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IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 04 Issue: 04 | Apr-2015, Available @ http://www.ijret.org 207
DEVELOPING AN EFFECTIVE WORKFLOW MODULE FOR
PRODUCTIVITY ANALYSIS USING STATISTICAL METHODS IN
VARIOUS CONSTRUCTION SITES
N.Indulekha1
, S.Anandh2
1
Student, Construction engineering and management, SRM University, Tamil Nadu, India
2
Assistant Professor, Construction engineering and management, SRM University, Tamil Nadu, India
Abstract
Productivity plays a vital role in the success of any construction project. Productivity improvements leads to the higher cost
saving with minimal investment. The main objective of the study is to find out the factors affecting construction productivity. The
various types of risks were identified and based on the risk factors that affects construction productivity a questionnaire was
framed A questionnaire survey was carried out in the southern part of India. The questionnaire is distributed to various civil
engineers, contractors, site engineers, planning engineers and total of 53 respondents were obtained. The analysis is carried out
using Statistical Product and Service Solutions (SPSS). From the analysis mean and their respective ranks were found out, based
on which the conclusions are made.
Keywords: Productivity , Questionnaire , risk ,questionnaire survey
--------------------------------------------------------------------***----------------------------------------------------------------------
1. INTRODUCTION
Construction industry plays a vital role in developing the
country’s infrastructure ultimately improving the country’s
economical status. Number of planners, engineers and
consultants are involved throughout the completion of any
construction project. Systematic planning leads to the
successful implementation of the plan thus leading to the
successful completion of the project. Productivity plays a
very important role in any construction site. Thus improving
productivity by applying various modern methods leads to
the project success which saves both money and time.
Effective utilization of the 4M’s namely men, material ,
machinery , money leads to the success of any construction
project .Productivity in general is the ratio between the
output and the input. It is the key factor for the project's
success. It can be improved by proper implementation and
tracking of works that is being carried out in the
construction site. The project standards are rated based on
productivity. The overall analysis of productivity gives an
idea about the delays and factors of delay that affects the
construction activities which leads to the cost overrun and
time over run. The delay can be minimized by proper
scheduling of activities using and subsequently scheduling
can also be done if there is any error in scheduling of
activities , thereby improving productivity.
Productivity plays a vital role both in micro and macro
levels. The construction cost can be minimized by
improving the productivity ultimately completing the
construction project within the stipulated time. The software
by name SPSS is are used , the construction delays are also
reduced by this study.
2. LITERATURE REIVIEW
Saleh al Hadi Jumi, Abdelnaser Omran, Abdul Hamid
Kadhir Pakir, (Nov 2009) has found that delays can lead to
many negative effects such as lawsuits betwwen owners and
contractors, increased cost, oss of productivity and revenue
and termination. Even though various studiees have been
taken into acccount , these studies discuss only the common
and general causes of delays in construction project. Thus a
comprehensive study on these delays is essential. The study
leads to focus on specific causes of delaying like insufficient
cordination and effective communication.
Jarek Hegazy, Mohammad Said; Moustafa Kassab(2011)
recorded all progress events, including rework and calculate
the expected project delay. Analyse the project delay to
identifying the number of days attributed each parties action.
Per-Eeick Josephson ; Bengt Lasson ; Hengli (April
2002)says that rework has become an endemic feature of the
procurement process in construction that invariably leads to
time and cost over runs in projects in order to improve the
performance, it is necessary to identify the causes and cost
of construction networ
Oko John Aneh, Emeka Emmanuel, Oregboh (Nov 2011)
says that the history of construction industry world wide is
full of projects that were completed with significant time
and cost over runs. In an atempt to reverse this trend, this
study aims at establishing the relationship between time
over run and labour productivity on construction site in
Lagos.
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 04 Issue: 04 | Apr-2015, Available @ http://www.ijret.org 208
Polycorp Olabu Alumbugu, Saidu, Ibrahim, Abdullaih Sa
Adu Gulma (Vol 6 no 4 2014) Wasiuadenran Ola-Awo
analyse the relationship betwwen workin height and
productivity of masonary worker on construction site by
investigating two project site. Data were also gatherd by
observing work activity on site.
