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Evaluation of work postures - The associated risk analysis and the impact on labor productivity

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Various musculoskeletal disorder (MSD) symptoms can be experienced by the workers performing their tasks in bad work postures which are largely static and consequently these are associated with long term risks and injuries. These postures also have a bad impact on work performance and labor productivity. In this regard, this case study research work has been conducted in a selected ceramic factory of Bangladesh with the aim of evaluation of work postures of workers working in the production section of the factory through rapid upper limb assessment (RULA) and their impact on labor productivity. The secondary objective of the research work was to draw an analysis of associated risks with the bad work posture. In order to evaluate the work postures of workers, RULA technique has been used. RULA is a widely used tool developed for the assessment of work postures which specifically examines the level of risk associated with the upper limb disorder of individual workers by scoring the different body region of the workers. The results obtained from this research work have been plotted into three main sections, namely the identification of good or bad work posture and the level of risks associated with poor work posture and their impact on labor productivity. It has been identified that most workers have been exposed to the upper limb discomfort which in turn contributes to the risk of injuries during the performance of work. Through the analysis of RULA, it has been revealed that no posture is found risk free during the investigation of work postures of workers. According to RULA grand score of 7, 43.59% of the workers need immediate investigation and changes indicating that the level of exposure to postural risks is very high and immediate ergonomics intervention to decrease the exposure to risk level seem essential. The consequence of bad work posture results in musculoskeletal disorders (MSDs) which have also been analyzed in this research work. The most commonly affected body regions found among the 39 listed workers are shoulders (92.31%), neck (71.79%), wrist (71.31%), lower back (43.59%) and upper back (41.03%). Lastly, the correlation between RULA grand score and labor productivity has been shown. The graphical analysis reveals that there is a decreasing trend of labor productivity with the higher RULA grand score establishing the fact that there exists an inverse relationship between average RULA grand score and average labor productivity.
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VOL. 10, NO. 6, APRIL 2015 ISSN 1819-6608
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EVALUATION OF WORK POSTURES - THE ASSOCIATED RISK
ANALYSIS AND THE IMPACT ON LABOR PRODUCTIVITY
Chowdury M. L. Rahman, Syed Misbah Uddin, M. A. Karim, and Mohiuddin Ahmed
Department of Industrial and Production Engineering, ShahJalal University of Science and Technology (SUST), Sylhet, Bangladesh
E-Mail: basitchy_23@yahoo.com
ABSTRACT
Various musculoskeletal disorder (MSD) symptoms can be experienced by the workers performing their tasks in
bad work postures which are largely static and consequently these are associated with long term risks and injuries. These
postures also have a bad impact on work performance and labor productivity. In this regard, this case study research work
has been conducted in a selected ceramic factory of Bangladesh with the aim of evaluation of work postures of workers
working in the production section of the factory through rapid upper limb assessment (RULA) and their impact on labor
productivity. The secondary objective of the research work was to draw an analysis of associated risks with the bad work
posture. In order to evaluate the work postures of workers, RULA technique has been used. RULA is a widely used tool
developed for the assessment of work postures which specifically examines the level of risk associated with the upper limb
disorder of individual workers by scoring the different body region of the workers. The results obtained from this research
work have been plotted into three main sections, namely the identification of good or bad work posture and the level of
risks associated with poor work posture and their impact on labor productivity. It has been identified that most workers
have been exposed to the upper limb discomfort which in turn contributes to the risk of injuries during the performance of
work. Through the analysis of RULA, it has been revealed that no posture is found risk free during the investigation of
work postures of workers. According to RULA grand score of 7, 43.59% of the workers need immediate investigation and
changes indicating that the level of exposure to postural risks is very high and immediate ergonomics intervention to
decrease the exposure to risk level seem essential. The consequence of bad work posture results in musculoskeletal
disorders (MSDs) which have also been analyzed in this research work. The most commonly affected body regions found
among the 39 listed workers are shoulders (92.31%), neck (71.79%), wrist (71.31%), lower back (43.59%) and upper back
(41.03%). Lastly, the correlation between RULA grand score and labor productivity has been shown. The graphical
analysis reveals that there is a decreasing trend of labor productivity with the higher RULA grand score establishing the
fact that there exists an inverse relationship between average RULA grand score and average labor productivity.
