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Effect of Weather on Construction Labour Productivity

Paper Type: Free Essay Subject: Construction
Wordcount: 2967 words Published: 10th Jul 2018

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Effect of Hot and Cold Weather on Construction Labour Productivity

EXECUTIVE SUMMARY

The research deals with the variation of labour productivity in extreme weather conditions in India. As we head more and more into the rural areas for construction the labourers are faced with unprecedented weather conditions as extreme cold and heat stress combined with other geographical factors. We compare the difference in productivity achieved in normal weather conditions with extreme cold locations as Kargil and hot regions as Ahmedabad. Further this is compared by the standards set by IS 7272 for ideal productivity. After studying the results recommendations are done specifically for domestic projects considering the situations prevailing in India and future weather uncertainties.

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CHAPTER – 1: INTRODUCTION

BACKGROUND OF THE STUDY

An Industry ultimately thrives upon the physical input put in by the labourers and the construction industry is no exception, in fact the construction industry is one of the most labour dependent industries operating in India. It is the groundwork of the labourers, which ultimately runs this industry. Though lot of work has already been done to optimize labour productivity around the world, majority of the projects still stay behind schedule and are completed with cost and time overruns, though this might be due to multiple reasons but labour productivity still dominates the final output.

With the increase in population the infrastructure and public wealth construction is being pushed more and more into the rural areas which are untouched in the last century. Thus are the studies, which prevailed in earlier times about the productivity, as these new regions put up new challenges of the working environment. Not much has been done to check the productivity changes in these regions, this often results in variation from the IS values which should be attained ideally.

OBJECTIVES

Our objective of this research is to study and outline the factors, which are, determinable in altering productivity outputs in adverse weather. To compare the factors stated in IS 7272 with actual ground data for productivity achieved on construction site and suggest methods to counter. This would further transform into meeting project milestones in time.

SCOPE OF WORK

The research work is based on actual site data collected from different construction sites in India. It aims to study the variations observed if any from the standards in the IS 7272 for labour productivity and the reasons leading to these changes. It covers both extremes of the temperature in its study hot and cold regions, finally suggesting the measures to be taken to optimize labour output in extreme weather conditions.

RESEARCH METHODOLOGY

The methodology adopted to prepare this report ranged from reviewing work previously done in these areas of labour productivity along with site visits and collection of data. We reviewed papers from journals and tried to draw a few conclusions by correlating the studies and common factors in the research papers. Data collection was done by visiting sites of projects under progress across India. For the sake of comparison with other site data to keep maximum parameters same we worked on productivity for the activities which were common to both the sites. Data was collected over different periods of duration with respect to every project and analysed for their productivity calculations. These calculations were further compared with the standards set by the IS 7272. Further we attempt to outline the factors which may be the probable cause for the deviation and suggest remedial measures to counter them.

LIMITATION OF STUDY

Since the data was collected from sites in India and the observations made were from Indian gang of labourers, the results and study are limited to Indian subcontinent. Also ideally for comparison there should be similar situation of work with less variables such as work type and other conditions other than the weather, but due to the limitation of the projects the sites were not executing similar projects, thus the data cannot be said to be 100% precise. Although we have put in our best efforts to counter this by selecting similar activities of execution. Furthermore due to the limitation of availability of data the results achieved cannot be said to depict the conditions prevailing all through India as more work is awaited on this topic in India.

CHAPTER – 2: LITERATURE REVIEW

To study the work previously done research in this area we studied numerous papers published on Productivity from various journals across the globe. Though it was out observation that the research work was more or less biased to the productivity concerns due to increasing temperature, and less about the colder conditions. India being a tropical country experiences both extremes of the climate through the year, thus we review work done in colder regions too, a few of our findings are as follows.

Tord Kjellstrom, PhD; R. Sari Kovats, MSc; Simon J. Lloyd, MSc; Tom Holt, PhD; Richard S. J. Tol, PhD studied the changing pattern of temperatures across the globe, which will ultimately lead to a global climate change and an increase in heat load and will degrade the productivity of workers in the coming future. It was a region-based study where they established a relationship between the rise in temperature and loss of productivity as a percentage drop. The study was localized for a much accurate assumption, overall there was a loss in productivity with the increase in temperature.