3. FACTORS AFFECTING PRODUCTIVITY IN
CONSTRUCTION SITE
 Lack of material
 Lack of equipment
 Absentiseem
 Supervision delays
 Delays in clients decision
 Labour personal conflict
 Shortage of unskilled labour
 Uncertain productivity of men
 Improper time management assistance
 Poor management assistance
 Inadequate scheduling process
 Price fluctuation in the market
 Inadequate site investigation
 Inspection delay
 Unrealistic time and cost schedule
 Incomplete design
 Errors in choosing the construction method
 Changes in monsoon cycle
4. QUESTIONNAIRE ANALYSIS
The data collected from the from all 53 respondents are fed
into the SPSS software and their respective mean , rank ,
overall mean and overall rank are obtained. The questions in
the questionnaire survey are framed based on the risk factors
which affect the construction productivity.
4.1 Questionnaire details
The tables given below are the results obtained from the
SPSS analysis. The questionnaire are rated on laggard scale
is given in the table 4.1. Ranking is based on extent of
agreeing on a scale of 1-5 as follows.
Strongly
disagree
Disagree Neutral Agree Strongly
disagree
1 2 3 4 5
Table 4.2 are the results obtained from the analysis which
falls under technical risk.
Table 4.2 Input data of technical risk
Q no Question Mean Rank
1 Inadequate site
investigation
4.30 2
2 Incomplete design 4.55 1
3 Uncertainty over the
availability of construction
materials
4.1 5
4 Lack of supervision
of site engineer
4.125 4
5 Error in choosing
construction method
3.975 9
6 Inadequate specification
and standards
by the architect
4.075 6
7 Poor communication
between the site
engineer and labours
4.250 3
8 Not completely
understanding the
clients requirements
3.975 10
9 Inspection delay by the
Planning engineer
4.0 8
10 Shift work 4.055 7
Table 4.3 are the results obtained from the analysis which
falls management risk
Table 4.3 Input data of management risk
Q no Question Mean Rank
1 Delay in clients decision
4.2 3
2 Stoppages due
to dispute between
owner and contractor
4.27 1
3 Labour personal
conflict 3.85 8
4 Shortage of unskilled
labor
3.9 7
5 Time management
of labours
3.92 6
6 Poor project
management assistance 3.55 11
7 Non involvement of
construction crew in
production objectives
4.2 4
8 Time management
of equipments
3.85 9
9 Uncertain productivity
of machinery
3.67 10
10 Inadequate program
scheduling
4.3 2
11 Uncertain productivity
of men
4.10 5
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 04 Issue: 04 | Apr-2015, Available @ http://www.ijret.org 209
Table 4.4 are the results obtained from the analysis which
falls financial risk.
Table 4.4 Input data of financial risk
Q no Question Mean Rank
1 Standard wage
schemes in firm
4.24 1
2 Price fluctuation
in the market
4.02 4
3 Financial difficulties
of owners
4.22 2
4 Financial difficulties
of contractors
3.65 10
5 Additional works added
during the course of
construction process
4.12 3
6 Delays in payment to
the members of the
construction projects
3.70 9
7 Inflation in the market 3.97 6
8 Fluctuation in foreign
exchange
3.82 8
9 Effect of availability of
finance from
contractor side
3.95 7
10 Effect of availability
of finance from owner side
3.97 5
Table 4.5 are the results obtained from the analysis which
falls environmental risk.
Table 4.5 input data of Environmental risk
Q no Question Mean Rank
1 Changes in Weather 3.925 5
2 Effect of wind
prevailing in the
construction site
4.075 4
3 Unexpected rainfall 4.225 1
4 Change in the level
of water table due
to unexpected rainfall
3.875 6
5 Water scarcity 4.125 3
6 Changes in the
monsoon cycle
4.150 2
7 Extreme heat 3.70 7
Table 4.6 are the results obtained from the analysis which
falls under quality related risk.
