i.a. jimoh

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INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS

COPY RIGHT © 2013 Institute of Interdisciplinary Business Research 105

AUGUST 2013

VOL 5, NO 4

EFFECTS OF DELAY FACTORS ON LABOUR PRODUCTIVITY ON

NIGERIAN CONSTRUCTION SITES

I.A. Jimoh

Department of Building,

Federal University of Technology

Minna, Nigeria

Abstract

To determine the factors affecting labour productivity, ninety six (96)

construction workers on two active construction sites in Minna were studied for fourteen days through Activity Sampling, application of Method

Productivity Delay Model (MPDM) and Foreman Delay Survey (FDS). Data obtained on the workers were analysed to obtain labour productivity and, the types and extent to which delay factors affect production. Activity

sampling gave 54% as measure of labour productivity and 21% as delay while MPDM resulted in 1:10 relationship between Ideal and Overall labour productivity, 1:3 between Ideal and Overall cycle variability and

3.5% as expected cumulative percentage of delay. The MPDM also assessed specific contributions to delay as 4.5%, 4.0%, 4.0% and 4.5% by

Job Environment, Equipment, Labour and Material related factors respectively. By FDS, waiting for other workers, waiting for information, waiting for materials and machine breakdown made significant

contributions of 25%, 24% and 17% to lost man-hours. It is therefore recommended that proper documentation, adequate information, efficient organization of resources and analysis of work environment be given

commensurate attention so as to raise level of labour productivity on construction sites.

Keywords: Construction site; construction workers; labour productivity;

delay; man-hour.

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1.0 INTRODUCTION

Productivity is the efficient and effective utilization of resources of

production for achieving, optimally, set organization objectives (Durdyev

and Ismail, 2012). Mbachu (2008) also asserted that improved productivity

correlates highly with increased profitability, competitiveness, achievement

of key stakeholder value and long-term growth and sustainability of an

organization, industry or an economy (Nation). Low profitability and

profitability, in the construction industry, has been a subject of concern

for long because the manufacturing industry has increased its productivity

by more than 100% whereas that of construction has been declining

(Chromokos and McKee, 1981; Briscoe, 1988). The reasons adduced for

the low level of productivity and which are related to peculiarities of the

construction industry include labour characteristics, varying project work

conditions and environment and the inherent non-productive activities

(Jerges, 2000; Oglesby, 1989; Talhouni, 1995). Labour cost in

construction was assessed by Kazaz and Ulibeyili (2004) to be between

20% and 50% of the total project cost. Calvert (1995) also confirmed that a

5-10% increase in productivity could have a tremendous favourable effect

on the profitability of construction works, by virtue of reduction in project

duration, if non-productive time could be reduced drastically or even

eliminated.

Lack of measurement methods for assessing productivity in the

construction industry, generally, is critical and this has shrouded the

nature of size of the productivity problem (Chapman and Butry, n.d). Most

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of the researches on productivity issues focused attention on

improvements (Tavakoli, 1985; Thomas and Yiakoumis, 1987; Proverbs,

1990). Issues like poor on-site management (Chromokos and McKee,

1981; Oglesby, 1989) and the impact of delays and interruptions by

Horner and Talhouni (1995) contribute to make the construction industry

unstable in its performance leading, often, to cost and time overruns aside

from poor quality of work and frustrations suffered by clients and other

stakeholders. It is therefore the aim of this study to evaluate the types

and effects of delay factors on labour productivity on construction sites.

Labour in the context of this study means the tradesmen or skilled

workers, involved directly on production activities on construction sites

and does not include workers in strategic or tactical levels, administrative

staff and the like. It is also worthy of mention that only productivity

indices on homogenous labour resource shall be determined through

activity based survey and measurement i.e. partial productivity at the

micro level.

2.0 METHODOLOGY

The population of this study is made up of workers on two construction

sites in Minna metropolis. The workers were employed by two

construction firms that handled the construction of National Examination

Council (NECO) headquarters (i.e. Site A) and Intercontinental Bank (ICB)

(i.e. Site B) in Minna, Nigeria. Observation and survey were made for

fourteen days on ninety six (96) workers on the two sites. At site A,

nineteen (19) concretors, eight (8) carpenters, seven (7) iron benders,

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twelve (12) masons, seven (7) domestic electricians, six (6) plumbers and

seven (7) labourers were engaged, actively, in construction works every

day. On site „B‟, seven (7) concretors, six (6) concrete mixers, seven (7)

masons, eight (8) carpenters, six (6) iron benders, four (4) domestic

electricians, three (3) plumbers and sixteen (16) labourers worked, on the

average, per day.

