HTML:Labour Output of Steel Fixers in Selected Building Construction Sites In Malaysia

 

Research Article

 

 

Labour Output of Steel Fixers in Selected Building Construction Sites In Malaysia

Oko John Ameh

 

Department of Building, University of Lagos, Nigeria

 

ARTICLE INFO Article history

Received: 10/11/2012  

Accepted: 31/01/2013

 

A b s t r a c t
This study investigates labour output of steel fixers in in-situ concrete storey building construction on selected sites in Lagos state. The main aim of the study is to aid the estimation of labour cost of steel works in reinforced concrete construction and to provide information for planning and schedule of work. Data were collected from twenty (20) construction sites through work study and activity sampling. The investigation reveals that a proficient steel fixer, averagely motivated is capable of cutting and bending one tonne of steel using simple hand tools for beams, columns, stairs and floor slabs in 41.58 hours, 24.10 hours, 25.06 hours and 27.05 hours respectively. He is also capable of tying one tonne of steel rods into the same structural elements aforementioned in 67.70 hours, 35.20 hours, 25.10 hours and 45.60 hours respectively. Furthermore, steel fixers use 75.1% of their working time effectively while 24.9% of same is used ineffectively. It is recommended that labour output obtained in this study be adapted as local substitute for the British Standard labour rate currently in use.  

 

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Keywords:Building construction, Labour output, Steel fixers, work study, Nigeria;  

 

1. Background of the Study

Productivity is commonly defined as a ratio between an output value and an input value used to produce the output. Output consists of products or services and input consists of materials, labour, capital, energy, etc. There is nothing as dangerous to an economy as a decrease in productivities because it creates inflationary pressure, social conflict, and mutual suspicion (Drucker, 1980). There are diverse reasons for embarking on productivity studies in the construction industry. First, it may be for detailed estimating and project scheduling, which measures the input as labour hours and the output as installed quantities (Dozzi and AbouRizk 1993). Second, productivity may be measured to identify industry trends and to allow performance comparisons with other industry sectors (BFC 2006) and third, Company-level or project-level productivity measurement provides internal and external benchmarks for comparison with company or project norms (Park et al. 2005; Ellis and Lee 2006). Jarkas (2010) argued that, since construction is a labour-intensive industry, manpower is the only productive resource, thus construction productivity is mainly dependent on human effort and performance. In most countries, construction labour cost comprises 30% – 50% of the overall project’s cost (Jarkas et al, 2012). Over the years, consultants and contractors relies on personal judgment and productivity data based on craftsmen output in the UK for labour cost estimate of civil and building works in Nigeria (Ayeni, 1992 p12). This is not only misleading but a contentious issue in view of the fact that, the construction industry of most developing countries still maintains a low level of mechanization on the construction sites, and at the same time, factors that influence labour productivity varies from one country to another. Besides, productivity data used over time were rarely amended or revised and hence subject to considerable uncertainty.  Earlier studies revealed that outputs of labour in the Nigeria construction industry are much lower than those of their counterparts in the United States of America and United Kingdom (Ayandele, 1997).  In specific terms Edmond (1974) reported an output of 2.93 and 4.18 square metre per man-day for formwork to soffits and walls respectively in Nigeria as against output of 10.87 and 13.38 square metre respectively for the same activity in United Kingdom.  In  Wahab’s  study, it was shown that the man-days per square metre in Nigeria varied from 6.44 to 16.78 as against 2.33 for U.K, 3.28 for Ireland and 1.53 for USA.

The steel fixer is one who specializes in the cutting, bending and fixing of steel reinforcement into forms and in accordance to specification. Reinforcement fixing is highly labour intensive and time consuming. The cost of the rebar trade is approximately one third of the overall cost of the reinforced concrete frame (Illingworth, 2000), of which the cost of labour comprises approximately 30%. The fixing operation in beams is associated with added difficulty because of the space confinement of formwork moulds in which reinforcement is fixed, and the variability of reinforcing bar diameters, locations and details. However, for structural elements such as foundations, slabs, and to a large extent columns and walls, the fixing operation takes place in a relatively open and accessible space, thus for an approximately equal quantity of reinforcement, it is usually characterized by smaller gang sizes and shorter duration. In view of the absence of a local standard for measuring the outputs of steel fixers, the focus of this study is to determine the output of steel fixers in cutting, bending and placing reinforcing bars into structural elements (beams, column, floor slabs and stair) and to determine the percentage of time spent productively on site. The value of this research is that, apart from its usefulness in preliminary advice to the client and in preparation of labour estimate for steel fixers based on Nigerian craftsmen capacity, it will be useful to the contractors when decision regarding the adequacy of crew size and award of bonus incentives scheme to deserving workers that put in work in excess of the set standard has to be taken. It will also enable the planning engineer to maintain basic productivity rate and likewise enhance the assessment of sub-contractors nationally.

