Characteristics of forklift accidents in korean industrial sites

Abstract

BACKGROUND:

Although using forklifts in industrial sites contributes to productivity, many workers have been injured or killed owing to industrial accidents caused by forklifts.

OBJECTIVE:

This study analyzed the characteristics of forklift accidents by employment type and work process, thereby identifying the factors contributing to industrial accidents and providing recommendations to prevent accidents.

METHODS:

Data on 1,061 industrial forklift accidents occurring in 2018 collected from the national injury insurance compensation database were analyzed. In addition to analyzing the accident characteristics, this study performed a risk assessment per forklift work process.

RESULTS:

Many accidents were associated with older workers, those employed for < 6 months, and workplaces with ≤49 workers. The risk was the highest for accidents involving caught-in objects in the loading/unloading step and collision accidents in the forward- and backward-driving steps.

CONCLUSIONS:

Measures are needed to prevent industrial forklift accidents. First, forklift and worker movement routes must be strictly separated or controlled by a work supervisor. It is necessary to secure a time margin for workers to avoid collapsing cargo by using an appropriate tool/jig during loading/unloading. Second, guidance, inspection, and support are needed to promote employers’ safety and health awareness in workplaces with < 50 workers. Lastly, intensive education and training concerning health and safety is required for workers with less than six months of experience.

Keywords

Risk assessment industrial accident employment type work process

1 Introduction

Many workers are injured; develop ailments such as occupational pulmonary disease, work-related mu-sculoskeletal disorders, or malignant mesothelioma; or are killed by industrial accidents on industrial sites [1 –6]. Industrial accidents not only cause distress to workers and their families, but also negatively affect the national economy. In South Korea, the economic loss from industrial accidents in 2013 was estimated to be USD 27,224 million, corresponding to 2.1%of South Korea’s gross domestic product (GDP) [7]. The International Labour Organization reported that the losses from injuries and diseases due to industrial accidents amount to approximately 4%of the global GDP. The European Union (EU) Information Agency for Occupational Safety and Health reported that the losses of EU member countries due to industrial accidents ranged from 2.6%to 3.8%of each respective EU countries’ GDP [8, 9]. Germany estimated the losses from industrial accidents in 2016 as 2.4%of their GDP, and the U.S. estimates the losses from industrial accidents in 2007 as 1.8%of their GDP [10 –12]. Singapore estimated the losses from industrial accidents in 2011 as 3.2%of their GDP [13]. Because industrial accidents inhibit economic growth, many countries are conducting preventive activities to reduce industrial accidents.

In South Korea, fatal accidents caused by forklifts are the most commonly reported among all single machines [14]. Many forklifts are used in industrial sites for their ability to easily move heavy objects. In fact, forklifts have become indispensable for material handling as well as for transportation in many tasks [15]. Although forklifts bring about many benefits for productivity improvement, many workers have been injured or killed owing to industrial accidents caused by forklifts, particularly in the cases of forklifts used near pedestrians [16]. Forklifts frequently move forward and backward owing to the characteristics of work sites such as narrow spaces, entrance ramps of warehouses, and docks for cargo unloading. In addition, blind spots in the view of forklift operators are generated by the forklift operator enclosure, forklift mast assembly, and the forklift load [17]. Collision between workers and forklifts due to blind spots in work sites can lead to serious injuries or death [18 –20].

Methods to protect workers and operators from forklift accidents have been researched. Specifically, validation tests of passive safety systems for forklifts have been examined [21, 22], and test methods for safety belts and door-bar systems have been proposed [23]. Furthermore, airbags for forklift operators have been developed [24].

Although safety improvement and accident risks associated with forklifts have been researched, additional analysis is required on the characteristics of the injured workers and the accidents per a detailed forklift work process. Analysis of these issues, which is lacking, can help to prioritize accident prevention measures.

Therefore, the objective of this study was to identify factors contributing to industrial accidents and provide recommendations to prevent accidents by analyzing the characteristics of forklift accidents by employment type and work process. In addition, the forklift work process was subdivided, and the priorities of accident prevention measures are provided through risk assessment for each work process.