Keywords: labor productivity, musculoskeletal disorder, posture, rapid upper limb assessment, risk.
INTRODUCTION
Musculoskeletal disorders (MSDs) are injuries
and disorders that affect the musculoskeletal system of
human body. Various musculoskeletal disorder (MSD)
symptoms are experienced by the workers performing
their tasks in bad work postures which are largely static
and consequently these are associated with long term risks
and injuries. The disorder occurs when the body part is
called on to work harder in bad work postures. These
postures do have an adverse impact on work performance
and labor productivity. Labor is one of the most important
factors of a business organization because it is directly
related to the productivity of the system. Labor
productivity is a key indicator of successful business
efficiency, particularly for firms in which the production
process is labor-intensive like ceramics manufacturing
factory. Good and bad posture can positively and
negatively affect the labor productivity. Disorders and
stress which caused by bad work posture can lead to a
reduction in productivity and the body's ability to work
skillfully. Tuning into proper body posture can limit the
amount of stress and disorders. Additionally, a strong,
healthy worker is a productive worker and that
productivity is reflected positively in the bottom line.
There are some criteria which have a significant
impact on the ability, skills, productivity and performance
of workers such as work environment, methods of
production, wages, body posture of worker etc. Work
posture may be regarded as the position or configuration
of the limbs or body parts at the time of work. Work
posture refers to the posture that an individual is required
to adopt due to the layout of a workstation and/or the
nature of the task. Work posture has a direct impact on
worker’s performance and productivity. Poor working
posture is a common ergonomic hazard that can cause
fatigue, discomfort and injury risk, particularly at fixed
workstations such as safety cabinets, inspection or packing
workstations [1].
In this connection, this case study research work
has been conducted in a selected ceramic factory of
Bangladesh with the aim of evaluation of work postures of
workers working in the production section of the factory
through rapid upper limb assessment (RULA) and their
impact on labor productivity. The poor posture and
movement can lead to local mechanical stress on the
muscles, tendons, ligaments and joints, resulting in
discomfort in the neck, back, shoulder, wrist and other
parts of the musculoskeletal system. This is because, when
maintaining a posture, the joints must be kept in a neutral
position with the limbs, as far as possible, close to the
body, thus enabling the muscles to deliver the greatest
force. On the contrary good posture allows muscles to
VOL. 10, NO. 6, APRIL 2015 ISSN 1819-6608
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2543
work properly, decreases abnormal wear on joints, keeps
the spine from becoming fixed in irregular positions, and
prevents backache and muscular pain and resultantly
contributes to an attractive appearance.
Research objectives
The objectives of this case study research work
are:
a) To evaluate the work postures of workers working in
the production section of a selected ceramic factory
through rapid upper limb assessment (RULA).
b) To establish the correlation between the associated
risks and the bad work posture.
c) To evaluate the impact of RULA grand score of
various work postures on labor productivity.
Assessment of work posture
Body posture should be assessed for knowing the
condition of risk level as well as validity of the posture.
There are different types of methods to assess the validity
and risk level of body posture.
Ergonomic work posture assessment tools
Tools are needed in working posture assessment
so that the workplace that is safe to the workers can be
created. This includes the method for measurement and
analysis of workers physiology while they are performing
a task. In designing a proper workplace, it is necessary to
obtain relevant information on tasks, equipment, working
postures and environments.
Many of the methods such as observation
method, direct measurement method can be used for the
purpose of evaluation of work posture. The objectives of
such methods are to measure and analyze the physiology
of workers in the workplace and to make
recommendations for changes to reduce risk of injuries
and disorders. Occupational diseases have been found to
be associated with numerous occupational risk factors
such as physical work load factors including excessive
force, awkward postures and vibration. These physical
postures are being measured by ergonomic assessment
tools [2].
Review of past research works
A research work was done by D. N. Agrawal, T.
A. Madankar and M. S. Jibhakate in 2011 on ‘Study and
Validation of Body Postures of Workers Working in Small
Scale Industry through RULA’. This paper has focused the
attention on the ergonomics consideration required to be
governed in the small scale industries; a specific case of
tractor trolley manufacturing unit was considered.
Welding in this industry has been done on kneeling
posture as the fixture used for welding is placed on the
ground. Worker has to sit constantly on that posture and
has to perform the assigned welding work. It has been
observed and found that due to continuous kneeling
posture worker got fatigued frequently and
musculoskeletal problems were identified which have
been then validated by using RULA [4].