Methods used for data collection include direct observation, timing of

production activities and administration of questionnaire. The direct

observation was used to rate the effectiveness of the workers by Activity

Sampling while Method Productivity Delay Model (MPDM) involves the

timing of production cycles and Foreman Delay Survey (FDS)

questionnaires were distributed to Foremen on the two sites. The MPDM

and FDS were designed by the Construction Research Council (CRC) of

Canada for assessing the effects of delay factors on Labour productivity.

By Activity sampling, the major production activity in each of the two

construction sites was identified. Each crew carrying out the major

activity was observed randomly to collect activity level data on the

workers. The worker‟s activity was categorized and recorded as

productive, semi-productive and non-productive, which translate to

productive time, ancillary time and wasted time spent on production

respectively. All the observations made were recorded on a prepared form

using checkmarks under the appropriate mode of activity, as observed. In

order to obtain a sampling error of 5% and a level of confidence of 95%,

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the statistical criterion of 384 minimum number of observation was

satisfied. The data recorded are in Appendix I.

Application of MPDM entail observation and recording of production cycle

times, including source and period of delay on a special form. Two types

of production cycles recorded are the non-delayed and delayed cycles.

Sources of delay have been classified into six as Environmental,

Equipment, Labour, Material, Management and any other. The data

collected are in Appendix II and III.

In FDS, only the Foreman or Supervisor of each craft is questioned on the

extent and type of delays that affected the performance of the workers.

Considering his close contact with both the workers and management the

Foreman is assessed to be more competent in identifying the cause of any

delay and giving an accurate estimate of its duration. Only delays that are

beyond the control of the Foreman are recorded in terms of source, length

of time lost and the number of workers affected. The questionnaire was

administered daily, took about ten minutes of the Foreman‟s time at close

of work and involved all the key trades. Appendix IV contains the data

obtained from the survey.

3.0 DATA PRESENTATION, ANALYSIS AND DISCUSSION OF

FINDINGS.

The data collected were analysed with the use of SPSS and Microsoft Excel

packages to obtain descriptive and inferential statistics in ranked means,

and percentages.

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3.1 Activity Sampling

Eight four (84) rounds of observation on working modes of workers on the

two construction sites were recorded with each round containing ten (10)

observations. The three working modes are productive, semi-productive

and unproductive (idle). Summary of observations that gave the mean

values on productivity and delay in percentages are in Tables I and II.

Productivity Rating

Fig. 1- Labour Productivity by Activity Sampling- site „A‟

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Productivity Rating

Fig 2: labour Productivity by Activity Sampling- Site „B‟

Productivity Rating

Fig 3: Labour Productivity by Activity Sampling- Site „A‟ & „B‟ Combined

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Figures 1, 2, and 3 above indicate labour productivity measured by

proportion of time spent on production activities, as 51% for site „A‟; 57%

for site „B‟ and 54% for the two sites combined. By this result, labour

productivity in site „B‟ is higher, by 6%, then in site „A‟. If the result of the

two sites combined is taken as benchmark site „B‟ could be regarded as

more productive then site „A‟ by 3% albeit this could be contested because

the work environments of the two sites are not the same.

Proportion of unproductive time (idle time) for site „A‟ is 20.5% while for

site „B‟ it is 22% and the two sites combined had 21%- which interpretes to

“higher productivity created higher unproductive time”. With the two sites

combined, relationship between productive time and idle time is 54:21 (i.e.

39%). By this overall indicator of relationship between productive and idle

time and taking labour cost to be 35% on the average, of the total cost of

construction (Calvert, 1995), then a 21% delay tantamount to a saving of

N735,000.00 on a N10.0 million job.

3.2 Method Productivity Delay Model (MPDM)

The data obtained through records on cycles of production are in Appendix

II and were thereafter analyzed to produce the results in Table I below.

