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Civil-Comp Proceedings
ISSN 1759-3433 CCP: 9/10
PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON CIVIL AND STRUCTURAL ENGINEERING COMPUTING Edited by: B.H.V. Topping
Paper II.7
Application of Database Management Systems in Productivity Analysis R.M.W. Horner and B.T. Talhouni
Department of Civil Engineering, University of Dundee, UK R.M.W. Horner, B.T. Talhouni, "Application of Database Management Systems in Productivity Analysis", in B.H.V. Topping, (Editor), "Proceedings of the Fourth International Conference on Civil and Structural Engineering Computing", Civil-Comp Press, Edinburgh, UK, pp 69-76, 1989. doi:10.4203/ccp.9.2.7
Abstract
Productivity definitions are numerous but the widely accepted definition in the construction industry is output/input, where output is the actual physically measured progress and input is the manhours to achieve such progress.
On a construction site output involves numerous activities requiring different trades and skills. Even in the same activity there will be a huge number of different tasks each with different output rates. For the purpose of research, a classification system based on material used, function of the item being constructed and the finished product is proposed. Using such a numerically coded classification system, outputs of each individual activity’s task and sub-task and the relevant information affecting each task can be stored in a computerised database on a personal computer. Daily feedback from all monitored construction sites can be stored in the database. Feedback from the sites is by filling in a preprinted set of forms completed daily by the site management and the tradesmen involved in the activity. Data input to the computer is through screen input templates. "ProdCalc" is a program written within the environment of Ashton Tate DBase III Plus to analyze productivity. It consists of a number of modules for various screen templates and productivity calculation and analysis. Module 1 converts various outputs from different tasks to a single output using mensuration indices. Sensitivity of the output to the indices may be checked by interfacing with a spreadsheet. Module 2 calculates productivities daily and weekly. Module 3 produces performance factors relative to a fixed standard specified by the investigator or relative to the generic average productivity calculated from the information held within the database. Module 4 exports certain selected fields for statistical analysis such as analysis of variance and multivariate regression analysis and identifies factors that are detrimental to productivity. Module 5 calculates the adjustment factor needed to discount the effect of the detrimental factors and to convert the data to standard conditions. Adjustment factors are created from within the database by comparing average productivities achieved under the varying design, management and environmental conditions affecting each job. The database is updated by using the adjustment factors. purchase the full-text of this paper (price £20)
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