2 Methods

In South Korea, employers are obligated to sub-scribe to an industrial accident compensation insurance scheme to compensate injured workers from industrial accidents [25 –27]. This study extracted cases causing worker deaths or four or more days of sick leave due to forklift accidents in industrial sites from the national injury insurance compensation database and used them as the basic data for analyses. In 2018, 1,061 industrial-forklift accidents occurred, which resulted in 21 deaths (2.0%) and 1,040 injuries (98.0%).

First, characteristics of workers injured by forklift accidents were analyzed. In other words, differences in the characteristics of injured workers such as injury severity, age, employment period, and company size were analyzed by employment type. Table 1 describes the parameters used for analyses. Second, differences in the types of industrial accidents by employment type were analyzed. The types of industrial accidents were classified as falling, tripping, caught-in, collision, struck-by, and other, which was based on the classification criteria presented by the Korea Occupational Safety and Health Agency [28]. Third, after the forklift work processes were subdivided, differences in industrial accidents by work process were analyzed according to employment type. Table 2 shows the subdivision of forklift work processes. Fourth, the types of industrial accidents by forklift work process were analyzed. Finally, the risk level of each work process was determined by performing a risk assessment for each forklift work process. The frequency grading in the risk assessment is based on the number of industrial accidents and the severity grading is based on sick leave (in days). Chi-square tests were used to analyze the characteristics of forklift accidents.

Table 1
Classification criteria of parameters used in analyzing the characteristics of forklift accidents

Parameter Classification criteria

Age 19 years or younger, 20–29 years, 30–39 years, 40–49 years, 50–59 years, 60 years or older

Employment period Less than 6 months, 6 months to less than 1 year, 1 year to less than 3 years, 3 years to less than 5 years, 5 years to less than 10 years, 10 years or more

Company size 49 workers or fewer, 50–99, 100–299, 300–499, 500–999, 1,000 or more

Employment type Regular, irregular

Injury severity Death, injury

Parameter	Classification criteria
Age	19 years or younger, 20–29 years, 30–39 years, 40–49 years, 50–59 years, 60 years or older
Employment period	Less than 6 months, 6 months to less than 1 year, 1 year to less than 3 years, 3 years to less than 5 years, 5 years to less than 10 years, 10 years or more
Company size	49 workers or fewer, 50–99, 100–299, 300–499, 500–999, 1,000 or more
Employment type	Regular, irregular
Injury severity	Death, injury

Table 2

Classification of forklift work processes

Process	Task example
	Process from the forklift storage site to loading cargo to the forklift forks
Work preparation	•Forklift check and repair
	•Getting on or off the forklift to move to the workplace
	•Adjusting the gaps of forklift forks to load cargo
	•Putting pallets with no cargo on the forklift forks or removing them
	•Driving the forklift to the cargo loading site
Loading/unloading	Loading or unloading cargos to/from forklift forks
Transport(forward driving)	Transporting the cargo through forward driving
Transport(backward driving)	Transporting the cargo through backward driving
Work completion	The process of driving the forklift to the storage site, storing the forklift, and getting off from the forklift after work completion
Other	Using the forklift for other uses than the specified uses. For example, workers working on the forklift forks to replace lamps on the ceiling.

Statistical tests were performed using SPSS 18.0 (IBM, Armonk, NY, USA). The significance level was set at p < .05.

3 Results

3.1 Characteristics of industrial accidents

Table 3 outlines the distribution of injured workers by age, employment period, and company size. The age distribution of injured workers was 28.2%for 50 s, 22.6%for 40 s, and 20.7%for 60 s. The distribution of injured workers by age showed differences by employment type (χ² = 32.115, p < .001). Regular workers showed higher ratios of injured workers in their 50 s (27.7%) and 40 s (25.5%) as compared to other age groups. Irregular workers showed higher ratios of injured workers in their 50 s (29.8%) and 60 s (26.2%) as compared to other age groups.