Meglan, Meglan & Company Ltd. outlined in their publication Construction Claim Topics the loss of productivity due to effects of weather the reasons for loss. They subdivided their study into three subcategories Low temperature and Wind chill, high temperature and humidity & Wind only effects. They stated that the loss of productivity occurs In all three conditions due to different factors in each conditions. They stated that a drop of as much as 50 % can be observed in extreme situations. They established a fact that humidity also played a detrimental role in the loss as at the same temperatures the change in productivity was evident with the change in humidity levels at the site.

Adham Shahin, Simaan AbouRizk, Yasser Mohamed and Siri Fernando developed a simulation based framework for quantifying the cold weather region impacts on construction scedules, the framework composed of components that help in understanding and simulating construction projects. The basic aim of this framework is to enable the researcher to quantify the impact of weather alterations on project schedule. The process involves the creation of a basic discreet simulation model to simulate the activities on site.

An article published in THE Monitor | Climate stated the economic impact of the increasing temperature uncertainty across the globe, they forecasted the future developments for the year 2030 where the prediction is of 450 hotspots from the 55 existent today. In 2030 the expected loss is 413 billion USD. In their country level impact analysis they have plotted a country wise loss index in which India comes under the Acute category forecasting a loss of 450,000 million US $ additional economic cost in 2030 only due to increase in temperature of working environments of labourers. They suggest adaptation to the new environment is the most cost effective measure, which can be taken against this.

Yildirim, Kemal. Koyuncu, Cuneyt. Koyuncu, Julide. In their paper does temperature affect labor productivity: cross- country evidence published in the journal Applied Econometrics and International Development. They established a relation between temperature and labour productivity and plotted a graph to depict it. The study done over 111 over a period of several years’ states that increase in temperature has a negative effect on labour productivity.

Pieter Diedericks
 Senior Project Director, Oil Sands Projects, Petro-Canada, Canada in his study OPTIMIZING WINTER CONSTRUCTION studied the effects of cold weather on construction industry. He used temperatures below 200 F as the basis of cold temperature. He stated that an average loss of labour productivity due to cold temperature is almost 50%. Thomas suggested the use of annual cycles to schedule activities most affected by weather. He suggested remedial measures as use of wind protective armour and setup of machinery when the conditions are adverse instead of physical labour-intensive work.

Karin Lundgren1*, Kalev Kuklane1, Chuansi Gao1 and Ingvar Holmér1 presented a paper on Effects of Heat Stress on Working Populations when Facing Climate Change, Their study relates o heat stress on workers and how it negatively impacts the productivity overall. They suggested the ideal temperature for physical work as 370C, any more beyond these results in physiological effects in the human body reducing its capacity to perform productively.

CHAPTER – 3: LABOUR PRODUCTIVITY THEORY

WHAT IS LABOUR PRODUCTIVITY

Labour productivity as defined as the amount of output received by the number of man hours or man days input by the worker. Labour productivity optimization is needed to get the optimum output from a projects workforce, thus is also termed as workforce productivity. In the construction industry which is predominantly labour intensive this factor plays a determinable role in deciding the fate of the project itself. And in a country like India where there is cheap and efficient labour available, if used properly the production costs can be brought down drastically, be it of any industry in this scenario. Labour productivity can be measured in number of ways depending on each industry but the thumb rule for calculation of labour productivity is

Labour productivity = volume measure of output / measure of input use

WHY MEASURE LABOUR PRODUCTIVITY?

In the construction industry most of the contractors take careful note of variation in local and regional weather patterns, the norms andtrends, and based on these they schedule their construction projects. Well planned construction schedules are prepared to take advantage of favorableseasonal, local, or regional weather patterns and avoid the unfavorable ones.

Thus, when a Project doesn’t start on time, or it gets delayed during the time of execution weather may become an all important factor in the overall delay, reducing planned productivity and efficiency. Most of the construction contracts allow excusable delay and time extensions at the time of abnormal or unusual weather conditions. When this kind of delay is encountered it incursenormous losses in the number of extra man hours spent, and further delays of the project and work.

Hot weather and cold weather create efficiency and productivity losses which can be explained separately as follows:

Cold Weather

Workers productivity drops with the fall in temperature. The productivity of the manual labours drops gradually during extreme temperature conditions. This productivity losses can be best quantified by comparing productivity from cold weather effected work periodsto that measured during normal work periods, thereby determining the difference. It only requires man-hours data and weather data (can be obtained from internet), sorted by date. The man-hours and temperature data are entered into a spreadsheetprogram by date any their productivity is calculated.