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Table I: Deductions from measurement of Labour Productivity with MPDM

Descriptors Construction Sites Mean

Site ‘A’ Site ‘B’

Mean overall cycle time (secs) 316.09 191.57 253.83

Mean non-delay cycle time (secs) 306.09 186.30 246.19

Expected percentage of delay (%) 4.00 3.00 3.50

Ideal cycle variability (%) 1.00 1.00 1.00

Overall cycle variability (%) 3.00 3.00 3.00

Ideal labour productivity 0.0033 0.0054 0.0044

Overall method productivity 0.003 0.005 0.004

Source: Researcher’s Fieldwork

Results in table I indicate that the Ideal labour productivity i.e. based on

non-delayed production cycles is ten times higher than that of the Overall

cycle time. Delays caused by the Environmental factors, Equipment,

Labour, Material and Management are as follow: in Table II and III.

Table II: Extent of delay on Site „A‟ based on Mean non-delay cycle time

(306.09) as Bench mark by MPDM.

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Table II: Extent of Delay on Site ‘A’ based on Mean Non-Delay Cycle

Time (186.30) as Benchmark by MPDM

Source of

Delay

Cycle

No

Cycle

Time

Delay per

Cycle

Percentage

Delay/ Cycle

Cumulative

delay

Ranking &

Remarks

Environmental

11

14

15

316

330

331

9.91

23.91

24.91

3.0

7.0

7.5

9.91

33.82

58.73

*Mean = 6%

* Rank = 1

*Highest

delay of 7.5%

in cycle 15

Equipment

13

19

20

24

26

324

324

319

324

316

17.91

7.16*2

12.91

17.91

9.91

5.5

2.0

4.0

5.5

3.0

17.91

25.07

37.98

55.89

65.80

*Mean = 4%

*Rank = 3

*Highest

delay of 5.5%

in cycles 13 &

24

*2 40% of

delay shared

Labour

2

10

12

19

29

30

315

319

318

324

327

322

8.91

12.91

11.91

10.75*2

17.911

20.912

3.0

4.0

4.0

3.0

6.0

5.0

8.91

21.82

33.73

44.4

65.39

81.30

*Mean = 4%

* Rank = 3

*Highest

delay of 6%

in cycle 29

60% of Delay

shared

Materials

3

4

5

16

17

18

310

322

325

321

331

328

3.91

15.91

18.91

14.91

24.91

21.91

1.0

5.0

6.0

5.0

7.5

7.0

3.91

19.82

38.73

53.64

78.55

100.46

* Mean = 5%

* Rank = 2

* Highest

delay of 7.5%

in cycle 17

From Tables II and III, delays caused to production activities in Site „A‟

were due to Environmental, Equipment, Labour and Material factors with

Environmental ranking highest. There was no delay caused by

management. On the other hand, three factors (Environmental, Labour

and Material) caused delay in Site „B‟ with labour and material ranked

equally in terms of specific contribution. In general, expected percentage

of delay is higher in site „A‟ than site „B‟ (4% vs. 3%) while production cycle

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differentials for Ideal and Over-all production runs remain the same (i.e.

1%) for the two sites as shown in Table I.

Table III: Extent of Delay on Site ‘B’ Site based on Mean Non-Delay Cycle Time (186.30) as Benchmark by MPDM

Source of Delay Cycle

No

Cycle

time

Delay

Per cycle

Percentage/

Delay Cycle

Cumulative

Delay

Ranking &

Remarks

Environmental

4

13

23

24

25

191

189

191

195

197

4.70

2.70

4.70

8.70

10.70

2.5

1.0

2.5

4.5

5.0

4.70

7.40

12.10

20.80

31.50

*Mean = 3%

* Rank = 3

*Highest delay

of 5% in cycle

25

Labour

6

7

8

9

17

18

19

26

29

30

195

197

190

198

194

192

191

201(60

%)*2

196

194

8.70

10.70

3.70

11.70

7.70

5.70

4.70

8.82

9.70

7.70

4.5

5.0

2.0

6.0

4.0

3.0

2.5

4.0

5.0

4.0

8.70

19.40

23.10

34.80

42.50

48.20

52.90

61.72

71.42

79.12

*Mean = 4%

*Rank = 1

*Highest delay

of 6% in cycles 9

*2 60% of delay

shared

Material

26

27

28

201(40

%)*2

192

198

5.88

5.70

11.70

3.0

3.0

6.0

5.88

11.58

23.28

*Mean = 4%

* Rank = 1

*Highest delay

of 6% in cycle

28

*2 40% of Delay

shared

3.3 Foreman Delay Survey (FDS)

The data obtained from Foreman Delay Survey (FDS) contain the total

number of production hours lost per week through the influence of ten

factors (Appendix III). The factors have been ranked in Table IV, in

accordance with level of disruption (lost hours) to production.