An important research work was carried out by
Tirthankar Ghosh, Banibrata Das and Somnath
Gangopadhyay in 2010 on ‘Work-related Musculoskeletal
Disorder: An Occupational Disorder of the Goldsmiths in
India’. MSDs were discussed in their papers which have
been reported in different occupations due to improper
body posture and work load. Poor design of workstation is
the mail cause of improper postures such as twisting,
bending and over reaching. These postures increase the
discomfort and pain at different body parts such as back,
neck and shoulders. By providing proper work desk, the
working condition could have been improved [5].
Another research study was conducted by Alireza
Choobineh, Sayed Hamidreza Tabatabaei,
MarziehTozihian, and Fatemeh Ghadami in 2007 on
‘Musculoskeletal problems among workers of an Iranian
communication company’. In their research, they used
Nordic musculoskeletal questionnaire and RULA in order
to find out the work related MSDs and it was observed that
there has been very high score of RULA (action level 3
and 4). RULA score can be reduced by designing
ergonomic workstation and it may reduce the WRMDs
among the workers. RULA shows that the awkward
working postures and static work are found to be the major
risk factors that the workers encountered. Improper design
and poor arrangement of workstation are the causes of
postural problems and could be cured by redesigning the
workstations based on ergonomics principles that will
reduce the RULA Grand Score [6].
METHODOLOGY
The action plan followed in conducting this case-
study research work is shown in Figure-1.
Figure 1. Research methodology.
Work posture evaluation method using RULA
VOL. 10, NO. 6, APRIL 2015 ISSN 1819-6608
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Among the assessment tools to evaluate the work
posture however, RULA - a pen paper based observation
method is widely being applied in many industries. RULA
is a commonly used tool developed for the assessment of
work postures which specifically examines the level of
risk associated with the upper limb disorder of individual
workers by scoring the different body region of the
workers. In this research work, the RULA work sheet
scoring system has been used to gather the overall score
for the designated workers working in the production
section of the selected ceramic factory.
The Rapid Upper Limb Assessment (RULA) was
developed by Dr. Lynn McAtamney and Dr. Nigel Corlett
of the University of Nottingham's Institute of Occupational
Ergonomics. It was first described in a 1993 issue of the
journal ‘Applied Ergonomics’. This ergonomic technique
evaluates individuals' exposures to work postures, forces
and muscle activities that have been shown to contribute to
Repetitive Strain Injuries (RSIs). Use of this ergonomic
evaluation approach results in a risk score between one
and seven, where higher scores signify greater levels of
apparent risk. A low RULA score does not guarantee that
the workplace is free of ergonomic hazards and a higher
score does not assure that a severe problem exists. It was
developed to detect work postures or risk factors that
deserve further attention [3].
DATA COLLECTION AND ANALYSIS
The objective of data collection and analysis is to
screen and format the data of various work postures into
necessary form and then to analyze the structured data to
identify the good or bad posture of workers in order to find
out the rapid upper limb assessment (RULA) grand score.
Data analysis through RULA worksheet
At first the various work postures of workers
have been observed in the view point of RULA. Then the
observed work postures have been evaluated in terms of
RULA score sheet. According to this method, a score is
calculated for the position of arms, wrists, neck, trunk and
leg. Score 1 indicates the most neutral posture and
gradually increasing scores shows the worst position. The
combined individual scores for arm and wrist provide
group A score and neck, trunk and leg provide group B
score of RULA worksheet. Muscle use and muscle force
are attributed to a score of 0 or 1. These scores are added
to Table A and B scores to obtain the final arm and wrist
score as well as final neck, trunk and leg position score.
After that these two scores are compiled in table C of
RULA worksheet in order to obtain the RULA grand
score.
The range of RULA grand score is 1 to 7 which
indicates different terms and conditions. Higher RULA
score indicates the lower validity of work posture and
higher risk. On the contrary, lower RULA score indicates
the higher validity of work posture and association of
lower risk. The various ranges of RULA grand score and
the regarding decisions about work posture is shown in
Table-1. According to the table, green color is used for
good work posture and red color is used for bad work
posture.
Table 1. Elaboration of RULA grand score.
RULA Grand Score Decision about Posture
1-2 Posture is acceptable if it is not maintained or repeated for long periods.
