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    Idrus et al


    Towards Development of a Database for Civil and

    Structural Construction Works’ Production Rates

Arazi Idrus*, Universiti Teknologi PETRONAS, Malaysia

    Kamaludin Hashim, Universiti Teknologi PETRONAS, Malaysia

    Ahmed Mohamed Farah, Universiti Teknologi PETRONAS, Malaysia


    Production rate (also known as construction or productivity rate) is one of the important data needed for determining activity duration and hence for scheduling of the activities in a project. However, because production rates are greatly affected by various controlled and uncontrolled factors, no specific calculations can be derived to evaluate them. Because of this, their values have all been based on the experience and judgment of the individual construction manager, as well as from previous company records. These values are often subjective and also not freely available to others outside the company. The aim of this paper is to report on the pioneering work at UTP to develop a formal database of “moderated”

    production rates for in-situ civil and structural construction works, which will not only be reliable but also accessible to everyone in the industry. The Survey Research Methodology has been used in this research to elicit data on production rates. For this, structured closed-ended questionnaires were sent to individuals in contracting companies. Face-to-face interviews were also conducted with some of the respondents. Data collected were compiled and analyzed using descriptive statistics and variance analysis. It was found that the survey had produced quite a wide range of production rate values for each activity. As the study is one of the pioneering works to be conducted in Malaysia, the results obtained may not yet be taken as final or universally accepted for use by the construction industry. However, it does provide an indication of the range of values of production rates data in the industry.

     Keywords: Production rates, database, civil and structural works, in-situ construction

*Correspondence Author: Assoc. Prof. Ir. Dr. Arazi Bin Idrus, Universiti Teknologi PETRONAS, Malaysia, Tel:

    +6053687313, Fax: +6053656716. E-mail:

ICCBT 2008 - B - (07) - pp149-164 149

Towards Development of a Database for Civil & Structural Construction Works’

    Production Rates


    Planning of a construction work greatly relies on the availability of some fundamental information such as scope, sequence, quantity, production rates and subsequently duration of each activity associated with the project. Among the information described above, discrepancies often arise in predicting the values of the production rates. Production rate can be defined as the amount of work that could be done within a certain period of time. It is one of the most crucial information needed in determining the duration of a specific construction activity during work scheduling. Production rates are, however, greatly affected by various factors such as level of manpower, level of productivity, climate, geography and construction technology applied. The variation of these factors cannot be completely controlled, thus for the same activity, different values of production rates are produced in every project. Besides, no specific calculations of production rates can be derived from mathematical calculations alone. Because of this, their values have all been based on experience and judgment of the individual construction manager, as well as from previous company records. Such information is not only subjective, but also not freely available to others outside the company. This research aims to collect data on Civil and Structural construction work‟s production rates

    from the industry, and to compile and analyze the data obtained to develop a database containing initial values of “moderated” production rates, with the strategic goal of making it

    universally accepted and freely accessible to everyone in the Malaysian construction industry.


    Information on activity duration is important in scheduling construction activities on site, in costing the activities, or in predicting overall project completion time. Activity duration is computed by dividing the quantity of work involved with the number of resources used and with the corresponding production rate of that activity (e.g. no. of tonnes of steel bars installed 2 3per hour (or day), mof formwork installed per hour (or day), m of concrete poured per hour,

    etc.). Thus [1]:

Activity duration (T) = Quantity of work (Q)

     Production rates (R) x No. of resources (N)

    Quantity of work and number of resources (people or machine) can be quantitatively determined respectively by “taking off quantities” and by looking at the amount of resources

    assigned. Production rates, are, however, greatly affected by various controlled and uncontrolled factors and have therefore been based on rules of thumb, as described before.

    There has been relatively a limited amount of research conducted overseas on the subject of construction productivity measurements. Among these are Price and Harris [2],[3],[4] who reported a series of small scale work studies in the UK attempting to establish statistical correlations for rebar installation, concrete placement and formwork erection respectively. Proverbs et al [5], [6] conducted questionnaire surveys to compare productivities of UK, French and German contractors with regard to concreting and rebar installation works respectively. They found that there were significant differences of production rate values ICCBT 2008 - B - (07) - pp149-164 150

    Idrus et al

    between the three groups of contractors for both the activities. The corresponding author‟s

    own work in 1999 [7] made on-site observations of production rates during the construction of the (Experimental) European Concrete Building Project in Cardington, Bedfordshire, UK.

