authorBold, Mikael
dc.contributor.authorNelson, Liz
dc.contributor.authorTemple, Tracey
dc.date.accessioned2025-01-09T15:17:32Z
dc.date.available2025-01-09T15:17:32Z
dc.date.freetoread2025-01-09
dc.date.issued2024-12-15
dc.date.pubOnline2024-11-29
dc.description.abstractFrom September 2023 to March 2024 a field trial on a live manual demining site was conducted to test a new and innovative approach for the collection and analysis of operational data. The approach, titled the Clearance Data Model, involved the collection of sixty-six data attributes for each mine found. For the first time the mine itself would become the accountable unit of demining data, against which an expanded range of relevant attributes particular to that specific mine would be recorded. This novel approach represented a considerable expansion to the operational data collected concerning Victim Operated Explosive Devices such as mines, booby-traps and victim operated Improvised Explosive Devices from the field. Previously few if any details about individual accountable mines were collected. The trial proved that is it entirely practical to collect such levels of data without impeding operational efficiency. It also showed that such data has significant benefits for quantitative operational risk management, as well as overall operations and quality management. For example, the recording of mine depth alongside excavation times enables oversight of individual excavation speed and management of any risk identified.
dc.description.journalNameHeliyon
dc.format.mediumElectronic-eCollection
dc.identifier.citationEvans R, Bold M, Nelson L, Temple T. (2024) Innovative clearance data model for demining operational data collection: insights from field trials in Zimbabwe. Heliyon, Volume 10, Issue 23, December 2024, Article number e40538
dc.identifier.eissn2405-8440
dc.identifier.elementsID559676
dc.identifier.issn2405-8440
dc.identifier.issueNo23
dc.identifier.paperNoe40538
dc.identifier.urihttps://doi.org/10.1016/j.heliyon.2024.e40538
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/23339
dc.identifier.volumeNo10
dc.languageEnglish
dc.language.isoen
dc.publisherElsevier
dc.publisher.urihttps://www.sciencedirect.com/science/article/pii/S2405844024165693?via%3Dihub
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject3509 Transportation, Logistics and Supply Chains
dc.subject40 Engineering
dc.subject35 Commerce, Management, Tourism and Services
dc.titleInnovative clearance data model for demining operational data collection: insights from field trials in Zimbabwe
dc.typeArticle
dc.type.subtypeJournal Article
dcterms.coverageEngland
dcterms.dateAccepted2024-11-18

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