Table 4.6 Input data of quality related risk
Q no Question Mean Rank
1 Unrealistic time
assessment
4.0 5
2 Unrealistic cost
assessment
3.95 8
3 Material selection for
construction work
4.27 1
4 Material usage for the
construction work
4 6
5 Poor inspection
of the site
4.13 2
6 Inadequate design 4.1 4
7 Poor work execution 4.12 3
8 Report on non
to quality standards
3.67 10
9 Inspection delay 4 7
10 Rework 3.93 9
Table 4.7 are the results obtained from the analysis which
falls under safety related risk
Table 4.7 Input data of safety related risk
Q no Question Mean Rank
1 Accident 4.25 3
2 improper lighting 4.22 4
3 Improper Ventilation 4.07 7
4 Noise pollution 3.65
5 Carelessness of
the labours
4.2 5
6 Not following the
safety rules
4.27 2
7 Distraction of labours
among themselves
4.02 9
8 Performing multiple
work tasks
4.07 8
9 Not giving proper rest
to workers
4.42 1
10 Improper usage of
safety protection items
4.15 6
Table 4.8 are results obtained from the analysis which gives
the overall mean and overall rank of all the questionnaire
that is being fed into the SPSS software
Table 4.8 Input data of overall mean and overall rank
Risk Overall mean Overall rank
Technical risk 4.1505 1
Management risk 4.0127 4
Financial risk 3.970 6
Environmental risk 4.0107 5
Quality related risk 4.1075 3
Safety related risk 4.136 2
5. RESULTS AND DISCUSSION
Based on the analysis obtained from SPSS and the
questionnaire survey we have found that the factors under
technical risk have got the maximum mean and highest rank.
Many respondents have given importance to technical risk.
The factors affecting productivity based on technical risk
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 04 Issue: 04 | Apr-2015, Available @ http://www.ijret.org 210
affects the construction productivity to a greater extent. By
proper checking and inspection of activities in the
construction site these problems can be minimized to greater
extent. Before the commencement of the construction
project the factors that affect the productivity of that
particular project should be analyzed by referring to the past
records and by analyzing through software’s like SPSS. An
engineer should be appointed to check these thus improving
construction productivity. Next comes the safety related
risk, more importance should be given to safety. The people
involved in the project should taught about safety and an
engineer should be appointed to track thus improving
productivity. Financial risk cannot be taken into
consideration because companies are not telling the financial
details fully as it affects the companies development.
Based on my survey the factors based on the technical and
safety related risk affects the construction productivity. I am
glad to tell that we are working to develop a schedule on MS
Project which improves productivity to a greater extent.
6. Acknowledgements
First and foremost I thank the Almighty, who has given me
the strength to complete this task. Thereafter I would like to
express my sincere gratitude and appreciation to the
generosity of the following people who contributed to the
success of this study.
 My guide, Professor.S.Anandh for his continuous
professional guidance in keeping me focused on the
research topic, for his on-going support and
motivation throughout the study.
 I thank my brother Joshua , my parents, family
members and friends for their support and
encouragement.
 I thank all the engineers and contractors for filling
up my questionnaire paper inspite of their busy
schedule.
REFERENCES
[1] Abdullah, M.O. and Battaineh, H.T. (2002). Causes
of construction delays: traditional contracts, Journal of
Project Management, 20, 6773.
[2] AbdulKadir, M., Lee, W., Jaafar, M., Sapuan, S., and
Ali, A. (2005). “Factors affecting construction labor
productivity for Malaysian residential projects.” Structural
Survey, 23(1), 42–54
[3] Adrian, J.J. 1987. Construction Productivity
Improvement. New York: Elsevier.
[4] Analysis of Construction Fatalities (1990). The OSHA
Data Base 1985-1989. United States. Arboleda, C. A. &
Abraham, D. M. (2004). Fatalities in trenching operations -
Analysis using models of accident causation. Journal of
Construction Engineering and ManagementAsce, 130, 273-
280
[5] Abd El-Razek, M.E., Bassioni, H.A., & Mobarak, A.M.
(2008). Causes of delays in building construction projects in
Egypt. Journal of Construction Engineering and
Management, 134 (11), 831-841.
[6] El-Rayes, K. and Mosehli, O. (2001) Impact of rainfall
on the productivity of highway construction. Journal of
Construction Engineering and Management, 127(2), 125-
131
[7] Shehata, M. and El-Gohary, K. (2011). “Towards
improving construction labor productivity and projects’
performance.” Alexandria Engineering Journal, 50(4), 321–
330.
[8] Assaf, S. A., Al-Khalil, M., & Al-Hazmi, M. (1995).
Causes of delay in large building construction projects.
Journal of Engineering and Management, 17(2), 45-50.
Borcherding
[9] Kumaraswamy, M.M. and Chan, W.M. (1998).
Contributes to Construction Delays, Journal of Construction
Management & Economics, 16; 1729. Lock, D.
[11] Okpala, D.C. and Aniekwu, A.N. (1988). Cause of high
cost of construction in Nigeria .Journal of Construction
Engineering and Management, ASCE, 114 (2) 223-34.
