Predicting downtime costs of tracked hydraulic excavators operating in the UK opencast mining industry

David Edwards, Gary Holt and Frank Harris

Construction Management and Economics, 2002, vol. 20, issue 7, 581-591

Abstract: This paper describes the development of a model to predict the hourly cost of downtime (using regression equations) for tracked hydraulic excavators operating in the UK opencast mining industry. A three-stage process was utilized for the model's development. The first stage predicted machine cycle times, the second predicted hire costs per hour and the third used the outputs of the first two to forecast the cost of breakdown. Both cycle time and hire cost models were revealed to be good predictors, as exhibited by the 'high' R2 values of 0.86 and 0.95, respectively. A plant expert employed within the Defence Logistics Organisation, UK Ministry of Defence, validated these regression models and the process by which downtime costs were predicted. Future research work will aim to enhance the predictive ability of the models developed, expand the research to cover other machine types, and reproduce the findings in graphical and tabular format to improve the interpretation of information generated.

Keywords: Construction Plant; Machine Cycle Time; Productivity; Downtime Cost; Regression Analysis (search for similar items in EconPapers)
Date: 2002
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/01446190210163552 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:conmgt:v:20:y:2002:i:7:p:581-591

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RCME20

DOI: 10.1080/01446190210163552

Access Statistics for this article

Construction Management and Economics is currently edited by Will Hughes

More articles in Construction Management and Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().