    Locally, research of this kind is even more limited. Mansur et al [8] reported on tools for

    determining correction indices to values of production rates while applying schedule compression. Al-Werafy [9] wrote a thesis on factors influencing activity times while Chin [10] attempted to establish a relationship between the improvement of production rates and percentage of local labors in construction projects.

    However, in all of the work previously conducted, none specifically addressed the development of some kind of a database for construction work production rates, similar to today‟s easily-available cost databases. The small amount of studies devoted to this topic, the lack of a reliable, flexible and freely available production rates database specifically for Malaysia, together with personal supports given by staff of the Construction Industry Development Board (CIDB) have all been the motivating forces behind this study.


    In this research, the Survey Research Methodology (SRM) has been chosen as the methodology to gather opinions from industry experts with regard to values of production rates data for Civil and Structural work (in-situ construction only). For this purpose, a total of 300 CIDB Class G5-G7 contractors specializing in building works were identified from CIDB‟s Directory of Contractors comprising of 100 from Perak, 100 from Selangor and 100 from Wilayah Persekutuan Kuala Lumpur. The survey could only cover these three states because of time and financial constraints. Perak was chosen not only for convenience but also for representing productivity characteristics outside the Klang Valley. The list was then arranged alphabetically and from this, 150 contractors were further selected using the Systematic Random Sampling procedure. A total of 150 carefully-designed structured questionnaires were distributed to these contractors by post and some by hand. The questionnaire design consisted three sections. The first sought information regarding respondents‟ background. The second (i.e. main) section asked respondents to give their

    opinions on production rates for a typical list of activities associated with one complete cycle of reinforced concrete work in a building project: Piling; Excavation; Falsework Installation; Formwork Installation (Soffit and Edge); Reinforcement Fixing (Main bars and links, mesh and loose types); Concrete Placement (by skip and by pumping); Falsework Dismantling and finally Formwork Dismantling. In this research “formwork” refers to the timber pieces

    required to make the forms or mould to contain the concrete, while “falsework” refers to the temporary supporting structure (or scaffolding) required to support the formwork. The third section of the questionnaire asks respondent to freely give any additional information regarding the research topic. As an attachment, the questionnaire also included some assumptions on gang size and a figure of an example building to guide the respondents so that they have the same basis or datum in arriving at the production rates.

    To help ensure good response, and to seek as much information as possible about the topic, a “hybrid” survey approach was also taken, in which semi-structured face-to-face interviews were simultaneously conducted in place of 5 postal questionnaires (2 in Selangor and Kuala Lumpur each and 1 in Perak), using the same but a slightly extended survey format. ICCBT 2008 - B - (07) - pp149-164 151

Towards Development of a Database for Civil & Structural Construction Works’

    Production Rates


    A total of 14 out of 150 respondents returned the questionnaire. Though representing only 9.3% of the original sample, this low percentage of response had been expected for this pre-dominantly mailed and questionnaire-based survey research. However, this is still considered goodbearing in mind the highly specialized nature of the information to be collected and also the questionnaire response rate from the Malaysian construction industry being typically between 5-15% only.

    For the section on general/background information about the respondents, data collected are presented in Tables 1-6 and descriptive analyses of these data depicted in the corresponding pie charts. For production rates data collected, they are presented as “raw data” in Table 7 and

    analyzed accordingly in Tables 8-12.

4.1 General / Background information:

    4.1.1 Company’s Location:

    Table 1 and Figure 1 below visually show that most of the respondents are from Selangor. Initially, the purpose of knowing the respondent‟s company‟s location is to distinguish whether there is any significance difference in the three states with regard to civil and structural works‟ production rates. However, no indication can be made since so few respondents replied the questionnaire.

    Table1: Company‟s Location:

    State No. of Respondents

    Perak 1

    Selangor 11

    Kuala Lumpur 2

    Company's Location

    7% 14%



    Kuala Lumpur


     Figure 1: Company‟s Location

    ICCBT 2008 - B - (07) - pp149-164 152

    Idrus et al 4.1.2 Respondent’s Class of PKK and CIDB Registration

Table 2 and Figure 2 ; and Table 3, Figure 3 illustrate respondents‟ class of registration with

    the Pusat Khidmat Kontraktor (PKK) and the CIDB respectively.

