Site Inspections And Accidents On Jamaican Construction Sites Construction Essay

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The report incorporates several decision- making techniques to analyse, estimate, test, predict and ultimately make correct decisions obtained from data collected. It illustrates the use of Regression analysis, Standard Deviations, Grid Analysis, Cause and Effect diagram as well as using computer model programme such as Microsoft Excel to test the relationship between the numbers of inspections carried out and the number of reported injuries on construction site in Jamaica between 1996 and 2003. The decision is to provide the Ministry of health with a formula or a relationship that is to be used to predict or forecast the amount of reported accidents that occur on a construction site in a year. The results show that there is a positive relationship between the two variables, but it is proven to be weak.

Background and Introduction

The Ministry of Health Jamaica, due to budgetary constraints, can only afford to conduct 150 inspections for the coming year and they would like to have an idea as to the number of reported accidents from the construction industry in previous years. This would be used as threshold with which they can anticipate as it would be measured against the number of inspections conducted. We are construction students of Heriot Watt University and we have been consulted by the Ministry to conduct a research that will allow the Ministry to forecast the number of injuries that may occur on construction sites. This is to aid them in making better decisions as to how they should allocate funds towards better accident responses by the hospitals. We will be capable of determining and informing the Ministry on the amount of injuries to expect.

The Occupational Health and Safety Department defines the term 'accident' as

"An unplanned event that results in the damage to or loss of property, limb or life. The law requires that an accident be reported if it results in an employee being required to be absent from work for more than two days."

These unplanned events can prove to be very dangerous on site. Construction is generally considered one of the most dangerous jobs in the world. As reported by Valerie Banner (2008), "According to 2006 data from the U.S. Bureau of Labour Statistics (BLS), construction workers, miners, and pilots actually have some of the riskiest jobs."

Health and Safety involves wearing safety gear on site, taking precautions and being aware as well as implementing good Health and Safety practices. The culture of the workers in Jamaica does not facilitate good Health and Safety practices. Due to prices for materials, labour and equipment being high, generally contractors try to cut their costs as best as possible to remain competitive. Unfortunately Health and Safety is one of the areas in which the contractors tend to cut on cost. Implementing good Health and Safety practices and providing the proper gear comes at a cost and most workers prefer not to wear the proper gear and it is said to "slow them down" or the workers do not take good care of the gear and generally lose or destroy them. So the thought in many cases is 'Why waste money on the gear if the workers are not going to wear it or take care of it? ' Top management may provide the gear and budget for Health and Safety but do not emphasise the importance and rivet the concept of safety in the minds of the workers on site. Another contributing factor to the malpractice is due to the lack of rigidity of the Health and Safety regulatory bodies in Jamaica.

This general topic is of major interest in the construction industry on a whole, due to the number of incidents that may occur per year. Also, the magnitude of the repercussions and the adverse effect they have on the success of the project, in terms of budget and time overruns. As future construction project managers we must be aware of these possible effects, how they come about and even more importantly, how they can be prevented or reduced; this is where site inspections come into play. At no point will we be able to fully neglect the idea that injuries will occur on site. Accident will always occur, even if the best Health and Safety mechanisms are in place to reduce injuries on site, so adequate provisions have to be made for these cases regardless. So the Ministry of Health is trying to provide a "safety net" for those cases, despite the low budget.

Overview

Problem statement

We aim to give the Ministry of Health a means to forecast the amount of injuries that may occur on construction sites based on the number of inspection carried out per year.

Rationale

Occupational Health and Safety is an integral aspect of any construction project. Health and Safety has generally been an issue of great consideration in the construction industry for years. On a typical construction site people are working with heavy machinery, working at high elevations, working in the sun and dust and these are some of the characteristics of the universal construction-working environment. As such, it is considered one of the most dangerous working environments in the world.

We as a group of future construction project managers must be well informed of the various concepts that fall under Health and Safety. We were conducting a research on Health and Safety in the construction industry in Jamaica and during our research we realize the need of the health Ministry. As a group, we had a consensus in idem, and decided that we wanted to contribute with the aim of making a difference. The group wishes to aid in the improvement of the construction industry as well as provide information that will help the country on a whole. The Ministry has a duty of care under Tort, and they seem to be proactive in maintaining their duty. Furthermore, we are also very serious about conducting our research whilst helping the Ministry. Our group is generally, collectively interested in finding out the relationship between the two variables (number of site inspections per year and the number of injuries reported per year) as a means of projecting number of accidents based on the inspections carried out for that year.