[12] Cleland, D.I. (1999). Project management strategic
design and implementation, 3rd Ed., New York
BIOGRAPHIES
Indulekha.N , PG Student
Department of Civil Engineering ,
SRM University , Katangulathur ,
Chennai
Anandh.S , Assistant Professor,
Department of Civil Engineering ,
SRM University , Katangulathur ,
Chennai
to
hor’s
Photo

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Developing an effective workflow module for productivity analysis using statistical methods in various construction sites

  • 1. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 04 Issue: 04 | Apr-2015, Available @ http://www.ijret.org 207 DEVELOPING AN EFFECTIVE WORKFLOW MODULE FOR PRODUCTIVITY ANALYSIS USING STATISTICAL METHODS IN VARIOUS CONSTRUCTION SITES N.Indulekha1 , S.Anandh2 1 Student, Construction engineering and management, SRM University, Tamil Nadu, India 2 Assistant Professor, Construction engineering and management, SRM University, Tamil Nadu, India Abstract Productivity plays a vital role in the success of any construction project. Productivity improvements leads to the higher cost saving with minimal investment. The main objective of the study is to find out the factors affecting construction productivity. The various types of risks were identified and based on the risk factors that affects construction productivity a questionnaire was framed A questionnaire survey was carried out in the southern part of India. The questionnaire is distributed to various civil engineers, contractors, site engineers, planning engineers and total of 53 respondents were obtained. The analysis is carried out using Statistical Product and Service Solutions (SPSS). From the analysis mean and their respective ranks were found out, based on which the conclusions are made. Keywords: Productivity , Questionnaire , risk ,questionnaire survey --------------------------------------------------------------------***---------------------------------------------------------------------- 1. INTRODUCTION Construction industry plays a vital role in developing the country’s infrastructure ultimately improving the country’s economical status. Number of planners, engineers and consultants are involved throughout the completion of any construction project. Systematic planning leads to the successful implementation of the plan thus leading to the successful completion of the project. Productivity plays a very important role in any construction site. Thus improving productivity by applying various modern methods leads to the project success which saves both money and time. Effective utilization of the 4M’s namely men, material , machinery , money leads to the success of any construction project .Productivity in general is the ratio between the output and the input. It is the key factor for the project's success. It can be improved by proper implementation and tracking of works that is being carried out in the construction site. The project standards are rated based on productivity. The overall analysis of productivity gives an idea about the delays and factors of delay that affects the construction activities which leads to the cost overrun and time over run. The delay can be minimized by proper scheduling of activities using and subsequently scheduling can also be done if there is any error in scheduling of activities , thereby improving productivity. Productivity plays a vital role both in micro and macro levels. The construction cost can be minimized by improving the productivity ultimately completing the construction project within the stipulated time. The software by name SPSS is are used , the construction delays are also reduced by this study. 2. LITERATURE REIVIEW Saleh al Hadi Jumi, Abdelnaser Omran, Abdul Hamid Kadhir Pakir, (Nov 2009) has found that delays can lead to many negative effects such as lawsuits betwwen owners and contractors, increased cost, oss of productivity and revenue and termination. Even though various studiees have been taken into acccount , these studies discuss only the common and general causes of delays in construction project. Thus a comprehensive study on these delays is essential. The study leads to focus on specific causes of delaying like insufficient cordination and effective communication. Jarek Hegazy, Mohammad Said; Moustafa Kassab(2011) recorded all progress events, including rework and calculate the expected project delay. Analyse the project delay to identifying the number of days attributed each parties action. Per-Eeick Josephson ; Bengt Lasson ; Hengli (April 2002)says that rework has become an endemic feature of the procurement process in construction that invariably leads to time and cost over runs in projects in order to improve the performance, it is necessary to identify the causes and cost of construction networ Oko John Aneh, Emeka Emmanuel, Oregboh (Nov 2011) says that the history of construction industry world wide is full of projects that were completed with significant time and cost over runs. In an atempt to reverse this trend, this study aims at establishing the relationship between time over run and labour productivity on construction site in Lagos.