    Table 2: Respondent‟s PKK Class: PKK Class

    PKK Class No. of Respondents

    A 11

    B 1

    Unknown 2 14% A 7% Most of the respondents are from Class B A PKK contractor which is the highest

    Unknown of the PKK classes. 79%

    Figure 2: Respondent’s PKK Class

    Table 3: Respondent‟s CIDB Class: CIDB Class

    No. of Respondents CIDB Class

    G7 11

    G4 1

    Unknown 2 21% G7 For CIDB class, most of the respondents

    are from G7 Class, which is the highest G4 7%

    of the CIDB classes. 72% Unknown

    Figure 3: Respondent’s CIDB


    4.1.3 Company’s experience in building construction: ICCBT 2008 - B - (07) - pp149-164 153

Towards Development of a Database for Civil & Structural Construction Works’

    Production Rates

    Table 4: Company‟s Experience: Company's

    Company‟s No. of Experience (Years) Experience (Years) Respondents

    Less than 5 3

    5 10 6

    10 - 20 5

    21% Less than 5 36% Most of the companies have 5-10 years 5 to 10

    experience. This shows that the 10 to 20 companies which replied the 43%

    questionnaire have sufficient knowledge

    on building construction.

    Figure 4: Company’s Experience

4.1.4 Respondent’s experience in building construction

    Table 5: Respondent‟s Experience: Respondent's

    Experience Experience (Years) No. of Respondents (Years)

    Less than 5 7 Less than 5 5 10 4

    10 15 2 7% 5 to 10 14% More than 15 1

    50% 10 to 15 29%

    Half of the respondents have less than 5

    More than years experience in building

    15 construction. However, it is assumed that

    the respondents could rely on the

    Figure 5: Respondent’s Experience company’s historical records regarding

    building construction, in answering the


4.1.5 Respondent’s Designation

    ICCBT 2008 - B - (07) - pp149-164 154

    Idrus et al

    Respondent‟s designation with the company is indicated by Table 6 and Figure 6 below.

    Table 6: Respondent‟s Designation

    Respondent‟s Designation No. of Respondents

    Managing Director 1

    General Manager 1

    Project Manager 5

    Construction Manager 3

    Qa Qc Manager 1

    Planner 2

    Project Engineer 1

    Respondent's Designation

    Managing Director

    7% 7% 7% General Manager 14%

    7% Project Manager 36%




     Figure 6: Respondent‟s Designation

4.2 Production Rates : Presentation of Raw Data

The production rates data collected from the survey are presented as “raw” (unanalyzed) data

    in Table 7. These are measured in days, assuming an 8-hour working day. Nine sets of data were obtained from the questionnaire distributions, while five more from the interviews. However, 1 set of data from the questionnaires could not be shown in the table as the respondent, instead of giving production rates, only gave durations for the activities with no indication of quantities involved.

4.2 Production Rates : Analysis

    As the number of responds is below 30, no parametric inferential statistics could be carried out on the raw data collected [11]. Instead, descriptive statistics is used to analyze the data which also include Variance Analysis, Mean and Variance Analysis and Mode Analysis. Variance Analysis is used to analyze in the differences (and significance) of production rate values based on contractors‟ class and also based on respondents‟ experience. Mean and

    Variance Analysis discuss the mean and (statistical) variance values calculated from the raw data, while Mode Analysis aims to select the best production rates value for each activity. ICCBT 2008 - B - (07) - pp149-164 155

Towards Development of a Database for Civil & Structural Construction Works’

    Production Rates

    By observing the data in Table 8, no conclusion can be made on the pattern of differences in production rates given by different classes of contractor. All the known and unknown classes give more or less the same production rates with respect to each other. Furthermore, the presence of the unknown class further prevents the authors from making any conclusion from this analysis.

    By observing the data in Table 9, we can see some patterns of data which distinguish the production rates data given by different respondents‟ experience. Most of the low production

    rates are given by respondents who have less than five years of experience indicating that this group of respondents tends to be more conservative in predicting values of production rates. The table also shows that respondents with experience eleven years or more provide the highest values of production rates and these figures tend to be more or less the same. With regard to mean and variance values as shown in Table 10, it is obvious that there is a

    large variation among the data, thus the mean cannot not be accepted as the measure of central

    tendency. However, there are some values that occur more often in the raw data, thus the mode of the data was instead taken to represent the average data.