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Table IV: Factors and Extent of Delay on Construction Sites by Foreman Delay Survey (FDS)

S/N Factors Site ‘A’ Site ‘B’ Cumulative (Sites ‘A’ & ‘B’)

Lost

Man Hrs

% Rank Lost

Man Hrs

% Rank Mean lost

man hrs

% Rank

1 Waiting for information 96.00 35.00 1 36.00 13.00 4 70 25.00 1

2 Waiting for other workers 79.50 29.00 2 59.50 22.00 2 66 24.00 2

3 Waiting for materials 71.00 26.00 3 52.00 19.00 3 62 22.00 3

4 Machine breakdown 12.00 4.00 4 84.00 30.00 1 48 17.00 4

5 Design error (Redo work) 8.50 3.00 5 10.50 4.00 6 17 6.00 5

6 Production error (Redo work 8.00 3.00 6 26.00 9.00 5 10 4.00 6

7 Change in design (Redo work) 0.00 0.00 7 9.00 3.00 7 5 2.00 7

8 Waiting for machines 0.00 0.00 8 0.00 0.00 8 0 0.00 8

9 Waiting for tools 0.00 0.00 8 0.00 0.00 8 0 0.00 8

10 Unnecessary move 0.00 0.00 8 0.00 0.00 8 0 0.00 8

276.00 100.00 277.00 100.00 278 100.00

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From the results in table IV, waiting for other workers, information and

materials ranked first, second and third respectively. Dependency on other

workers is a common feature, in construction, albeit 22 – 25% idle time is

on the high side. Information and materials are also crucial at every stage

of construction work.

Lost hours on tools were not recorded because the artisans often possess

and work with their personal tools. The workers did not also depend on

machines and were not therefore affected by this factor, despite the 17%

lost time on breakdown of concrete mixer; they had enough material to

work with.

4.0 CONCLUSION

Labour productivity of construction workers is 54% by Activity Sampling

with 21% of the time wasted, MDPM gave a relationship of 1:10 between

Ideal and Overall labour productivity on the two construction sites and 1:3

between Ideal cycle variability and the Overall. The expected cumulative

percentage of delay thereof is 3.5%. In specific terms, delays were caused

by Environmental factors (4.5%), Equipment (4%), labour (4%) and

materials (4.5%). Environment and labour factors on Site „A‟ deserve close

attention while it is labour and material factors on Site „B‟. These

deductions confirm the assertion of Oglesby et al., (1989) and Jerges et al,

(2000).

Foreman Delay Survey (FDS) threw more light on delay factors by breaking

them down further into ten. Out of the ten factors, waiting for other

workers, waiting for information, waiting for materials and machine

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breakdown made significant contributions to lost man hours – 25%, 24%,

22% and 17% respectively. Delay of 22% on materials fall within 5.4 to

56.8 indicated in Thomas and Sanvido (2000). Re-do work in relation to

Design and Production documentation had little contribution to delay

while waiting for machine, waiting for tools and unnecessary move were

not recorded.

In order to raise labour productivity on construction sites, proper

documentation, adequate information, efficient organization of labour,

materials and equipment become crucial. There is also the need to

analyze the work environment well before commencement of work on site

to as to develop an appropriate production template for higher productivity

across board.

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REFERENCES

Calvert, R.E. (1995): Introduction to Building Management, 6th Edition,

Oxford, Butterworth-Heinemann.

Chapman, R.E. and Butry, D.I. (n.d). Measuring and Improving the

Productivity of the U.S. Construction Industry: Issues, Challenges and

Opportunities. Building and Fire Research Laboratory, National

Institute of Standards and Technology, Gaithersburg, MD 20899.

Chromokos Jr., J. and McKee, K.E. (1981): Construction Productivity

Improvement, Journal of the Construction Division, ASCE, 107 (1):

37-47

Dozzi, S.P and Abou-Rizk, S.M. (1991): Productivity in Construction.