3-4 Further investigation is needed and change of posture may be required.
5-6 Further investigation and changes are required soon.
7+ Investigation and changes are required now.
Evaluation of RULA grand score
After the evaluation of RULA grand scores
through RULA worksheet for various work postures of a
certain number of workers working in the production
section of the selected ceramic factory, these 39 workers
have been arranged according to their relevant scores and
the percentage of workers for different scores is shown in
the Table-2 accordingly.
Table 2. RULA grand score of different workers
RULA
grand score Number of
worker Percentage
4 6 15.38%
5 6 15.38%
6 10 25.64%
7 17 43.59%
It has been found that the RULA grand score for
6 workers is 4 and 5 respectively. Moreover, for 10
workers the grand score is 6 whereas for 17 workers the
score is 7. From the Table-2, it is evident that the no
VOL. 10, NO. 6, APRIL 2015 ISSN 1819-6608
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workers have acceptable work posture and most of the
workers are working in high posture related risk.
The relative percentage of the workers for various
RULA grand scores is plotted in the Figure-2 accordingly.
It has been identified that no existing posture is valid
according to the standard of RULA. Further investigation
or change may be required of 15.38% workers because
their RULA grand score is 4. Further investigation or rapid
changes of posture is required of 41.02%
(15.38%+25.64%) workers as they have the score of 5 or
6. Must investigation and immediate changes of posture is
needed for 43.59% workers because they have the very
high RULA grand score of 7+.
Figure-2. RULA grand score Vs percentages of workers.
Analysis of risk level by RULA grand score
The RULA grand score has been compared to
different levels of risk. However this comparison provides
us with a guide line for further action. In most cases, this
guide line is used as an aid in efficient and effective
control of any risks identified, the actions lead to a more
detailed investigation. Table-3 represents the risk level of
39 workers according to RULA grand score. In this table
different risk levels have been categorized with the
different ranges of RULA grand score.
Table 3. Analysis of risk level.
RULA grand
score Risk level Percentage
1-2 Low -
3-4 Intermediate 15.38
5-6 High 41.02
7+ Very High 43.59
The relative percentage of workers in association
with various RULA grand scores against different risk
levels is plotted here in the Figure-3.
Figure-3. Risk levels Vs percentages of workers.
Figure-3 shows that there have been no workers
found in low risk level. It has been observed that the
RULA grand score of 15.38% of the studied workers is in
between 3 and 4 which represents the intermediate risk
level and indicates the level of exposure to postural risks
needed considering. The RULA grand score of 41.02%
(15.38%+25.64%) workers is in between 5 and 6
indicating that the level of exposure to postural risks is
high and ergonomics intervention to decrease exposure
level seems necessary. The RULA grand score of 43.59%
workers is 7 indicating that the level of exposure to
postural risks is very high and immediate ergonomics
intervention to decrease the exposure to risk level seems
essential.
Analysis of risk frequency
The data of the pain and discomfort of five body
regions (shoulder, elbow, wrist, upper back, lower back)
have been collected and categorized into three levels. If
the disorders occur quarterly the risk is considered to fall
in intermediate level, if the disorders occur monthly the
risk is in high level and if the disorders occur weekly or
daily, the risk is considered to fall in very high level.
These terms and condition have been tabulated together
with the categorization of three levels of risk frequency in
Table-4. Table-4. Risk frequency category.
If disorders occur Risk frequency
Never No
Quarterly Intermediate
Monthly High
Weekly Very High
In the following Table-5, the percentage of risk
frequency of five important body regions of 39 workers
has been tabulated. The association of risks level with
these body regions has also been found out here with the
help of t-test.
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Table 5. Analysis of risk frequency and association of risks with body regions
Areas of
disorder
Risk frequency Number of sample = 39, Degree of freedom = 38,
significance level = .05.
