Modelling the magnitude of plant downtime: A tool for improving plant operations management

David J. Edwards, Silas Yisa

Research output: Contribution to journalReview articlepeer-review

5 Citations (Scopus)


Utilization of off-highway vehicles forms an essential part of UK industry's efforts to augment the productivity of plant operations and reduce production costs. However, uninterrupted utilization of plant and equipment is requisite to reaping the maximum benefit of mechanization; one particular problem being plant breakdown duration and its impact upon process productivity. Predicting the duration of plant downtime would enable plant managers to develop suitable contingency plans to reduce the impact of downtime. This paper presents a stochastic mathematical modelling methodology (more specifically, probability density function of random numbers) which predicts the probable magnitude of ‘the next’ breakdown, in terms of duration for tracked hydraulic excavators. A random sample of 33 machines was obtained from opencast mining contractors, containing 1070 observations of machine breakdown duration. Utilization of the random numbers technique will engender improved maintenance practice by providing a practical methodology for planning, scheduling and controlling future plant resource requirements. The paper concludes with direction for future research which aims to: extend the model's application to cover other industrial settings and plant items; to predict the time at which breakdown will occur (vis-à-vis the duration of breakdown); and apply the random numbers modelling to individual machine compartments.

Original languageEnglish
Pages (from-to)225-232
Number of pages8
JournalEngineering, Construction and Architectural Management
Issue number3
Publication statusPublished - 1 Mar 2001
Externally publishedYes


  • Breakdown duration
  • Linear interpolation
  • Plant operations management
  • Probability
  • Stochastic random numbers
  • Tracked hydraulic excavators

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Architecture
  • Building and Construction
  • General Business,Management and Accounting


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