Table 3
Distribution of injured workers by workers’ characteristics

Characteristic Classification Regular workers Irregular workers Total

n % n % n %

Injury severity Death 15 1.9 6 2.4 21 2.0

Injury 794 98.1 246 97.6 1,040 98.0

Age ≤19 years 0 0.0 1 0.4 1 0.1

20–29 years 79 9.8 43 17.0 122 11.5

30–39 years 146 18.0 33 13.1 179 16.9

40–49 years 206 25.5 34 13.5 240 22.6

50–59 years 224 27.7 75 29.8 299 28.2

≥60 years 154 19.0 66 26.2 220 20.7

Employment period < 6 months 246 30.4 214 84.9 460 43.4

6 months to < 1 year 101 12.5 17 6.7 118 11.1

1 year to < 3 years 184 22.7 9 3.6 193 18.2

3 years to < 5 years 77 9.5 1 0.4 78 7.3

5 years to < 10 years 104 12.9 3 1.2 107 10.1

≥10 years 97 12.0 8 3.2 105 9.9

Company size ≤49 workers 596 73.7 194 77.0 790 74.5

50–99 77 9.5 12 4.8 89 8.4

100–299 87 10.8 21 8.2 108 10.2

300–499 14 1.7 10 4.0 24 2.2

500–999 10 1.2 10 4.0 20 1.9

≥1,000 25 3.1 5 2.0 30 2.8

Total 809 100.0 252 100.0 1,061 100.0

Characteristic	Classification	Regular workers	Irregular workers	Total
Injury severity	Death	15	1.9	6	2.4	21	2.0
	Injury	794	98.1	246	97.6	1,040	98.0
Age	≤19 years	0	0.0	1	0.4	1	0.1
	20–29 years	79	9.8	43	17.0	122	11.5
	30–39 years	146	18.0	33	13.1	179	16.9
	40–49 years	206	25.5	34	13.5	240	22.6
	50–59 years	224	27.7	75	29.8	299	28.2
	≥60 years	154	19.0	66	26.2	220	20.7
Employment period	< 6 months	246	30.4	214	84.9	460	43.4
	6 months to < 1 year	101	12.5	17	6.7	118	11.1
	1 year to < 3 years	184	22.7	9	3.6	193	18.2
	3 years to < 5 years	77	9.5	1	0.4	78	7.3
	5 years to < 10 years	104	12.9	3	1.2	107	10.1
	≥10 years	97	12.0	8	3.2	105	9.9
Company size	≤49 workers	596	73.7	194	77.0	790	74.5
	50–99	77	9.5	12	4.8	89	8.4
	100–299	87	10.8	21	8.2	108	10.2
	300–499	14	1.7	10	4.0	24	2.2
	500–999	10	1.2	10	4.0	20	1.9
	≥1,000	25	3.1	5	2.0	30	2.8
Total		809	100.0	252	100.0	1,061	100.0

The distribution of injured workers by employment period was 43.4%for less than six months, 11.1%for six months to less than one year, and 18.2%for one year to less than three years. The distribution of injured workers by employment period showed differences by employment type (χ² = 238.978, p < 0.001). In the case of regular workers, 30.4%of injured workers had been employed for lesser than six months, and 22.7%of injured workers had been employed for one year to lesser than three years. That is, half of regular workers injured had been employed for lesser than three years. Most irregular workers were employed for less than six months (84.9%).

In the distribution by company size, 74.5%of the injured workers worked in companies with 49 or fe-wer workers. Among the rest of the injured workers, 8.4%worked in companies with 50–99 workers, 10.2%worked in companies with 100–299 workers, 2.2%worked in companies with 300–499 workers, 1.9%worked in companies with 500–999 workers, and 2.8%worked in companies with 1,000 or more workers. The distribution of injured workers by company size showed differences by employment type (χ² = 19.265, p = 0.002). The ratios of injured workers in companies with 49 or fewer workers were high among both regular (73.7%) and irregular workers (77.0%).

Table 4 shows the characteristics of forklift acc-idents by industrial accident type. Among the industrial accident types, collision accidents accounted for the largest ratio at 58.5%, followed by caught-in accidents at 21.4%, falling accidents at 9.3%, and struck-by accidents at 6.3%. The distribution by industrial accident type did not show differences by employment type (χ² = 5.869, p = 0.319).