Intermediate (%) High (%) Very high (%) t-value Critical t-
value p-value
Shoulder 25.64 28.21 38.46 6.1664
2.02
0.00001 p<.05
Elbow 7.69 5.13 7.69 4.0508 0.000121 P<.05
Wrist 12.82 23.08 35.90 3.3172 0.001005 p<.05
Upper back 15.38 17.95 7.69 1.595 0.059498 p>.05
Lower back 20.51 12.82 10.26 1.3889 0.086475 p>.05
One sample t-test was used to determine the
association among the shoulder, elbow, wrist, upper back
and lower back pain and discomfort. Table-5 represents
the prevalence rate of reported symptoms in different body
regions in three levels of exposure to risks among the 39
workers studied. One sample t-test revealed that for the
disorders of shoulder, elbow and wrist, the calculated t-
values are higher than the critical t-value and consequently
the corresponding p-values are less than 0.05, which is
significant. However for the disorders of upper back and
lower back, the calculated t-values are lower than the
critical-t value, and consequently the corresponding p-
values are greater than 0.05 which is insignificant. These
results indicate that there is a significant association
between RULA risk frequency and prevalence rate of
reported musculoskeletal disorders (MSDs) in shoulder,
elbow and wrist (P<0.05). The statistical significance of
this score reflects the high loading of this part while
performing the assigned task. The various disorders
occurred in a month corresponding to the % of workers
exposure to high risk frequency is now plotted in Figure-4.
The Figure-4 shows the various MSDs reported
in a month in association with the percentage of workers
of high level of risk frequency. It reveals that maximum
number of workers (28.21%) has experienced shoulder
pain and minimum number of workers (5.13%) has had
elbow related problems.
Figure-4. Percentage of workers of high risk frequency Vs areas of disorder.
Analysis of MSDs of very high risk frequency
The frequency of various MSDs occurred daily
and weekly corresponding to the percentage of workers
exposure to very high risk frequency is now plotted in
Figure-5. The bar chart illustrates the weekly and daily
frequency of MSDs occurred in various body parts
corresponding to percentage of workers of very high risk
frequency.
VOL. 10, NO. 6, APRIL 2015 ISSN 1819-6608
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Figure-5. Percentage of workers of very high risk frequency Vs areas of disorder.
Like the quarterly and monthly occurred
disorders in different body regions corresponding to
percentage of workers of intermediate and high risk
frequency, shoulder pain is very common for workers
exposure to very high risks and it is the highest number of
workers (38.46%) and importantly the same number of
workers have experienced elbow and back pain (7.69%)
and this is the least Figure.
IMPACT OF WORK POSTURE ON LABOR
PRODUCTIVITY
Labor productivity measures the amount of goods
and services produced by one hour of labor. More
specifically, labor productivity measures the amount of
real GDP produced by an hour of labor. Labor
productivity is the rate of output per labor per unit of time
compared with an established standard or expected rate of
output.
There are many standard formulas for measuring
the labor productivity. Labor productivity can be measured
as a ratio of the total output (goods or services) in dollars
to the number of man-hours to produce the output [7].
Labor productivity can also be measured as the ratio of
total output to the number of workers used to produce the
output. In the analysis of labor productivity, the formula
used for measuring the labor productivity is given below.
Labor Productivity = Total Output /Total Man-Hours.
Calculation of labor productivity
The calculation is based on the total number of
workers working on the total machines which are fully
utilized in the production section of the selected ceramic
factory. In this calculation other factors like the skill of the
workers and the machines condition have been considered
as invariant.
In the existing condition,
Each machine includes three workers (One
operator + two helpers)
Total number of running machines = 12
Total number of operators = 12
Total number of helpers = 24
As for instance, on Machine - 1,
Daily production of ceramic tiles = 1600 (pieces)
Time required per worker = 8 hours
Number of worker = 3.
So, the Labor productivity on machine -1
= 1600/ (3×8) = 66.66 67.
Similarly the productivity calculations of all other
workers on the respective machines have been performed
and tabulated in Table-6.
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Table 6. Hourly labor productivity calculation.
Worker
RULA
grand
score Machine Average
RULA grand
score
Number of
workers
Hourly
production
(Pieces)
Daily
production
(Pieces)
Labor
productivity
per hour in
terms of
production
1 5
Machine 1 6.00 3 200 1600 67
2 7
3 6
4 4
Machine 2 5.00 3 225 1800 75
5 7
6 4
7 4
Machine 3 5.00 3 210 1680 70
8 6
9 5
10 5
Machine 4 5.67 3 190 1520 63
11 6
12 6
13 5
Machine 5 6.00 3 180 1440 60
14 7
15 6
16 5
Machine 6 5.67 3 200 1600 67
17 7
18 5
19 7
Machine 7 6.00 3 170 1360 57
20 7
21 4
22 7
Machine 8 6.00 3 190 1520 63
23 7
24 4
25 7
Machine 9 6.33 3 160 1280 53
26 7
27 5
28 6
Machine 10 5.33 3 225 1800 75
29 6
30 4
31 4
Machine 11 6.00 3 200 1600 67
32 7
33 7
34 4
Machine 12 5.00 3 210 1680 70
35 7
36 4
The relation between RULA grand score and the
corresponding labor productivity has been shown in Table-
6. The results represent the RULA grand score of 36
workers in total working on 12 different machines.
