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Time prediction: an alternative approach

Time prediction: an alternative approach

Mehrtens, Ian Nigel (1988) Time prediction: an alternative approach. MPhil thesis, Thames Polytechnic.

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Abstract

The construction industry and its commercial and industrial clients have become increasingly aware of the importance of time in the planning and construction of projects. A comparison of the construction industries in the UK and the USA concluded that orthodox contract procedures in the UK are largely determined by public sector requirements of accountbility and control, whereas private sector requirements are for speed and a clear allocation of responsibilities and tasks. The important relationship between time and cost has not been studied to any extent in UK practice.

It is clear from the little research that has been undertaken that the subjective methods of time prediction adopted by surveyors in the UK are far from being adequate when it can only be expected that 50% of contracts will meet the stipulated contract period. The problem is one of trying to predict a time period without being able to fully anticipate all possible future events. To date the industry has had no scientific method of making that time prediction, moreover it is often left simply to the judgement of a professional quantity surveyor. In order to provide a better and more effective time and cost control system, it is imperative that a more accurate system or predicting time is devised.

This research then aims to identify the factors affecting the time aspect of construction, to suggest which of those could be anticipated at a given point during the design procedure and to prepare a model whereby the time for construction can be accurately predicted.

Item Type: Thesis (MPhil)
Uncontrolled Keywords: time planning, time prediction, construction projects, construction industry, UK, USA,
Subjects: Q Science > QA Mathematics
Pre-2014 Departments: Thames Polytechnic
Thames Polytechnic > School of Mathematics, Statistics and Computing
Last Modified: 08 Mar 2017 14:27
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/8631

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