 

2. Literature Review

Labour productivity is influenced by various factors present at the project site. These factors are very difficult to consider during the measurement and estimation of production rates because of its variable nature and uniqueness of every project. Ameh and Odusami (2002) identified low wages, lack of materials and unfriendly working atmosphere as having key impact on productivity of craftsmen involved in in-situ concrete operation in single storey building projects in Nigeria.  Makulsawatudom et al. (2004) established 10 most significant factors affecting construction productivity in Thailand and they include lack of materials, incomplete drawings, incompetent supervisors, lack of tools and equipment, absenteeism, poor communication, instruction time, poor site layout, inspection delay and rework. Enshassi et al.’s (2007) study in the Gaza Strip identified the five most important factors that impact negatively on labour productivity as material shortages, lack of experience of labour, lack of labour surveillance, and alteration of drawings/specification during execution. The major categories of factors in Dai et al.’s (2009) study of craft workers perception of 83 factors that affect their productivity in the US revolve around availability of tools and consumables, materials, construction equipment and engineering drawing management.

Reinforcement in concrete may be steel bars or mesh fabric. The steel bars are usually classified or manufactured on account of their strength as:

*          Mild steel, which is usually round in section and plain, but could be deformed.

*          High yield which is usually deformed.

High yield bars are almost twice as strong as mild steel for the same diameter. This factor enables designers to achieve reduction in the overall sectional area of steel reinforcement in concrete by using high yield rod. Reinforcing bars are rolled in ten standard diameters as shown in the Table 1 below:

Table 1: Standard reinforcing Bars in Nigeria Market

                                    SIZES

Mm

Inches

Weight Kg/m

6

¼

0.222

8

5/16

0.375

10

5/8

0.616

12

½

0.888

16

5/8

1.579

20

¾

2.466

25

1

3.854

32

6.313

40

9.864

50

2

15.413

The common tools used by steel fixers in Nigeria are: (a) Pincers: This is a tool consisting of two hinged arms, for gripping and for cutting binding wire. (b) Bender: This is another important tool used by the steel fixer, formed and welded into F-shape using high yield steel bar, mainly used in bending reinforcement into the required shape so as to fit into the forms easily. (c ) Hacksaw: It is a hand saw used for cutting metal. (d) Measuring Tape: Used for measuring steel bar, size of forms etc.

Cutting and bending, and fixing of reinforcement are two distinct activities which could be performed by two different gangs on site. Alternatively, the reinforcement could be pre-assembled into cages off-site, transported and lifted into position using mechanical hoist. The commonest method of tying reinforcing rode is using the soft iron binding wire at selected intersection of main bars and links or stirrups in the appropriate structural element using the pincer.

In the context of labour productivity, the input to an activity is measured by the direct labour hours charged to the activity. Several methods have evolved for improving the construction productivity based on the motion and time study (Thomas and Daily,1983). Some examples of such methods are stopwatch study, photographic method, taping video, time-lapse video. Other method of productivity measurement is work-sampling and five minutes rating.

3.  Research Method

The aim of the study was to establish a standard labour output that will serve as a data base for computation of labour cost estimation in Nigeria. The choice of Lagos as the study area benefits the study because it permits the sampling of a large population of craftsmen in construction firms. Lagos is located in South-West Nigeria. Being a former federal capital and now the commercial nerve centre of the country, Lagos hosts many of the reputable construction companies operating in Nigeria. Lagos is listed as one of the 25 megacities of the World with an estimated population of about 17million in 2007 and a growth rate (3.2%) which has an attendant pressure on its infrastructure. There are numerous construction projects in Lagos executed by both the private and public sector to meet the housing, economic and infrastructure requirements of the emerging megacity.

Two approaches adopted for measuring steel workers’ productivity are activity sampling and work study. Activity sampling is used to determine the proportion of time spent by a gang of workers productively or un-productively. The equipment used was mainly stopwatch, pencil, calculator and activity sampling sheet (Groover, 2007 p. 341). These studies were observed on different days but starting at the same time and stopped at the same time in all the sites visited for observation. An observation interval of ten minutes was used between 9.30am – 3.20pm. A total of 25 observations per steel fixers in a day was made. Time study measures the time required to perform a given task in accordance with a specified method.

