DEVELOPING REGRESSION BASED APPROXIMATE QUANTITIES MODELS FOR QUANTIFICATION OF ELECTRICAL CABLES FOR RESIDENTIAL BUILDING CONSTRUCTION IN NIGERIA
Journal Title: Engineering and Technology Journal - Year 2019, Vol 4, Issue 5
Abstract
In quantity surveying practice, the building and engineering standard method of measurement 4th edition stipulates that electrical final circuits should be enumerated during quantity take-off of electrical cables. This approach poses challenges during estimation and material scheduling because it does not readily provide the quantity (length) and estimate of cables needed for the electrical installation works. This study was aimed at developing regression based approximate quantities models which can be used by quantity surveyors to predict lighting and power electrical cables quantities for proposed residential building projects. Take-off(measurement) of thirty architectural and electrical drawings designed by registered architects and electrical engineers was carried out to obtain data on the number of lighting points and socket outlets as well as the corresponding length of cables, which was further validated by an experienced quantity surveyor and electrical engineer and analysed using linear regression. Two linear regression models were generated as follows (1) PC qty = 317.237 + 14.358 SOqty, Where: PC qty = power cable quantities (in metres); SOqty= number of socket outlets (2) LC qty = 363.867 + 13.518 LPqty Where: LC qty = Lighting cable quantities(in metres); LPqty= number of lighting points. These models have time saving potentials, but their efficacy relies heavily on the accurate measurement of the number of lighting and power points. These models are recommended for use by practicing quantity surveyors to generate realistic feasibility estimates of electrical cables and beat short tender deadlines.
Authors and Affiliations
Dr. Ogunsina Olusola, Dr. Ugochukwu, Stanley C. , Oguejiofor Josiah E. , Dr. Agu Nathan N.
Keywords
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- EP ID EP705207
- DOI 10.31142/etj/v4i5.01
- Views 78
- Downloads 0
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