  • 2. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 04 Issue: 04 | Apr-2015, Available @ http://www.ijret.org 208 Polycorp Olabu Alumbugu, Saidu, Ibrahim, Abdullaih Sa Adu Gulma (Vol 6 no 4 2014) Wasiuadenran Ola-Awo analyse the relationship betwwen workin height and productivity of masonary worker on construction site by investigating two project site. Data were also gatherd by observing work activity on site. 3. FACTORS AFFECTING PRODUCTIVITY IN CONSTRUCTION SITE  Lack of material  Lack of equipment  Absentiseem  Supervision delays  Delays in clients decision  Labour personal conflict  Shortage of unskilled labour  Uncertain productivity of men  Improper time management assistance  Poor management assistance  Inadequate scheduling process  Price fluctuation in the market  Inadequate site investigation  Inspection delay  Unrealistic time and cost schedule  Incomplete design  Errors in choosing the construction method  Changes in monsoon cycle 4. QUESTIONNAIRE ANALYSIS The data collected from the from all 53 respondents are fed into the SPSS software and their respective mean , rank , overall mean and overall rank are obtained. The questions in the questionnaire survey are framed based on the risk factors which affect the construction productivity. 4.1 Questionnaire details The tables given below are the results obtained from the SPSS analysis. The questionnaire are rated on laggard scale is given in the table 4.1. Ranking is based on extent of agreeing on a scale of 1-5 as follows. Strongly disagree Disagree Neutral Agree Strongly disagree 1 2 3 4 5 Table 4.2 are the results obtained from the analysis which falls under technical risk. Table 4.2 Input data of technical risk Q no Question Mean Rank 1 Inadequate site investigation 4.30 2 2 Incomplete design 4.55 1 3 Uncertainty over the availability of construction materials 4.1 5 4 Lack of supervision of site engineer 4.125 4 5 Error in choosing construction method 3.975 9 6 Inadequate specification and standards by the architect 4.075 6 7 Poor communication between the site engineer and labours 4.250 3 8 Not completely understanding the clients requirements 3.975 10 9 Inspection delay by the Planning engineer 4.0 8 10 Shift work 4.055 7 Table 4.3 are the results obtained from the analysis which falls management risk Table 4.3 Input data of management risk Q no Question Mean Rank 1 Delay in clients decision 4.2 3 2 Stoppages due to dispute between owner and contractor 4.27 1 3 Labour personal conflict 3.85 8 4 Shortage of unskilled labor 3.9 7 5 Time management of labours 3.92 6 6 Poor project management assistance 3.55 11 7 Non involvement of construction crew in production objectives 4.2 4 8 Time management of equipments 3.85 9 9 Uncertain productivity of machinery 3.67 10 10 Inadequate program scheduling 4.3 2 11 Uncertain productivity of men 4.10 5
  • 3. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 04 Issue: 04 | Apr-2015, Available @ http://www.ijret.org 209 Table 4.4 are the results obtained from the analysis which falls financial risk. Table 4.4 Input data of financial risk Q no Question Mean Rank 1 Standard wage schemes in firm 4.24 1 2 Price fluctuation in the market 4.02 4 3 Financial difficulties of owners 4.22 2 4 Financial difficulties of contractors 3.65 10 5 Additional works added during the course of construction process 4.12 3 6 Delays in payment to the members of the construction projects 3.70 9 7 Inflation in the market 3.97 6 8 Fluctuation in foreign exchange 3.82 8 9 Effect of availability of finance from contractor side 3.95 7 10 Effect of availability of finance from owner side 3.97 5 Table 4.5 are the results obtained from the analysis which falls environmental risk. Table 4.5 input data of Environmental risk Q no Question Mean Rank 1 Changes in Weather 3.925 5 2 Effect of wind prevailing in the construction site 4.075 4 3 Unexpected rainfall 4.225 1 4 Change in the level of water table due to unexpected rainfall 3.875 6 5 Water scarcity 4.125 3 6 Changes in the monsoon cycle 4.150 2 7 Extreme heat 3.70 7 Table 4.6 are the results obtained from the analysis which falls under quality related risk. Table 4.6 Input data of quality related risk Q no Question Mean Rank 1 Unrealistic time assessment 4.0 5 2 Unrealistic cost assessment 3.95 8 3 Material selection for construction work 4.27 1 4 Material usage for the construction work 4 6 5 Poor inspection of the site 4.13 2 6 Inadequate design 4.1 4 7 Poor work execution 4.12 3 8 Report on non to quality standards 3.67 10 9 Inspection delay 4 7 10 Rework 3.93 9 Table 4.7 are the results obtained from the analysis which falls under safety related risk Table 4.7 Input data of safety related risk Q no Question Mean Rank 1 Accident 4.25 3 2 improper lighting 4.22 4 3 Improper Ventilation 4.07 7 4 Noise pollution 3.65 5 Carelessness of the labours 4.2 5 6 Not following