The data for this study was collected from twenty (20) building construction sites within Lagos metropolis. Considering the fact that only one trade (steel fixing) is involved, the sample size of 20 building construction sites is large and adequate enough to draw any reasonable conclusion. The activities of the iron fixer were divided into two tasks groups. The first group involves cutting and bending steel rods while the second group involves placing and tying steel rods into the appropriate structural forms for beams, columns, stairs and floor slabs. Decimal minute stop watch was used to record the time productively spent by a gang of steel fixer to cut and bend one tonne of steel as well as placing and tying a tonne of steel in specified structural form. All the steel fixers were averagely skilled, averagely motivated and of good physical health. The tools used were simple hand tools consisting of 15 metre tape, pincers, F-shaped high yield iron for bending bars, and hack saws.

4. Result

From the biographical information of the respondents presented in Table 2, four level of education were identified and used for the study. The response indicate that ten percent of the steel fixers had no basic education, 20% have trade test, 23.3% have ordinary level school certificate while 46.7% have primary school leaving certificate. It can be observed that the steel fixers were not will educated academically. The implication of this on the steel workers ability for critical reasoning and ability to make independent judgment is grievous.  On the total number of years each steel fixer have spent on the Job, only 25% of the respondent have over 16 years work experience 15% have below 5 years on the job experiences, 28.3% have between 5 and 10 years experience and 31.7% have between 11 and 15 years experience. The model class for the years of experience is between 11 – 15 years, which indicate adequate level of exposure to the task. The age distribution of the steel fixers that participated in the study indicate that very few (six percent) of the steel fixers were below 20 years. This category were in the minority. They are mostly apprentices who are working for their masters. 23.3% were between 20 and 30 years, 33.3% were between 31 – 40 years and 33.4% were ever 40 years. From the analysis, it can be inferred that majority of the steel fixers are within the active work group, although this again depend on the physiological makeup of the individual. The weekly (six days) wages in Naira of the steel fixers was also investigated. It was observed that overwhelming majority 71.7% earn between 3000 and 4000 Naira daily, 16.7% earn between 2000 and 2999 Naira while only few (eight percent) earn over 4000 Naira. It is important to note that as at the time of this study, a U.S. dollar officially exchange for One hundred and fifty six Naira (N156.00). This means that a daily wage rate of the highest paid steel fixer is more than 25.64 US dollars ($25.64). This is higher than the United Nation’s recommendation of at least $1.25 dollar per hour or $10 (N1, 560.00k) per day to escape poverty. Hence, the workers can be said to be moderately motivated financially.

Table 2: Demographic Characteristic of Steel Fixers

1. Level of Education (N=60) Frequency CumulativeFrequency % Cumulative
i. Primary School 28 28 46.7 46.7
ii. O’ Level 14 42 23.3 70
iii. No basic education 6 48 10 80
iv. Trade test 12 60 20 100
Year of experience (N=60)
i. Below 5 years 9 9 15 15
ii. 5 – 10 years 17 26 28.3 43.3
iii. 11 – 15 years 19 45 31.7 75
iv. 16 – 20 years 7 52 11.7 86.7
v. Over 20 years 8 60 13.3 100
Age (N= 60)
i. Below 20 years 6 6 10 10
ii. 20 – 30 years 14 20 23.3 33.3
iii. 31 – 40 years 20 40 33.3 66.6
iv. 41 – 50 years 16 56 26.7 93.3
v. Over 50 years 4 60 6.7 100
Daily wages in Naira (N=60)
i. 1000 – 2000 2 2 3.3 3.3
ii. 2000 – 3000 10 12 16.7 20
iii. 3000 – 4000 43 12 16.7 20
iv. Over 4000 5 60 8.3 100

 

Table 3 shows the result of activity sampling of steel fixers. The result indicate that a proficient steel fixer Spent about 75% of his time per day doing productive work while the remaining is spend doing work that are not directly related to productivity. This is however, not unconnected with the type of contract as the percentage may increase if it is a labour only contract as opposed to other contract type.