Institute for Research in Construction, National Research Council,

Ottawa, Ontario, Canada p. 1

Durdyev, S. and Ismail, S. (2012). Pareto Analysis of on-site Productivity

Constraints and Improvement Techniques in Construction Industry.

Scientific Research and Essays. 7(7):824-833.

Horner, R.M.W. and Talhouni, B.T.K. (1995): Effects of accelerated

working, delays and disruptions in labour productivity by daily

visits. AAC International Transactions Prod. 05:1

Jerges, G.E., Christy, S. and Leitner M.J. (2000): Construction

Productivity: A Survey of Industry Practices, ACCE International

Transactions, PM 06.01

Kazaz, A. and Ulubeyili, S. (2004): A different approach to construction

labour: Comparative Productivity analysis, Building and

Environment, 39:93-100

Liou, F. and Borcherding, J.D. (1986): Work Sampling can predict Hint

Rate Productivity. Journal of Construction Engineering and

Management, 112(1):91-94.

Mbachu, J. (2008). Conceptual Framework for the Assessment of

Subcontractors‟ Eligibility and Performance in the Construction

Industry. Construction Management and Economics, 26(5):471-484.

Oglesby, C., Parker, H. and Howell, G. (1989): Productivity Improvement in

Construction New York, McGraw-Hill.

Proverbs, D.G. Holt, G.D. and Olomolaiye, P.O. (1999): European

Construction Contractors: a Productivity Appraisal of In-situ

Concrete Operations. Construction Management and Economics,

17:221-30

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Tavakoli, A. (1985): Productivity Analysis of Construction Operations.

Journal of Construction Engineering and Management, ASCE,

107(1):37-47

Thomas, H. and Yiakoumis, I. (1987): Factor Model of Construction

Productivity. Journal of Construction Engineering and Management,

ASCE, 113(4):427-9

Thomas, H.R. and Sanvido, V.E. (2000). Role of the Fabricator in Labour

Productivity. Journal of Construction Engineering and Management,

126(5), September/October. P.358.

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APPENDIX I

Data on Labour Productivity by Activity Sampling on Construct ion Sites

Rating Frequency Percentage Valid

Percentage

Cumulative

Percentage

Site ‘A’

30 3 7.30 7.30 7.30

40 5 12.30 12.20 19.50

50 20 48.80 48.80 68.30

60 10 24.40 24.40 92.70

70 3 7.30 7.30 100.00

Total 41 100.00 100.00

Site ‘B’

40 3 7.30 7.30 7.30

50 16 39.00 39.00 46.30

60 15 36.60 36.60 82.90

70 5 12.20 12.20 95.10

80 2 4.90 4.90 100.00

Total 41 100.00 100.00

Site ‘A’ & ‘B’ Combined

30 3 3.70 3.70 3.70

40 8 9.80 9.80 13.40

50 36 43.90 43.90 57.30

60 25 30.50 30.50 87.80

70 8 9.80 9.80 97.60

80 2 2.40 2.40 100.00

Total 82 100.00 10.000

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APPENDIX II

FIELD DATA ON APPLICATION OF METHOD PRODUCTIVITY DELAY MODEL (MPDM)

Data on Workers- Construction Site ‘A’

Prod. Cycle Cycle time Non-delay Enviro. Delay Equip. delay Labour delay Mat. Delay Mngt. Delay Processing Columns

1 305 305 1.0909 1,0909

2 315 * 8.9091

3 310 * 3.9091

4 322 * 15.9091

5 325 * 18.9091

6 309 309 2.9091 2,9091

7 304 304 2.0909 2,0909

8 306 306 0.0909 0.0909

9 304 304 2.0909 2.0909

10 319 * 12.9091

11 316 * 9.9091

12 318 * 11.9091

13 324 * 17.9091

14 330 * 23.9091

15 331 * 24.9091

16 321 * 21.9091

17 331 * 17.9091

18 328 * 12.9091

19 324 40% 60% 0.9091 0.909091

20 319 * 1.0909 1.0909

21 307 307 1.9091 1.909091

22 305 305 17.9091

23 308 308 0.0909 0.0909

24 324 * 9.9091

25 306 306 2.0909 2.0909

26 316 * 2.9091 2.0909

27 304 304 20.9091

28 309 309 15.9091

29 327 * 20.9091

30 322 * 15.9091

Source: Researcher’s Fieldwork

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APPENDIX III

FIELD DATA ON APPLICATION OF METHOD PRODUCTIVITY DELAY MODEL (MPDM)