Definition of variable

The independent variable of this research is the number of site inspections in the construction industry per annum. In Jamaica site inspections are carried out by the Industrial Safety/ Occupational Health and Safety Department of the Ministry of Labour and Social Security. They are generally responsible for monitoring and enforcing safety regulations in accordance with the Factories Act and its accompanying regulations. The Ministry refers to construction site inspections as monitoring of the site working conditions; monitoring the site is done in accordance with Building and Works of Engineering Construction Regulations (1968). Some of the main heading of the regulations under the Factories Act (1986) are:

Safety of work places and means of access and regress

Lifting appliances

Chains ropes and lifting gear

Special provisions as to hoist

Carriage of persons and secured loads

Supervision of safe conduct of work

Excavation, shafts and tunnels

Explosives

Work on or adjacent to water

Demolition

During safety inspections, the inspector has a checklist that he is to fill out based on what he discovers on site. The general headings of the checklist should correlate to the main heading under the regulations and should encompass questions to be answered based on what is happening on that particular site, to ensure the site is maintaining good Health and Safety practices.

The dependent variable for this research is the number of reported injuries that occur on construction sites per year. An injury is any physical damage to an individual's body that may render that individual unable to carry out certain natural bodily functions. Some of the major injuries that occur on site include falls from high levels, being struck by moving (flying or falling) object, being struck by a moving site vehicle, slips, trips or falls, injuries by handling, lifting or carrying. On a construction site, injuries usually cause delays and incur additional costs. An injury that occurs on site will require immediate attention and other site personnel will try to aid the injured individual, hence, taking away from their onsite responsibilities, as well as the fact that there is one less worker (the injured individual), so reducing productivity and in turn causing time delay. In the case of critical injuries that may even involve the individual being hospitalized, the contractor is responsible for issuing the 'workman's compensation' which is payments to be made to the employee, by law, for work related injuries; thus increasing cost for the project. In addition, the further time and cost of hiring a replacement to complete the task also affect the success of the project.

It is assumed that a large percentage of the injuries that occur on construction sites are not reported. But not all injuries need to be reported. Major injuries should be reported. According to Reporting of Injuries, Diseases and Dangerous Occurrences Regulations (RIDDOR) "reportable injuries include:

fracture, other than to fingers, thumbs and toes;

amputation;

dislocation of the shoulder, hip, knee or spine;

loss of sight (temporary or permanent);

chemical or hot metal burn to the eye or any penetrating injury to the eye;

injury resulting from an electric shock or electrical burn leading to unconsciousness, or

requiring resuscitation or admittance to hospital for more than 24 hours; any other injury:

leading to hypothermia, heat-induced illness or unconsciousness; or requiring resuscitation;

or requiring admittance to hospital for more than 24 hours;

Unconsciousness caused by asphyxia or exposure to harmful substance or biological agent;

Acute illness requiring medical treatment, or loss of consciousness arising from absorption of any substance by inhalation, ingestion or through the skin.

Acute illness requiring medical treatment where there is reason to believe that this resulted from exposure to a biological agent or its toxins or infected material."

Source of the data

The Ministry of Labour and Social Security is the home to the Occupational Health and Safety Department who is responsible for monitoring occupational Health and Safety. This was the main source of the data we obtained for both variables. The fact that the data for both variables were obtained from the same place speaks to the reliability and consistency of the data. One of the services that the Occupational Health and Safety Department offers is that of preparation of annual statistics for Planning Institute of Jamaica (PIOJ) and the Statistical Institute of Jamaica (STATIN) which are the major statistical bodies in Jamaica. The department also provides the data for the International Labour Organisation (ILO). They are some of the reputable bodies that deals with statistical data for national and international use and this speaks to the validity of the data obtained based on the source.

Secondary, qualitative data about the actual regulations and the monitoring bodies were obtained via the internet. Some basic information on the overall topic were acquired from informally questioning Mr. Raymond Cooper, managing director of Cooper and Associates Limited and the current president of the Incorporated Master Builders Association of Jamaica (IMAJ). General information about the research topic was obtained by asking people in the construction industry informally, more information was also obtained via use of the internet and published report.