the safety rules 4.27 2 7 Distraction of labours among themselves 4.02 9 8 Performing multiple work tasks 4.07 8 9 Not giving proper rest to workers 4.42 1 10 Improper usage of safety protection items 4.15 6 Table 4.8 are results obtained from the analysis which gives the overall mean and overall rank of all the questionnaire that is being fed into the SPSS software Table 4.8 Input data of overall mean and overall rank Risk Overall mean Overall rank Technical risk 4.1505 1 Management risk 4.0127 4 Financial risk 3.970 6 Environmental risk 4.0107 5 Quality related risk 4.1075 3 Safety related risk 4.136 2 5. RESULTS AND DISCUSSION Based on the analysis obtained from SPSS and the questionnaire survey we have found that the factors under technical risk have got the maximum mean and highest rank. Many respondents have given importance to technical risk. The factors affecting productivity based on technical risk
  • 4. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 04 Issue: 04 | Apr-2015, Available @ http://www.ijret.org 210 affects the construction productivity to a greater extent. By proper checking and inspection of activities in the construction site these problems can be minimized to greater extent. Before the commencement of the construction project the factors that affect the productivity of that particular project should be analyzed by referring to the past records and by analyzing through software’s like SPSS. An engineer should be appointed to check these thus improving construction productivity. Next comes the safety related risk, more importance should be given to safety. The people involved in the project should taught about safety and an engineer should be appointed to track thus improving productivity. Financial risk cannot be taken into consideration because companies are not telling the financial details fully as it affects the companies development. Based on my survey the factors based on the technical and safety related risk affects the construction productivity. I am glad to tell that we are working to develop a schedule on MS Project which improves productivity to a greater extent. 6. Acknowledgements First and foremost I thank the Almighty, who has given me the strength to complete this task. Thereafter I would like to express my sincere gratitude and appreciation to the generosity of the following people who contributed to the success of this study.  My guide, Professor.S.Anandh for his continuous professional guidance in keeping me focused on the research topic, for his on-going support and motivation throughout the study.  I thank my brother Joshua , my parents, family members and friends for their support and encouragement.  I thank all the engineers and contractors for filling up my questionnaire paper inspite of their busy schedule. REFERENCES [1] Abdullah, M.O. and Battaineh, H.T. (2002). Causes of construction delays: traditional contracts, Journal of Project Management, 20, 6773. [2] AbdulKadir, M., Lee, W., Jaafar, M., Sapuan, S., and Ali, A. (2005). “Factors affecting construction labor productivity for Malaysian residential projects.” Structural Survey, 23(1), 42–54 [3] Adrian, J.J. 1987. Construction Productivity Improvement. New York: Elsevier. [4] Analysis of Construction Fatalities (1990). The OSHA Data Base 1985-1989. United States. Arboleda, C. A. & Abraham, D. M. (2004). Fatalities in trenching operations - Analysis using models of accident causation. Journal of Construction Engineering and ManagementAsce, 130, 273- 280 [5] Abd El-Razek, M.E., Bassioni, H.A., & Mobarak, A.M. (2008). Causes of delays in building construction projects in Egypt. Journal of Construction Engineering and Management, 134 (11), 831-841. [6] El-Rayes, K. and Mosehli, O. (2001) Impact of rainfall on the productivity of highway construction. Journal of Construction Engineering and Management, 127(2), 125- 131 [7] Shehata, M. and El-Gohary, K. (2011). “Towards improving construction labor productivity and projects’ performance.” Alexandria Engineering Journal, 50(4), 321– 330. [8] Assaf, S. A., Al-Khalil, M., & Al-Hazmi, M. (1995). Causes of delay in large building construction projects. Journal of Engineering and Management, 17(2), 45-50. Borcherding [9] Kumaraswamy, M.M. and Chan, W.M. (1998). Contributes to Construction Delays, Journal of Construction Management & Economics, 16; 1729. Lock, D. [11] Okpala, D.C. and Aniekwu, A.N. (1988). Cause of high cost of construction in Nigeria .Journal of Construction Engineering and Management, ASCE, 114 (2) 223-34. [12] Cleland, D.I. (1999). Project management strategic design and implementation, 3rd Ed., New York BIOGRAPHIES Indulekha.N , PG Student Department of Civil Engineering , SRM University , Katangulathur , Chennai Anandh.S , Assistant Professor, Department of Civil Engineering , SRM University , Katangulathur , Chennai to hor’s Photo