Table 4

Distribution of injured workers by industrial accident type

Type	Regular workers		Irregular workers		Total
	n	%	n	%	n	%
Falling	74	9.1	25	9.9	99	9.3
Tripping	17	2.1	4	1.6	21	2.0
Caught-in	168	20.8	59	23.4	227	21.4
Collision	483	59.7	138	54.8	621	58.5
Struck-by	45	5.6	22	8.7	67	6.3
Other	22	2.7	4	1.6	26	2.5
Total	809	100.0	252	100.0	1,061	100.0

Table 5 shows the characteristics of industrial accidents by forklift work process. The distribution of injured workers was 30.5%in the forward-driving process and 28.7%in the backward-driving process. Thus, driving processes accounted for 59.2%of all forklift accidents, followed by loading/unloading process for 24.6%. The distribution of injured workers by work process did not show differences by employment type (χ² = 7.996, p = 0.156).

Table 5

Distribution of injured workers by forklift work process

Work process	Regular workers		Irregular workers		Total
	n	%	n	%	n	%
Work preparation	80	9.9	15	6.0	95	9.0
Loading/unloading	195	24.1	66	26.2	261	24.6
Forward driving	234	28.9	90	35.7	324	30.5
Backward driving	240	29.7	65	25.8	305	28.7
Work completion	16	2.0	5	2.0	21	2.0
Other	44	5.4	11	4.3	55	5.2
Total	809	100.0	252	100.0	1,061	100.0

Table 6 shows the distributions of injured workers by industrial accident type according to forklift work process. The distributions of injured workers between forklift work process and industrial accident type showed significant differences (χ² = 718.276, p < 0.001). The work preparation step showed high proportions of caught-in (28.4%) and collision (27.4%) accidents. The loading/unloading step sho-wed high proportions of caught-in (41.8%) and collision (26.1%) accidents. The forward-driving step showed a high proportion of collision (75.3%) accidents, as did the backward-driving step (89.2%). The work completion step showed high proportions of tripping (42.9%) and collision (28.5%) accidents.

Table 6

Distribution of injured workers by work process and industrial accident type

Work process	Falling	Tripping	Caught-in	Collision	Struck-by	Other	Total
Work preparation
n	19	4	27	26	8	11	95
%	20.0	4.2	28.4	27.4	8.4	11.6	100.0
Loading/unloading
n	36	4	109	68	41	3	261
%	13.8	1.5	41.8	26.1	15.7	1.1	100.0
Forward driving
n	5	4	52	244	13	6	324
%	1.5	1.2	16.1	75.3	4.0	1.9	100.0
Backward driving
n	5	0	22	272	4	2	305
%	1.6	0.0	7.2	89.2	1.3	0.7	100.0
Work completion
n	3	9	1	6	0	2	21
%	14.3	42.9	4.8	28.5	0.0	9.5	100.0
Other
n	31	0	16	5	1	2	55
%	56.4	0.0	29.1	9.1	1.8	3.6	100.0
Total
n	99	21	227	621	67	26	1,061
%	9.3	2.0	21.4	58.5	6.3	2.5	100.0

3.2 Risk assessment

A risk assessment was performed to estimate the accident risk by the forklift work process. Table 7 outlines the accident frequency and injury severity of forklift accidents. For the accident frequency, the ratio of each industrial accident type in each work process step was used. For example, the frequency of falling accidents in the work preparation step in Table 7 was obtained by dividing 19 falling accidents by all 1,061 accidents.