Explanation of the Techniques used

Cause and effect diagram

Generally the cause and effect diagram (also referred to as Fishbone/Ishikawa diagram) identifies the main causes for the dependent variable (accidents of construction sites). The diagram works from the head of the "fishbone", questioning why it occurred, and then repeating the question for each of the underlying problems identified. So generally the diagram is read in reverse. It highlights causes for accidents and several primary factors. The main factors themselves have contributory causes which are also illustrated as branches coming from the main branch.

Grid Analysis

When there is a decision to be made and there are a number of good alternatives and more than one factor to take into consideration, a grid analysis is an effective technique to use for making the decision. This technique is used to analyze qualitative data. The grid analysis as the name suggests is done in a grid format where the options are listed as the row headers and the factors are listed as the column headers. The next step would be to work out the relative importance of the factors in the decision; these should be rated/ evaluated from a scale ranging from 0-5. These numbers are used to weigh the preferences by the importance of the factor. Where these values are not obvious, a Paired Comparison Analysis can be used to estimate them. This is done by comparing each option with the other options and determining the preferred option in each case.

The next step is to work across the table rating/scoring each option for each of the important factors in the decision. Each score is then multiplied by the values for the relative importance. The weighted scores are totalled for each option. The option with the highest overall total is to be selected.

Averages and Standard Deviation

The averages are done to give the one figure from the data that can represent all the data points of that variable; averages are approximations of the statistical norm. The median is an average based on the figure that is found in the middle of the data points when they are set out in numerical order. The mean is a calculated average which involves finding the sum of the data points and then dividing the sum by the number of data points. The mean is the average figure that is used in determining the Standard Deviation.

The standard deviation measures the variation between data points of a variable; measures the 'spread' of data about the mean value. It is calculated by finding the square root of the variance.

Variance = (x- xbar)2

n-1

Therefore the standard deviation, denoted by the lower case sigma, is given by the formula:

x bar represents the value for the mean

Regression Analysis:

In general, regression analysis is a statistical technique that attempts to predict the values of one variable using the values of one or more variables. By principle, the variable that we are trying to predict is called the dependent variable and the variable that we are using as predictors of that variable are called independent variable. For example, we might wish to explain the relationship between area of residence and income. It can be determined right away that income is the dependent variable and that area of residence is the independent variable not only because there is a positive relationship but also because persons who reside in up-scale communities usually have higher income and the reverse. An independent variable is one whose values do not change based on the change of the other variable, on the other hand, the dependent variables' value is reliant on the value of the other variable. Regression analysis allows an individual to make a statistical forecast of a value for the dependent variable based on a value for the independent variable by creating a mathematical relationship. Regression analysis also allows us to assess how accurately an independent variable predicts a dependent variable. Regression analysis involves the use of mathematical formulae to create a statistical relationship between two variables, this is done by first determining a 'reference point' which is represented by the value for the intercept denoted by an 'a'. A figure is then added to the reference point to give the predicted value for the dependent variable, this figure is the product of the slope or gradient and the predictor value (the independent variable).

So the general formula for the relationship is also termed the relationship for the line of best fit is:

y = a + bx

In the case of this report, our independent variable is the number of inspections that are done on construction sites per year and the dependent variable is the number of reported injuries that occur on construction sites per year. Carrying out a regression analysis on these two variables will give a general statistical relationship as well as give an idea of the accuracy with which the number of inspections that are done on construction sites per year can predict the amount of accidents likely to be reported in a given year.

Data Analysis

Grid Analysis:

For this report the factors are:

Minimize Costs

Reduce Accidents

Maintain Project Schedule

Increase Productivity

The options are:

F1. Safety Training

F2. Equipment Handling

F3. Site Inspection

F4. Management Supervision

Grid Analysis

Objectives

A

B

C

D

Relative importance of the objectives

3

4

2

1

F1

2

3

1

0

F2

3

4

2

3

F3

3

4

3

3

F4

4

2

3

4

F5

1

4

1

1

F5. Use of Personal Protective Equipment (PPE)

Results

Objectives

A

B

C

D

Total

F1

6

12

2

0

20

F2

9

16

4

3

32

F3

9

16

6

3

34

F4

12

8

6

4

30

F5

3

16

2

1

22

Averages and Standard deviation:Regression analysis:

Year

Number of Accidents Reported

1996

191

1997

145

1998

194

1999

223

2000

273

2001

95

2002

106

2003

104

TOTAL

1331

Standard Deviation

Mean

166.375

Median

168

Standard Deviation

64.40039374

Regression Analysis:

Year

Number of Inspections

Number of Accidents Reported from

1996

61

191

1997

48

145

1998

154

194

1999

168

223

2000

148

273

2001

157

95

2002

129

106

2003

126

104

SUMMARY OUTPUT

 

 

 

Regression Statistics

 

Coefficient of correlation

0.312984261

R Square

0.097959147

Adjusted R Square

-0.052380995

Standard Error

66.06554483

Observations

8

ANOVA

 

df

SS

MS

F

Significance F

Regression

1

2843.937721

2843.93772

0.651583

0.450352827

Residual

6

26187.93728

4364.65621

 

 

Total

7

29031.875

 

 

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Intercept

115.6866902

66.99815475

1.72671457

0.134966

-48.25188833

X Variable 1

0.43138987

0.534422732

0.80720719

0.450353

-0.876295445

Upper 95%

Lower 95.0%

Upper 95.0%

279.625269

-48.2519

279.6252688

1.73907519

-0.8763

1.739075185

RESIDUAL OUTPUT

PROBABILITY OUTPUT

Observation

Predicted Y

Residuals

Percentile

Y

1

142.0014723

48.99852768

6.25

95

2

136.393404

8.606595995

18.75

104

3

182.1207303

11.87926973

31.25

106

4

188.1601885

34.83981154

43.75

145

5

179.9637809

93.03621908

56.25

191

6

179.9637809

-84.96378092

68.75

194

7

171.3359835

-65.33598351

81.25

223

8

151.0606596

-47.0606596

93.75

273

Scattergram:

Interpretations and Conclusions of Results

Cause and effect diagram result:

They are the issues with which we have found to be the main factors, which results in accidents on construction sites in Jamaica.

Few or Limited Personal Protective Equipment (PPE)

Little or No Safety Training

Improper use of Equipment

Poor Management Supervision

Inadequate Inspection

Improper disposal of waste

Personal protective equipment (P.P.E)

These are safety gear, which workers are to attire themselves in while caring out their respective duties. Failure to do so generally lead to workers been vulnerable to injuries such as: eyes illness, respiratory illness, head, hand and foot injuries, etc. Examples of PPE are hard hats, steel toe booth, goggles, respirator, facemask, etc.

Safety Training

This involves workers been educated not only about PPE, but also of the procedures on how to execute their respective tasks in a safe manner. This is to achieve a safe work environment.

Improper use of Equipment

This has been a repeated issue on several construction sites for a number of years, as workers tend to misuse equipment. Failure to use as intended, leads to abuse the plant, which leads to malpractices that are prone to accidents.

Inadequate Inspection

This is one of the most crucial aspects of Health and Safety legislation as plant, working conditions; sanitary facilities, etc. need to be checked regularly to ensure that all personnel are adhering to the Health and Safety regulations. This is necessary to reduce/minimize accidents/illnesses.

Poor Management Supervision

Failure by management to enforce Health and Safety regulations, in most cases, lead to workers receiving injuries/illnesses. Management has a great responsibility to ensuring that the construction site is a healthy and injury free environment.

Improper disposal of waste

If disposal site are not established on site, workers will be forced to place their material and others waste in an unauthorized location. This will lead to accidents occurring as these waste materials would have been in the vicinity of the workers while they are doing their respective job.

Grid analysis results:

The results show that F3 - site inspection is the preferred choice.

Average and standard deviation analysis

Based on the type of data, the mode could not be used to determine the average because there are no reoccurring values. The mean was determined by dividing the sum of the data points by the number of data points. The mean value is 166.375 and the median is 168.

The standard deviation is 64.40039374, this means that the actual data points are not very close to the line of best fit and that is the deviation, that is how far off the values are. So any interpolation values calculated would be plus or minus 64.40039374.