Average RULA Grand score of each machine’s worker is
also calculated here. Hourly production as well production
per day on each machine and the hourly labor productivity
in terms of production are also listed in the table.
On the basis of labor productivity calculations,
the relation between RULA grand score and the labor
productivity per hour in terms of production is drawn in
the Figure-6.
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Figure-6. RULA grand score Vs productivity per hour in terms of production.
It has already been identified that higher RULA
grand score indicates the bad working posture. On the
contrary relatively lower score represents the good
working posture. At the time of working, body posture has
a significant effect on productivity. It is evident from the
above relationship that the good work postures
corresponding to lower RULA grand score ultimately
results in higher productivity and inversely bad work
postures corresponding to higher RULA grand score
decrease the labor productivity. Moreover, it has been
observed that for machine 1, the average RULA grand
score is 6 and the corresponding labor productivity is 67
whereas for machine 2, the average RULA grand score is
5 and the corresponding labor productivity is 75. It can be
concluded here that the labor productivity has been
increased as the RULA grand score gets decreased.
However, the labor productivity has been decreased from
75 to 70 for machine 3 though the average RULA grand
score is same for machine 2 and 3. This is because the
individual RULA scores for workers working on machine
2 are (4, 7, and 4) respectively and on machine 3 the
individual scores are (4, 6, and 5) respectively. On
machine 2, though a worker has high RULA grand score
of 7, another two workers have a unique lower score of 4.
However on machine 3 only one worker has low score of 4
but another two workers have relatively high score of 5,
and 6. The same conclusion can be drawn for machines 2
to 5; the labor productivity has got decreased with the
increase of average RULA grand score.
Relation between average RULA grand score and
average labor productivity
The following table represents the average labor
productivity data corresponding to average RULA grand
score for workers working on 12 different machines.
Table-7. Avg. RULA grand score Vs labor productivity.
Average RULA
grand score Average
labor productivity
5 71
5.33 75
5.67 65
6 62.2
6.33 53
Table-7 provides information on average RULA
grand score and the related labor productivity of workers
as well. It shows that labor productivity value of 75 is the
highest for the average RULA grand score of 5.33 whereas
the lowest labor productivity Figure of 53 has been found
for the highest average RULA grand score of 6.33 for
workers working on machine 9.
This same relationship has been plotted in the
Figure-7 accordingly. The correlation between average
RULA grand score and average labor productivity is
shown in the graph. Therefore, it can be concluded that
there exists an inverse relationship between these two and
there is a decreasing trend of labor productivity for the
higher RULA grand scores except the initial minimum
value of average RULA grand score.
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Figure-7. Relation between average labor productivity and
average RULA grand score.
CONCLUSIONS
In this case study research work the various work
postures of workers working particularly in the production
section of a selected ceramic factory have been evaluated
in the view point of RULA. After the evaluation of RULA
grand scores through RULA worksheet for various work
postures of a certain number of workers, it has been
observed that no workers have acceptable work posture
and most of the workers are working in high posture
related risk. The obtained scores indicate the condition of
work posture of the workers studied and low grand scores
(1 or 2) indicate an acceptable working posture. Through
the analysis of RULA grand score, it has been identified
that with the grand score of 7, 43.59% of the workers need
immediate investigation and changes to sustain the desired
level of performance. With the increase of RULA grand
score, the validity of work posture has got decreased
resulting in the increase of associated risks for the bad
posture.
The consequence of bad work posture results in
musculoskeletal disorders (MSDs) which have also been
analyzed in this research work. The RULA grand score
has been compared to different levels of risk frequency.
This comparison provides us with a guide line for further
action and in most cases this guide line is used as an aid in
efficient and effective control of any risks identified.
Moreover, the weekly, daily and monthly frequency of
MSDs occurred in various body parts corresponding to
percentage of workers of intermediate, high and very high
risk frequency have been shown with the help of bar
charts.
