Analysis of Safety Compliance and Accident Impacts on Lost time Performance of Small Scale Automotive Maintenance Workshops in Calabar - Juniper Publishers
Juniper Publishers - Open Access Journal of Engineering Technology
Abstract
The objective of the present research is twofold;
first to assess the level of safety compliance practices among artisans
and secondly, to measure the impacts of unplanned lost time emanating
from accident on time performance of small-scale auto maintenance firms.
Ninety different auto-maintenance jobs executed by Automobile, Heavy
duty, Generator and Panel beater auto firms between, January to
December, 2016 were sampled using direct observation. Furthermore,
primary data collected were analyzed using MS Excel 2013 and Minitab 17
software. Results revealed the mean performance rating of workshops on
the availability and usage of personal protective equipment as 143.9 and
154.7. While 224.2 and 302.7 constitutes respective poor usage rate and
non-availability of (PPE) in the respective workshops. Results further
revealed 58.2% as average productive lost time rate resulting from
accident occurrence. Conversely, regression analysis revealed that a
unit increase of 659.2, 63.5 and 82.8 in accident, severity and lost
time index, caused a decreased of -150.8 in overall productivity lost
factor. With a coefficient of determination (R2) of 72.01% at p-value
less than 0.005. Hence, a positive and significant relationship between
accident and auto mechanics time performance exist. Therefore,
sensitization of stakeholders in this sector on the usage of PPE and the
need to make safety their priority as well as regular inspection for
safety compliance by regulatory bodies are recommended to build
customers trust and improve productivity in this sector.
Keywords: Automotive
maintenance; Safety measures; Small scale; Accident index; Severity
index; Lost time index; Overall productivity lost factorNomenclature
Aindex Accident index
Atime Actual time
No Number of observation (90)
Ptime Planned time
Sindex Severity index
Tindex Time index
ai Constant expressing weighting given to each factor, at i=1,…4
β0 Constant estimated by regression model
β1,β2,β3 Coefficients of explanatory variable
b Frequency of the occurrence
OPLF Overall Productivity Lost factor
PLTR Productive lost time rate
N Total number of occurrence
i Recordable accident within the period
w Number of workers performing maintenance
Introduction
Dhillon et al. [1], described maintenance as appropriate
actions made for retaining an item/part/equipment, or restoring
it to a given condition. Concisely, maintenance is undertaken
to restore broken equipment’s, preserve equipment conditions
and prevent their failure, which ultimately reduces production
loss and downtime as well as the associated safety hazards. In
Nigeria, large proportion of auto maintenance firms are classified
as “small scale”. This classification owe to the fact that the sector
is characterized by low capital output ratio, that is the ratio
of capital level relative to output is low, [2]. SMS automotive
maintenance firms are vital to human resources in the automobile
industry in virtually every nation’s economy due to its significant
contribution in terms of job creation. Kayemuddin & Kayumm [3],
described the automotive maintenance workshop as a category
of small scale industry that contributes about 8.8% to the GDP
of a nation’s economy. In Nigeria, the industry records about
3billion as turnover annually to the local economy according to
the regulatory body of mechanics in Nigeria, National Automobile
Technicians Association (NATA) in its report “Nigeria economy and
the mechanic” of October 12, 2012. Auto mechanics are involved
in the repairs and maintenance of automotive facilities such as
vehicles and generating plants to enhanced optimum performance
when they breakdown [4]. Other task includes replacement of
worn mechanical parts that can cease transmission or prove
unsafe for effective operation, [5]. SMS auto maintenance firms
are characterized by preventive and corrective maintenance.
Preventive maintenance is defined as a series of pre-planned tasks
performed on auto facility either according to manufacturer’s
schedule to counteract the known causes of potential failures of the
intended functions of an asset [6]. Preventive maintenance (PM)
plays a vital role to mitigate if possible avoids potential stoppages
and disruptions of equipment or machinery from occurring in
daily operations. While corrective or breakdown maintenance, is
performed when a system or machine fails. It includes repair and
replacement of failed parts to create an optimal performance again.