Regression analysis results

a = 115.6866902

b = 0.43138987

r = 0.312984261

As mentioned before, the regression analysis allows us to make qualitative predictions for the dependent variable based on the values of the independent variable. In this research our independent variable (x) is the number of inspections that are done on construction sites per year and the dependent variable (y) is the number of injuries that occur on construction sites per year. The forecasting relationship formula is also the general formula for the line of best fit:

y = a + bx

'a' is termed the intercept, the calculations provide us with the figure of 115.6866902, this is the value at which the line of best fit would meet or cross one of the axes; this figure serves as a reference point on which the product of the gradient/ slope and the 'x' value that you are basing your prediction on. 'b' is termed the slope, also known as the gradient of the line. According to the calculations the slope is 0.43138987, this figure speaks to the extent of the incline of the line of best fit on the graph. Therefore the formula could be re-written:

Y = 115.6866902 + 0.43138987x

So with a random value for 'x', 'y' can be determined by plugging in the value for 'x' in the formula. This is the formula that the Ministry of Health requires for their project.

The Coefficient of correlation (r) is 0.312984261 which means that the values plotted on the graph are far from the line of best fit. The closer the coefficient is to 1 or -1 is the closer the plotted values are to the line of best fit. Therefore the predictions based on this relationship will not very accurate, but still gives a reasonable estimate to the predictions. The amount of inspections that can occur on site in one year (based on the Ministry's budgetary constraints) is known and that figure falls within the range of the data. So the fact that the Ministry is to interpolate allows the predicted figure to be accurate, as far as it can with this coefficient figure.

Conclusive statement

To conclude this research report, we look at the main objective and the results to ensure that the main objective has been covered and our results are in conjunction with the main objectives. In viewing the results, we can see that the relationship between the two variables is positively related but weak; therefore no accurate predictions can be made from the relationship. From the data and the calculations we have learned that the standard deviation for any predicted value would be + or - 64.4. Which means the value would not be very accurate. Based on our calculations the relationship formula is:

y = 115.6866902 + 0.43138987x

So with the ministry's decision to conduct 150 inspections per year, the corresponding value for the number of reported injuries would be:

115.6866902 + 0.43138987(150) = 180.3951707, rounded down to 180

Therefore in the case that only 150 inspections are done within the year on construction sites in Jamaica, the construction industry would have 180 reported injuries for the year.

Limitations

Due to unforeseen time constraints we were forced to obtain data from alternative means. Our aim was to obtain primary data from some of the main statistical institutes, but they requested a very particular protocol which would involve waiting indefinitely. We followed the protocol for one of the institutions but decided as a group to try and move along with different valid, paired data. Upon our last group meeting we did not receive any feedback from the various institutions. Due to the circumstance we had no choice but to make a good group decision within the limited time.

Information accessibility proved to be very problematic, the data that was obtained was paired data and based on our results from the regression analysis we learned that the accuracy of the predicted value based on our relationship formula (formula for the line of best fit) would be low. This could be attributed to the fact that we did not have as much data points to use, because more data points would have given a more reliable and accurate result.

Appendix

Regression Analysis Breakdown of functions (done in MS Excel)

Year

Number of Inspections (X)

Number of Accidents Reported (Y)

XY

X2

Y2

No.:

SD

1996

61

191

11651

3721

36481

8

60.24105

1997

48

145

6960

2304

21025

1998

154

194

29876

23716

37636

1999

168

223

37464

28224

49729

2000

148

273

40404

21904

74529

2001

157

95

14915

24649

9025

2002

129

106

13674

16641

11236

2003

82

104

8528

6724

10816

SUM

947

1331

163472

127883

250477

Calculations Key:

n(Σxy)

1307776

(Σx)2

1260457

n(Σx2)

1023064

(Σx)2

896809

(Σy)2

1771561

n(Σy2)

2003816

n(Σx2) - (Σx)2

126255

n(Σy2) - (Σy)2

232255

√(n(Σx2) - (Σx)2)

355.323796

√(n(Σy2) - (Σy)2)

481.9284179

n(Σxy) - (Σx)2

47319

√(n(Σx2) - (Σx)2) x √(n(Σy2) - (Σy)2)

171240.6349

b(Σx)

354.925294

Σy - b(Σx)

976.074706

Slope 'b'

0.374789117

Intercept 'a'

122.0093382

Coefficient correlation 'r'

0.27633044

Raw data from Ministry of Labour and Social Security

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