Table3: ANALYSIS OF THE EFFECTIVENESS OF STEEL FIXERS’ WORKING TIME ON SITE

Site

No. of effective time observed

Number of ineffective time observed

Total Number of Time observed

Effective time (%)

Ineffective time

 (%)

A

92

33

125

73.6

26.4

B

75

25

100

75

25

C

41

9

50

82

18

D

56

19

75

74.7

25.3

E

37

19

75

74.7

25.3

F

59

13

50

64

36

G

74

16

75

78.7

21.3

H

55

26

100

74

26

I

37

20

75

73.3

26.3

J

37

13

50

64

36

Mean effective time = 75.1%

Mean ineffective time = 24.9%.

Table 4 shows the labour output in hours per items for cutting and bending steel bars into structural forms for floor, beams, columns, staircase and floor slabs base on one steel fixer. The result indicate a mean labour output of 41.58 hours, 24.10 hours, 25.06 hours and 27.05 hours per tonne for beams, columns, stairs and floor slabs respectively. Similarly, Table 5 shows the mean labour output per steel fixer of 67.70 hours, 35.20 hours, 25.10 hours and 45.60 hours per tonne for placing, tying into forms for Beams, columns, staircase and floor slabs respectively. The outputs of steel fixers currently in use in Nigeria for estimation purposes irrespective of the structural member are 63 hours, 45 hours, 35 hours, 27.5 hours and 22.5 hours for cutting and bending one tone of 6mm, 8mm, 10mm, 12mm and 16mm reinforcing bars respectively (anonymous). The same output is used for placing the bars into structural forms.

 

4. Conclusion

The main aim of the study was to establish a local standard labour output for craftsmen involved in cutting, bending and placing steel bars into beams, columns and slabs, which will serve as information for planning and schedule of work. This study has shown that a proficient steel fixer, that is moderately motivated is capable of cutting and bending one tonne of steel rods manually into beams, columns and stairs in 41.58, 24.10 and 25.06 hours respectively and   also capable of doing the same for floor slabs in 27.65 hours. Similarly, a proficient steel fixer is capable of placing and tying one tonne of steel rods into beams, columns and stairs in 67.70, 35.20 and 26.10 hours respectively and also capable of doing same into slab in 45.60hours.

Steel fixers manage their time more effectively on site when engaged as sub-contractors rather than when employed on a day work schedule. The study revealed that steel fixers use 75.1% of their working time effectively while 24.9% of same is used ineffectively

 

 

 

 

 

 

 

 

References

1.      Ameh, O. J. and Odusami, K. T. (2002).    Factors affecting labour productivity in the Nigerian  construction industry- case study of indigenous contracting organization in Lagos. The Quantity Surveyor . 40( 3 ), 14 – 18

2.      Ayandele, J. O. (1997).     Evaluation of factors affecting labour productivity of some selected building trades in Nigerian construction sites. Unpublished Ph.D thesis submitted to the school of post-graduate studies, University of Lagos.

3.      Ayeni, J. O. (1992).           Estimating and price analysis. Longman publishing company ltd, Lagos

4.      Building Futures Council (BFC), (2006). Measuring productivity and evaluating innovation in the US construction industry, Building Future Council, Alexandria, Va

5.      Dai, J; Goodrum, P. M and Maloney, W. F. (2009). Construction craftworkers’ perceptions of the factors affecting their productivity. Journal of Construction Engineering and Management, 135(1), 217-226

6.      Dozzi, S. p. and AbouRizk, S. M. (1993). Productivity in construction. Institute for Research in Construction, National Resaerch Council, Ottawas, ON, Canada.

7.      Ellis, R. D and Lee, S. (2006). Measuring project level productivity on transportation projects. Journal of Construction Engineering and Management, 132(3), 314-320

8.      Enshassi, A; Mohammed, S; Mustafa, Z. A and Mayer, P. (2007).  Factors affecting labour productivity in building project in the Gazza Strip. Journal of Civil Engineering and Management, XIII(4), 245-254

9.      Groover, M. P. (2007). Work systems and the methods, measurement and management of work. Upper Saddle River, NJ: Pearson Prentice Hall.

10.  Illingworth, J. R. (2000). Construction methods and planning, 2nd edn, E&FN Spon, London

11.  Jarkas, A. M. (2010). The influence of buildability factors on rebar fixing labour productivity of beams. Construction Management and Economics, 28(2), 527-543

12.  Jarkas, A. M; Kadri, C. Y. and Younes, J. H. (2012). A survey of factors influencing the productivity of construction operatives in the state of Qatar. The international Journal of Construction Management, 12(3), 1-23

13.  Park, H; Thomas, S. R and Tucker, R. L. (2005). Benchmarking of construction productivity. Journal of Construction Engineering and Management, 137(7), 772-778