Lastly, the relation between RULA grand score
and the corresponding labor productivity has been
established in the analysis. The relationship between work
posture and productivity of workers working on various
machines shows that the higher RULA grand scores have
an adverse effect on labor productivity. For the bad
condition of the posture workers do not apply their full
efforts to their work which results in lower productivity.
The correlation between average RULA grand score and
average labor productivity establishes the fact that there
exists an inverse relationship between these two and there
is a decreasing trend of labor productivity for the higher
RULA grand scores.
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Ph.D Thesis, Department of Building, National
University of Singapore.
... Labor productivity is a key measure of successful business efficiency, particularly for firms in which the production process is labor-intensive (Rahman & Ahmed, 2015). ...
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Thesis
Work study is a tool of the investigation of a process by means of regular system the work is done in an industry, in order to achieve the best possible use of human, machine and materials available in the workstation. Ergonomics is fitting workplace conditions and work demands to capability of workers. The integration of ergonomics and work study requires new methodological framework that evolves from single approaches. Which clearly applies the principles of both and simultaneously guaranteeing better productivity and working condition. The objective of this study is to develop standard working procedures with reduced non-value adding activities and ergonomically designed working condition. Both primary and secondary data was used. To collect primary data direct observation and questionnaire was used. To analyze qualitative and quantitative analysis was employed and to compare the existing system and the proposed system arena simulation was conducted. The findings of this thesis indicate that the layout of the J-bolt production line is exposed to wastage of motion of workers and material that consume production time and there was no mechanical material handing on the line as well as there was awkward postures like forward bending and leaning, lateral bending and twisting, sitting above and below normal height and excessive forward reaching. Workers on the line facing different degree of pain in their body parts more than 53% of them face higher degree of pain in the lower back and half back. Also on average 9 injures are recorded per year. From the work measurement conducted and redesign the workstations the unit production time is reduced by 42.33% and the production volume is increased by 7 pieces p
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... The poor posture and movement can lead to local mechanical stress on the muscles, tendons, ligaments and joints resulting in discomfort in the neck, back, shoulder, wrist and other parts of the musculoskeletal system. This is because when maintaining a posture, the joints must be kept in a neutral position with the limbs, as far as possible, close to the body, thus enabling the muscles to deliver the greatest force (David, 2005;Chowdury et al., 2015) In previous studies, Trevelyan and Haslam (2001) has generally identified that both upper limb and back most affected. The studies have been conducted in handmade brick factory, and there has been a general indication that working with bricks may dispose towards upper limb disorders. ...
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This study has been carried out to evaluate the work-related musculoskeletal disorder (MSD) associated with working posture among workers at cable support system factory. From observation, workers have experienced high risk MSD which caused by awkward posture, excessive force and repetition due to limited working area, standing for prolong period and lifting heavy equipment. 36 workers have been evaluated by Nordic Musculoskeletal Disorder questionnaire and the data analysed by using correlation analysis. The study shows that among 36 workers, 30 workers (83%) have been reported to suffer from MSD risk. From the correlation analysis, ages of workers and years of workers’ experience were the most significant factors that contribute to MSD risk and the most affected body parts are knees, ankles and lower back. This study shows that the workers at cable support system manufacturing performed their task in bad working postures; hence, change required immediately to improve workers wellbeing.
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This study focuses on the problem of ergonomic evaluation for work tasks with a full-body postural approach. Although there has been much research in this area, including experimental investigations, there is still a need for objective and flexible approaches to the development of postural analysis. A new fuzzy-based full-body postural assessment tool is developed within a fuzzy inference engine (IE). Starting from an ergonomic map, the study develops a Fuzzy knowledge based system containing the main evaluation rules of the best known full-body evaluation checklists. The approach aims to give an integrated value of the ergonomic assessment for all of the postures investigated, indicating also the incidence of each posture. The methodology is applied to an industrial case of a set-up activity. A comparison is carried out with a standard integrated postural evaluation methods.