Hot Weather

Just as the productivity decreases in cold weather, same losses also occurs when the temperature rises above twenty nine degree centigrade to thirty four degree centigrade and beyond. The inefficiencies can only be quantified by actual measurement of productivity in hot weather and then comparing with normal weather productivity.

TYPES OF CONSTRUCTION LABOUR

A construction project is dependent on different levels of work done by the workers. Thus generally the division is among the levels of labourers. Namely

  1. Skilled Labor
  2. Semi Skilled Labor
  3. Unskilled Labor

SKILLED LABOUR PRODUCTIVITY

Skilled Labours constitute operators, foremen, and machine operator’s i.e the labourers with give a higher output of work per hour of input. The skilled labourers usually are head labourers for a gang, operators for special equipment and are highest paid in the lot.

SEMI SKILLED LABOUR PRODUCTIVITY

Semiskilled labours are mediocre paid workers with somewhat lesser skills as compared to skilled ones, their productivity outputs are higher per hour though compared to unskilled labourers. Carpenters, Masons, Fixers constitute this list of semi-skilled labours

UNSKILLED LABOUR PRODUCTIVITY

This is the largest clan of labourers who are good for maximum physical exertion, and it’s their tireless efforts which ultimately proves detrimental in the project being on schedule. Their productivity depends on how efficiently they are managed by their foremen. It is this clan of people we need to optimize for the drastic change in overall timing schedules.

DIFFERENT MODELS OF PRODUCTIVITY MEASUREMENT

To serve different purposes there are different measures of productivity, one can choose the method which serves their purpose.

Thomas et al. defined different models of measures to measure productivity which are as follows:

Economic models

The department of Commerce, and other governmental agencies use a productivity definition in the following form:

Equation (a)

Total factor productivity (TFP) =Total output / Labor + Materials + Equipment + Energy + Capital

Project-specific models

A more accurate definition that can be used by governmental agencies for specific program planning and by the private sector for conceptual estimates on individual projects is:

Equation (a)

Productivity=Output/ Labour+ Equipment + Materials

Equation (b)

Productivity = Square feet / rupees

Design professionals use productivity data in this form.

Activity-oriented models

A contractor is more likely to define productivity using a narrowly defined version of(a)and(b), where the units of output are specific for generic kinds of work. Typical units are cubic yards, tons, and square feet. Various related activities, such as formwork, steel reinforcement, and concrete placement, can be combined using the earned-value concept (Thomas and Kramer, 1987, cited in Thomas et al., 1990, p. 706).

Productivity is expressed as units of output per Rupee or work-hour.

At the project site, contractors are often interested in labor productivity. It can be defined in one of the following ways (Thomas and Mathews, 1985 cited in Thomas et al., 1990, p. 707)[5]:

Equation (4)

Labour productivity=Output/Labour cost

http://www.sciencedirect.com/sd/blank.gifor

Equation (5)

Labour productivity=Output/Work-hour

There is no standard definition of productivity and some contractors use the inverse of Eq.(5):

Equation (6)

Labour productivity=Labour costs or work-hours / Output

Eq.(6)is often called the unit rate. Still other contractors rely on the performance factor as a measure of productivity

Equation (7)

Performance factor=Estimated unit rate / Actual unit rate

FACTORS AFFECTING LABOUR PRODUCTIVITY

Identification and evaluation of factors that impact labour productivity has become important to determine the key elements that can be changed to bring about optimization of the entire process of work. Due to the complexity of work involved one factor alone cannot be held responsible for the change rather it is a combination of multiple factors which results in the desired/undesired change in the productivity of an individual or the project as a whole. Some of the key factors are listed as follows.

  1. Work Schedule
  2. Labour Pool
  3. Native Place of the gang
  4. Temperature
  5. Type of project
  6. Project Location
  7. Time Allocated for activities
  8. Design factors
  9. Execution plan factors
  10. Material factors
  11. Equipment factors
  12. Labour factors
  13. Health and safety factors
  14. Supervision factors
  15. Working time factors
  16. Project factors
  17. Quality factors
  18. Financial factors
  19. Leadership and coordination factors
  20. Organization factors
  21. Owner/consultant factors
  22. External factors

 

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