Corrective maintenance activities are, in contrast to preventive
maintenance, not schedulable [7]. This makes them harder to
plan and more costly to perform. However, hardly are these
activities or maintenance by auto mechanics completed without
hazards, thereby stimulates negative effects such as time delay,
increased costs, and productivity loss. The imbalance relative to
safety compliance among auto mechanics during maintenance has
significantly impacted performance time and is a major concern
[8,9]. Industrial safety, health and environmental management
opined that in order to meet the different needs which are seen in
the present day industrial environment which demands increased
production, high efficiency, and cost control etc. The subject of
safety, health and environment must come into play, otherwise any
neglect in these aspect can prove very costly. Neglect of safety at
any stage can result into disasters leading to loss of human life and
production. Thus, it is imperative to evaluate the level of accident/
injuries and safety compliance in small scale auto maintenance
firms and its impact on time performance.
An accident is defined as any unplanned event that
result in
the combination of the following consequences; physical injury,
lost time case, loss of property and number of fatalities [10].
While safety measures are facilities and strategies that are put in
a workplace place to prevent or reduce accident during various
stages of project [11]. Accordingly, Oisamoje, and Enaruna
[12] defined health and safety management as an area that is
concerned with ensuring the safety, health and welfare of people
engaged in work or employment. Consequently, there are several
risks which expose auto mechanics to workplace accidents/
injuries in the automotive maintenance workshops. Some of these
risks include exposure to chemicals, strenuous work postures, and
the use of improperly specified tools and lack of safety compliance
[13-15], thus, affecting their performance. However, to efficiently
regulate an issue, one should satisfactorily define the problem.
Bozena [16], opined that the level of accident in a particular sector
like the construction industry is estimated by the labour force in
the analyzed sector, the number of victims of accidents at work
and the number of days lost resulting from accident at work.
The Statistical Office of the European Communities (Eurostat),
established specific indicators that enables any company to
report their number of accident and accident index (defined as
the number of accidents per 100,000 working persons). Also, the
Office of Environmental Health and Safety, established specific
models that enable any firm to report their recordable incident
rates, lost time rates, and severity rates, so that they can be
compared with other industry or group. According to OEHS, the
standard base rate for the calculations is based on a rate of 200,000
labour hours. This number (200,000) equates to 100 employees,
who work 40 hours per week, and who work 50 weeks per year.
Using this standardized base rate, any company can calculate their
rate(s) and get a percentage per 100 employees. However, one
of the limitations about this approach is that none of the above
indicators provides any evidence about the achieved values of
productivity indices. It is therefore proposed in the current study
to take productivity indices, e.g. delivery efficiency into account in
accident level assessments of automotive maintenance firms. This
is because unplanned idle time resulting from industrial accidents
reduces real time productivity and increases delay. Downtime or
lost time refers to the variation between the estimated finish and
the actual finish time of tasks either resulting from ill health or
injuries/accident. Lost time is an imperative issue in industries
because of its relation to productivity and business profitability
[17]. Evaluating the causes and impacts of accident/injuries on
productivity performance in automotive maintenance workshops,
has become a necessity. Because productivity rises as the number
of incident related cases reduces, and the use of properly designed
tools increases [18]. Hence, small scale automotive maintenance
firms needs to be aware that lost time resulting from the use of
improperly designed tools and lack of safety compliance as well as
accident/injuries cases, whether planned or unplanned, is very
costly.
Methodology
Primary data used in the current study were basically
obtained through survey design approach with direct observation
of two automotive maintenance workshops each sampled across
forty-five different small scale auto firms, amounting to ninety
observations. This comprises of heavy duty, automobile, generator
and panel body auto firms caught across the seven layouts (Eight-
Mile, Diamond Hill, Anantigha, Essien Town, Ikot Enobong, Big-
Qua Town and Etta-Agbor) in Calabar metropolis where SMS auto
firms are found in their large numbers. Each auto firms had a work
force of at least four to six artisans performing different repairs
at a duration of 8hours daily (i.e. the peak hours of industrial
activities), for 6days per week, excluding Sundays, for a period
of twelve months between January to December 2016. The data
collected was tabulated and classified according to maintenance
characteristic (i.e. initial and actual final time, actual performance,
number of incident/injuries that resulted to lost days overrun cost
and time, and the severity rate of incident). This was done to ensure
that all variables considered were clearly defined. Furthermore,
Microsoft Excel 2013 and Minitab 17 statistical tools were used
for analyses of the data. Additionally, the analysis on proper usage
and safe handling of tools were ranked by the measurement of the
relative index ranging from (1= Excellent, 2= Very Good, 3= Poor,
4= none). Where 1 to 3 implies the level of usage or availability
of tools impact, to ascertain the mean rating of each response on
safety compliance in SMS auto maintenance firms.
Eqns. (2), (3), (4) and (5) defines the magnitude of lost time
index, time index, time performance achieved and productive lost
time rate of each project at completion [19-23].
