Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/90058
| Title: | A field survey of hand–arm vibration exposure in the UK utilities sector | Authors: | Edwards, DJ Rillie, I Chileshe, N Lai, J Hosseini, MR Thwala, WD |
Issue Date: | 2020 | Source: | Engineering, construction and architectural management, 2020, v. 27, no. 9, p. 2179-2198 | Abstract: | Purpose: Excessive exposure to HAV can lead to hand–arm vibration syndrome (HAVS) which is a major health and well-being issue that can irreparably damage the neurological, vascular and muscular skeletal system. This paper reports upon field research analysis of the hand–arm vibration (HAV) exposure levels of utility workers in the UK construction sector when operating hand-held vibrating power tools. Design/methodology/approach: An empirical epistemological lens was adopted to analyse primary quantitative data on the management of hand-held tool trigger times (seconds) collected from field studies. To augment the analysis further, an interpretivist perspective was undertaken to qualitatively analyse interviews held with the participating company's senior management team after field study results. This approach sought to provide further depth and perspective on the emergent numerical findings. Findings: The findings reveal that none of the operatives were exposed above the exposure limit value (ELV) and that 91.07% resided under the exposure action value (EAV). However, the Burr four parameter probability model (which satisfied the Anderson–Darling, Kolmogorov–Smirnov and chi-squared goodness of fit tests at (Formula presented.) 0.01, 0.02, 0.05, 0.1 and 0.2 levels of significance) illustrated that given the current data distribution pattern, there was a 3% likelihood that the ELV will be exceeded. Model parameters could be used to: forecast the future probability of HAV exposure levels on other utility contracts and provide benchmark indicators to alert senior management to pending breaches of the ELV. Originality/value: HAV field trials are rarely conducted within the UK utilities sector, and the research presented is the first to develop probability models to predict the likelihood of operatives exceeding the ELV based upon field data. Findings presented could go some way to preserving the health and well-being of workers by ensuing that adequate control measures implemented (e.g. procuring low vibrating tools) mitigate the risk posed. |
Keywords: | Hand-arm vibration Health and well-being Industry 4.0 Probability models Utilities industry |
Publisher: | Emerald Group Publishing Limited | Journal: | Engineering, construction and architectural management | ISSN: | 0969-9988 | EISSN: | 1365-232X | DOI: | 10.1108/ECAM-09-2019-0518 | Rights: | © Emerald Publishing Limited This is a submitted version of an article accepted for publication in Engineering, Construction and Architectural Management. The version of record Edwards, D.J., Rillie, I., Chileshe, N., Lai, J., Hosseini, M.R. and Thwala, W.D. (2020), "A field survey of hand–arm vibration exposure in the UK utilities sector", Engineering, Construction and Architectural Management, Vol. 27 No. 9, pp. 2179-2198 is available online at: https://dx.doi.org/10.1108/ECAM-09-2019-0518. This submitted version is provided for your own personal use only. It may not be used for resale, reprinting, systematic distribution, emailing, or for any other commercial purpose without the permission of the publisher |
| Appears in Collections: | Journal/Magazine Article |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| a0674-n05_Edwards_field_survey_hand.pdf | Preprint version | 1.24 MB | Adobe PDF | View/Open |
Page views
97
Last Week
0
0
Last month
Citations as of Apr 14, 2025
Downloads
47
Citations as of Apr 14, 2025
SCOPUSTM
Citations
56
Citations as of Dec 19, 2025
WEB OF SCIENCETM
Citations
43
Citations as of Oct 10, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.