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Ergonomics is an important aspect in order to improve workers performance at work, develop an autonomous rhythm at work which will synchronize physical, physiological and psychological aspects that is responsible for human behavior and efficiency at work and stands as a key factor deciding workers effectiveness. This paper focuses the attention on the ergonomics consideration required to be governed in the small scale industries, a specific case of tractor trolley manufacturing unit is considered, which is deviating from all these aspects. Particularly, an important & bulky component 'turn table' is considered for analyzing the ergonomic manufacturing methods. The gap between ergonomic considerations and actual practices at the workplace gives the perspective to design the workstation. The data of musculoskeletal disorder of worker working at workplace of tractor trolley manufacturing unit is collected, analyzed and validated by using RULA.
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Work-related musculoskeletal disorders (WMSDs) are a common health problem throughout the world and a major cause of disability in the workplace. Awkward working posture is a main risk factor for developing WMSDs. Assessment of exposure level to WMSDs risks can be an appropriate base for planning and implementing interventional ergonomics program in the workplace. This study was conducted among workers of an Iranian communication company with the objectives of a) determination of WMSDs prevalence and b) assessment of exposure level to WMSDs risks. In this cross-sectional study, 85 randomly selected workers from assembly line and closed circuit TV (CCTV) participated. Nordic musculoskeletal questionnaire (NMQ) was used to study prevalence of WMSDs and rapid upper limb assessment (RULA) technique was applied to assess physical exposure to the risks. The results of NMQ revealed that WMSDs occurred at an high rate. The highest rates of WMSDs prevalence were reported in shoulders (73%), knees (67.1%) and back (66.7%). RULA showed that the Grand Score of 88.1% of cases were high and very high (action levels 3 and 4). Significant association was found between risk level and musculoskeletal symptoms in lower back (P < 0.05). Given the association between RULA score and the prevalence of the problems, reducing RULA score by designing ergonomic workstation may reduce the prevalence of WMSDs among the workers.
Article
Gold ornament making industries are one of the widespread small-scale industries of India. These industries belong to the unorganized sector of the state. A large number of goldsmiths are working there for prolonged period in cross leg posture at semi-confined workstation. The aim of this study is to identify Occupational Disorder of the Goldsmiths in India. In the spresent study, 120 male goldsmiths were randomly selected from the Davangere district of Karnataka. A detailed questionnaire study on discomfort feeling was done by the modified Nordic questionnaire, which considering the information about work nature, job stress and discomfort feeling. The existing workstations were assessed by the measurement of work areas. Analysis of body posture by rapid upper limb assessment was done to evaluate the work stress during their job. From the analysis, it was revealed that MSDs were the major problem of the goldsmiths. The activities of the goldsmiths were also highly repetitive. Moreover, the questionnaire study revealed that most of the workers were affected by occupational disorder like pain at neck (80%), shoulder (20%), wrist (45%), and low back (75%) and also eye problem like irritation (30%) and burning sensation (70%). They also perform their job in hazardous postures. It was recorded that the workstations were poorly illuminated (19 Lux) in respect to precision work. Accidents like cut and burn occurred frequently due to the unsafe condition of the workstation. From the observation and analysis of the result it was concluded that health of the goldsmiths were highly affected improper body posture and workload. Twisting, bending, and over-reaching are the resultant of poorly designed workstation. These actions force them into a non-neutral position that increases the overall discomfort and pain at the lower back, neck, and shoulders. Moreover, lack of proper illumination at work site also exerts an additional adverse effect on the health of the goldsmiths.
A Proposed RULA for Computer Users-Proceedings of the Ergonomics Summer Workshop. UC Berkeley Center for Occupational and Environmental Health Continuing Education Program
  • R Lueder
Lueder R. 1996. A Proposed RULA for Computer Users-Proceedings of the Ergonomics Summer Workshop. UC Berkeley Center for Occupational and Environmental Health Continuing Education Program, San Francisco., USA.
Assessment of Working Posture in Manufacturing Industry Using RULA Method. Faculty of Manufacturing Engineering
  • Ramli Sarini Bt
Sarini bt Ramli. 2007. Assessment of Working Posture in Manufacturing Industry Using RULA Method. Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, Malaysia.
Forecasting Construction Industry-level Total Factor Productivity Growth using Neural Network Modeling
  • Mao Zhi
  • Bee Goh
  • Wang Hua
  • Shouqing
Mao Zhi, Goh Bee Hua and Wang Shouqing. 2003. Forecasting Construction Industry-level Total Factor Productivity Growth using Neural Network Modeling. Ph.D Thesis, Department of Building, National University of Singapore.