Also, Eqn. (6) defines the Overall Productivity lost factor
(OPLF) of each auto firm’s project executed.
OPLF helps to break down the reasons for productivity
losses into three main factors, which include; accident index,
lost time index and severity. Ideally, one fundamental area that
every organization can improve upon is productive efficiency/
conformity and one of the best measures is OPLF. A possible
explanation to this argument is that organizational efficiency has
relevance for business profitability.
Accident index and severity for each sector was determined as
expressed in Eqs. (7) and (8).
Accident index measures the productive time losses resulting
from accident from a predetermined sample. And is calculated
by dividing the number of incident/injuries in each sector by the
total number of observation [12].
The severity index quantifies the average number of working
days lost due to a worker’s involvement in minor and serious
accidents [16]. Furthermore, multiple linear regression analysis
in MS Excel and Minitab 7.1 statistical tools were used to establish
the relation between overall productivity lost factor (OPLF) from
accident index, lost time and severity index, and graphs plotted
accordingly. The element of multiple regressions is expressed in
equation (9).
Results and Discussion
Figure 1 present the result of common injuries/accident
identified to be associated with the four selected auto firms
(automobile, heavy duty, generator and panel beater workshop)
which vary from superficial wounds, dislocation, burns, bruises,
cuts, and backache, as evaluated using eqn (6) (Figure 1).
It is obvious from Figure 1, that superficial wounds, burns
injuries, and was prevailing among panel body work auto
mechanics with an average of 28.1% and 18.7%. Similarly,
dislocation injuries/accident was common among heavy duty
firms with an average of 44.4% been the highest. This group of auto
technicians have to constantly lift heavy items which can strain
their back, adopt awkward postures and may spend long hours
bent over or lying on their back. Furthermore, cuts and bruises
incident cases was found to be common with generator firms. A
possible explanation to this finding is that most of this firms lack
the basics personal protective equipment, and as such they fail
to use them. For instance, auto mechanics in panel beater auto
firms reported being aware of the hazards associated with their
jobs when interviewed, but stated that awareness did not seem to
help reduce the health problems they suffered. Additionally, the
analysis on proper usage and safe handling of tools, as depicted
in Figure 2 shows that about 55.1% of automotive maintenance
firms, lack the ability to handle hand tools before and after each
maintenance.
While about 19.2% averagely practiced safe handling of
hand tools. Also an average of about 16.6% of these workshops
do not even consider the handling of tools as a safety measure to
be observed. Also, the proper usage of power tools was marginal
with an average of 32.0%. While 28.2% didn’t make any attempt
within the period under consideration. The proper usage of
compressed air equipment was found to be 2.5% on the average,
while 12.8% observed the safety rules of wearing safety glasses or
face shield during operation to avoid metal particles into the eye.
Also about 29.4% used this equipment poorly by not observing
the safety rules, with unavailability of 55.1%. Also, from the result
as depicted the proper usage of hydraulic/hoist equipment by
auto mechanics was at an average 61.5% and 34.6 marginally
applied the safety rules while using it, and 3.8% used it but never
considered safety precaution at all level. Furthermore, Figure 2
reveals that only 18.5% auto mechanics appropriately used chain
hoist and crane when lifting an automobile engine from the sitting.
While 14.2% marginally used it well and unavailability of 67.1%
on the average. This is basically found among un standardized
workshops, as they lift engine manually using their hands.
It was obvious from that safety practice towards equipment
maintenance was lacking in most of the repair firms as majority
of these mechanics fail to ensure effective cleaning of equipment/
tools before and after use. The unavailability of fire extinguisher
among the auto repair firms was on the high side with an average
value of 58.9%, while about 20.5% had it in their workshop, but
weren’t in good condition. Except for few workshop which had it
in good operational condition with an average of 6.4% and 14.1%
respectively. According to survey the unavailability of goggles and
face shield among auto technicians, especially panel bitters was on
the high side with an average value of 70.59%, while about 22.06%
had it in their workshop, but was in poor condition. From analysis
the unavailability of hand gloves and safety boot among the auto
firms was high with an average of 79.69% (approximately 80%).This implies that most local mechanics violate the rule of wearing
safety personal protective (e.g. gloves and safety boot) equipment
when working. This is because most of the local mechanics were of
the opinion that protective equipment must be provided by their
masters or owners of the workshops.