Data on Workers- Construction Site ‘B’

Prod. Cycle Cycle time Non-delay Enviro. Delay Equip. delay Labour delay Mat. Delay Mngt. Delay Processing Columns

1 185 185 1.3000 1.3000

2 187 187 0.7000 0.7000

3 183 183 3.3000 3.3000

4 191 * 4.7000

5 185 185 1.3000 1.3000

6 195 * 8.7000

7 197 * 10.7000

8 190 * 3.7000

9 198 * 9.7000

10 195 8.7000

11 198 11.7000

12 192 5.7000

13 189 * 2.7000

14 185 185 1.3000 1.3000

15 188 18 1.7000 1.7000

16 191 191 4.7000 4.7000

17 194 * 7.7000

18 192 * 5.7000

19 191 * 4.7000

20 186 186 0.3000 0.3000

21 184 184 2.3000 2.3000

22 189 189 2.7000 2.7000

23 191 * 4.7000

24 195 * 8.7000

25 197 * 10.7000

26 201 60% 40% 14.7000

27 192 * 5.7000

28 198 * 11.7000

29 196 * 9.7000

30 194 * 7.7000

Source: Resources Fieldwork

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APPENDIX IV

FIELD DATA ON FORMAN DELAY SURVEY

Data on Workers Construction Site ‘A’

Survey

No

Sources

of Delay

No of

Men

Max Man

Hour

Lost Man Hrs

(Delay)

Lost Man

Hrs (in %)

A B C D E F G H I J

1 8 0 1.5 0 0 0 0 0 13 0 28 224 22 9.28%

2 0 0 0 14 0 0 0 21 14 0 21 168 49 29.17%

3 0 0 0 10 0 0 0 18 6 0 14 112 34 30.36%

4 0 0 2 12 0 0 4 7 8 0 21 168 33 19.64%

5 0 0 0 15 0 0 2 12 3 0 16 128 32 25%

6 0 0 5 20 0 0 6 28 20 0 35 280 79 28.21%

7 0 0 0 0 0 0 0 10 16 0 13 104 26 25%

Sum 8 0 8.5 71 0 0 12 96 80 0 148 1184 275 23.23%

Data on Workers Construction Site ‘B’

Survey

No

Sources

of Delay

No of

Men

Max Man

hour

Lost Man Hrs

(Delay)

Lost Man

hrs (in %)

A B C D E F G H I J

1 10 0 8 0 0 0 75 0 13 0 59 472 105.5 22.35%

2 6 0 0 20 0 0 9 3 15 0 19 152 53 34.87%

3 10 9 0.5 0 0 0 0 0 5 0 14 112 24.5 21.88%

4 0 0 0 16 0 0 0 8 16 0 24 192 40 20.83%

5 0 0 0 8 0 0 0 4 0 0 8 64 12 18.75%

6 0 0 2 8 0 0 0 5 6 0 14 112 21 18.75%

7 0 0 0 0 0 0 0 16 5 0 13 104 21 20.19%

Sum 26 9 10 53 0 0 84 36 60 0 151 1208 277 22.93%

KEY:

Classified Sources of Delay in Foreman delay Survey

A – Redoing work (Design error) B – Redoing work (Change in Design) C – Redoing work (Production error)

D – Waiting for materials E – Waiting for tools F – Waiting for machine

G – Machine Breakdown H – Waiting for information I – Waiting for other workers

J – Unnecessary move

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APPENDIX V

DATA COLLECTION FORM ON FOREMAN DELAY SURVEY (FDS)

Problem causing Area Person – Hours Lost

No of

Hours Lost

No of

Workers

Total Person-

Hours

(1) Redoing work (Design error)

(2) Redoing work (Prefabrication error)

(3) Redoing work (Field error or Damage)

(4) Waiting for materials (Warehouse)

(5) Waiting for material (Vendor/Supplier)

(6) Waiting for Tools

(7) Waiting for construction equipment

(8) Construction Equipment breakdown

(9) Waiting for information

(10) Waiting for other crews

(11) Waiting for fellow crew member(s)

(12) Unexplained or unnecessary move

(13) Other(s)

Comments:

Organization:

Date:

i.a. jimoh

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