    Table 11 presents the best range of values (or class interval) of production rates for each activity. This is obtained by first ranging the data and then selecting the range that have the highest frequency in the raw data. One of the reasons to use range of values as the end product of the analysis is because the data‟s variance is very high. Single-value results could not be

    extracted from the raw data due to small number of responds and also the large variance that occurred. It can be observed that the range of production rate values are wide for falsework installation, BRC (mesh) fixing, skip & bucket concrete placement and brickwork laying, in which the differences between the maximum and minimum (relative to the maximum) are 70%, 64%, 70% and 67.6% respectively. However, much smaller differences in maximum and minimum and therefore more consistent production rates values are obtained for links and for loose bar fixing.

ICCBT 2008 - B - (07) - pp149-164 156

    Idrus et al

Table 7: Production Rates: Raw Data

     Production Rates

    Activity / Task Unit Interviews Questionnaire

     1 2 3 4 5 6 7 8 9 10 11 12 13 Piling m/day 680 288 300 300 100 300 450 300 400 300 700 357 150 Excavation m?/day 200 360 200 200 50 50 150 200 150 150 225 220 50 Falsework Installation m?/day 50 500 60 50 50 40 80 70 100 80 50 50 140 Formwork Installation

     Soffit Formwork m?/day 148 100 100 150 20 70 100 96 70 60 150 75 12

     Edge Formwork m?/day 110 50 60 120 20 50 60 104 40 60 120 43 12 Reinforcement Fixing

     Main bar ton/day 3 1.5 2 3 0.7 1.5 2.4 1.1 0.6 1 2.5 1 0.7

     Links ton/day 1 0.5 1 1 0.7 1 0.5 0.7 0.3 1 1 0.8 0.7

     BRC (Mesh) m?/day 900 400 600 1000 150 200 400 500 100 500 850 250 150

     Loose Bar ton/day 1 0.3 0.5 1 0.7 0.4 0.5 1 0.3 1 1 0.5 0.7 Concrete Placement:

     Skip & Bucket m?/day 160 50 50 150 16 60 50 36 100 30 200 75 16

     Pumping Chute m?/day 300 150 180 275 16 180 150 320 180 160 280 200 16 Falsework Dismantling m?/day 150 1000 150 150 100 80 160 100 130 160 150 125 100 Formwork Dismantling m?/day 320 50 150 300 40 120 150 120 100 120 300 165 24 Brickwork Laying m?/day 190 40 100 150 18 50 30 32 40 80 200 80 18

    ICCBT 2008 - B - (07) - pp149-164 157

    Towards Development of a Database for Civil & Structural Construction Works’ Production Rates

     Table 8: Production Rates: Variance Analysis based on Contractor Class

     Production Rates

    Contractor Class (PKK) Activity /Task Unit

     A B Unknown Piling m/day 300 100 300 288 300 400 300 700 357 150 450 680 300 Excavation m?/day 200 50 50 360 200 150 150 225 220 50 150 200 200 Falsework Installation m?/day 50 50 40 500 70 100 80 50 50 140 80 50 60 Formwork Installation

     Soffit Formwork m?/day 150 20 70 100 96 70 60 150 75 12 100 148 100

     Edge Formwork m?/day 120 20 50 50 104 40 60 120 43 12 60 110 60 Reinforcement Fixing

     Main bar ton/day 3 0.7 1.5 1.5 1.1 0.6 1 2.5 1 0.7 2.4 3 2

     Links ton/day 1 0.7 1 0.5 0.7 0.3 1 1 0.8 0.7 0.5 1 1

     BRC (Mesh) m?/day 1000 150 200 400 500 100 500 850 250 150 400 900 600

     Loose Bar ton/day 1 0.7 0.4 0.3 1 0.3 1 1 0.5 0.7 0.5 1 0.5 Concrete Placement:

     Skip & Bucket m?/day 150 16 60 50 36 100 30 200 75 16 50 160 50

     Pumping Chute m?/day 275 16 180 150 320 180 160 280 200 16 150 300 180 Falsework Dismantling m?/day 150 100 80 1000 100 130 160 150 125 100 160 150 150 Formwork Dismantling m?/day 300 40 120 50 120 100 120 300 165 24 150 320 150 Brickwork Laying m?/day 150 17.5 50 40 32 40 80 200 80 18 30 190 100

    ICCBT 2008 - B - (07) - pp149-164 158

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