Also, descriptive analyses of the ninety maintenance projects
of the four sectors (heavy duty, automobile, generator, and panel
beater auto firms) evaluated reveals the following findings in
studying time performance and lost work days, as presented in
Figure 3-6 respectively.
It is clearly seen from the Figures 3-6 the need to maintain
close link between time performance and lost time resulting from
injuries/accident related cases. Obviously, as time performance
(efficiency) reduces, lost time increases. This implies that the
relationship between time performance and productivity is
inversely proportional i.e. the higher the time efficiency rate,
the lower the productive time losses and equally, the lower the
time efficiency rates, the higher losses in productivity. Also, Table
1, further present the summary of comparative analyses of time
performance and lost time rate inherent in each auto firms.
However, to determine the overall productivity lost factor
(OPLF) of each auto firms, the index of accident, lost time index
and severity index values were computed as depicted in Table 2.
Within these auto maintenance sectors, the accident index range
between 0.133, 0.111, 0.155, and 0.277 for automobile, generator,
heavy duty and panel beater auto firm. This implies that panel
beater autos firms recorded the highest number of injuries with
an accident index of 0.277. Thus, recording lost time index of 62
and 2.48 as severity index and 42.69% as overall productivity lost
factor. This is repeated for automobile, generator, and heavy duty
auto firms respectively as presented in Table 2.
However, an explanation to these findings is that artisans in
panel beater auto maintenance firms constantly get in contact
with hot surfaces, exhaust pipes, radiator and cooling system
pipes, soldering and welding operations due to the nature of
maintenance practices.
Furthermore, Table 3 shows the result of the multiple liner
regression model formulated to relate overall productivity
lost factor with accident index, lost time and severity index as
presented in eqn. (9). Table 3 indicates that the accident index
has a beta coefficient ( β0) of 659.2 at a probability value of 0.000
< 0.05. Hence, it is significant. This indicates that OPLF decrease
by -150.8 when accident index increases by 659.2 when all other
independent variable is held constant. For every unit rise in
accident index, there was a unit decrease in overall productivity
lost factor.
R2 = 72.01%, R2 (adj) = 71.03%, F −Value = 73.75, P −Value = 0.000
It can then be inferred that accident index has an impacts on
overall productivity lost factor. The data further revealed that
severity index has a coefficient of 63.5 at a probability value of
0.036 less than 0.05. Hence, it is significant, this indicates that,
for each unit increase in severity index, there is a corresponding
decrease of -150.8 in overall productivity lost factor when all
other independent variables are held constant. Similarly, the data
further reveals that lost time has a coefficient of 82.8 at p-value
0.000<0.05. This equally indicates that an increase of 82.8 in lost
time caused a reduction of -150.8 in overall productivity lost factor
when all other independent variables are held constant. Coefficient
of determination (R2)=72.01%. This indicates that all variations
in the dependent variables are as a result of the independent
variables. That is, 100% variation in overall productivity factor is
as a result of changes in accident index, severity index and lost
time.
Conclusion
The impacts of unplanned lost time emanating from
accident/injuries on time performance of small-scale automotive
maintenance firms has been evaluated using descriptive analysis
and multiple linear regression technique. Descriptive analysis
of ninety auto maintenance jobs executed across Automobile,
Heavy duty, generator and panel beater auto firms between
January to December, 2016 revealed the mean performance
rating of workshops on the availability and usage of appropriate
protective equipment were determined as 143.9 and 154.7
respectively while 224.2 and 302.7 constitutes respective poor
usage rate and non-availability of appropriate safety equipment
in the workshops. Results further revealed an average productive
lost time of 58.2% resulting from accident/injuries. Conversely,
regression model formulated revealed that a unit increase of
659.2, 63.5 and 82.8 in accident, severity and lost time index,
caused a decreased of -150.8 in overall productivity lost factor.
With a coefficient of determination (R2) of 72.01% at probability
value less than 0.005. Hence, it is concluded that compliance
to appropriate safety practice in this sector is very poor due to
nonchalant attitude of the operators of these firms toward safety
practices as well as inadequate diagnoses tools and supervision
by regulatory agencies. This study could also be extended to other
local artisans in the small scale industries such as auto electric
technicians etc. in Nigeria to possibly identify the risks associated
with non-safety compliance and the impacts of occupational
accident on productivity performance. Therefore, sensitization of
stakeholders in this sector on the need to make safety their priority
and regular inspection of these firms for safety compliance by
regulatory bodies are recommended to build customers trust and
improve productivity in this sector.
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