Table 7
Frequency and injury severity of accidents by work process

Work process Type Frequency Severity

% F Sick leave days Death S

Work preparation Falling 1.8 1 154.8 - 2

Tripping 0.4 1 79.5 - 1

Caught-in 2.5 1 136.0 2 3

Collision 2.5 1 243.5 - 3

Struck-by 0.8 1 219.1 - 3

Loading/unloading Falling 3.4 2 210.9 - 3

Tripping 0.4 1 170.5 - 3

Caught-in 10.3 3 160.5 3 3

Collision 6.4 3 129.4 - 2

Struck-by 3.9 2 169.1 2 3

Forward driving Falling 0.5 1 101.6 1 3

Tripping 0.4 1 78.3 - 1

Caught-in 4.9 2 145.0 4 3

Collision 23.0 3 199.7 1 3

Struck-by 1.2 1 146.7 - 2

Backward driving Falling 0.5 1 188.6 - 3

Tripping 0.0 1 - - 1

Caught-in 2.1 1 223.6 1 3

Collision 25.6 3 166.7 2 3

Struck-by 0.4 1 156.3 - 2

Work completion Falling 0.3 1 68.0 - 1

Tripping 0.8 1 94.6 - 1

Caught-in 0.1 1 - 1 3

Collision 0.6 1 120.5 - 2

Struck-by 0.0 1 - - 1

Work process	Type	Frequency	Severity
Work preparation	Falling	1.8	1	154.8	-	2
	Tripping	0.4	1	79.5	-	1
	Caught-in	2.5	1	136.0	2	3
	Collision	2.5	1	243.5	-	3
	Struck-by	0.8	1	219.1	-	3
Loading/unloading	Falling	3.4	2	210.9	-	3
	Tripping	0.4	1	170.5	-	3
	Caught-in	10.3	3	160.5	3	3
	Collision	6.4	3	129.4	-	2
	Struck-by	3.9	2	169.1	2	3
Forward driving	Falling	0.5	1	101.6	1	3
	Tripping	0.4	1	78.3	-	1
	Caught-in	4.9	2	145.0	4	3
	Collision	23.0	3	199.7	1	3
	Struck-by	1.2	1	146.7	-	2
Backward driving	Falling	0.5	1	188.6	-	3
	Tripping	0.0	1	-	-	1
	Caught-in	2.1	1	223.6	1	3
	Collision	25.6	3	166.7	2	3
	Struck-by	0.4	1	156.3	-	2
Work completion	Falling	0.3	1	68.0	-	1
	Tripping	0.8	1	94.6	-	1
	Caught-in	0.1	1	-	1	3
	Collision	0.6	1	120.5	-	2
	Struck-by	0.0	1	-	-	1

Note. Sick leave days is the average of injured workers’ sick leave days except the deceased.

For severity, the average of sick leave days for each industrial accident type in the work process was used. Table 8 lists the classification criteria for frequency and severity. The frequency and severity level in Table 8 followed the classification criteria of an existing research report [29]. If the risk assessment result is “high” or “medium,” improvement measures to remove the risk or lower it to an allowable level should be performed [29]. If it is “low,” improvement measures should be performed as needed [29].

Table 8

Grading criteria for frequency and severity

Frequency		Severity		Risk level
F	Accident (%)	S	Sick leave days	C = F×S	Level
3	> 6	3	Death > 0 or > 170	≥6	High
2	3–6	2	80–170	4–5	Medium
1	< 3	1	< 80	≤ 3	Low

Table 9 presents the risk assessment results. Items with a frequency (%) less than 1%were excluded from the risk matrix unless they caused death. The accidents that had the highest risks were getting caught-in in the loading/unloading step and collision in forward- and backward-driving steps. Other accidents that had high risk levels were falling, struck-by, and collision in the loading/unloading steps and getting caught-in in the forward-driving step.

Table 9

Risk matrix

Frequency (F)	Severity (S)
	3	2	1
3	<High>	<High>	-
	Loading/unloading: caught-in	Loading/unloading: collision
	Forward driving: collision
	Backward driving: collision
2	<High>	-	-
	Loading/unloading: falling
	Loading/unloading: struck-by
	Forward driving: caught-in
1	<Medium>	<Low>	<Low>
	Work preparation: struck-by	Work preparation: falling	Work preparation: tripping
	Work preparation: collision	Forward driving: struck-by	Forward driving: tripping
	Work preparation: caught-in	Backward driving: struck-by	Backward driving: tripping
	Loading/unloading: tripping	Work completion: collision	Work completion: falling
	Forward driving: falling		Work completion: tripping
	Backward driving: falling		Work completion: collision
	Backward driving: caught-in
	Work completion: caught-in

Note. Shading represents the risk level shown in Table 8.

4 Discussion and conclusion

This study examined differences in forklift accidents by the employment type of workers through an analysis of forklift accident characteristics. Many studies have reported that irregular workers are more vulnerable to industrial accidents than are regular workers [30 –36]. When the industrial forklift accidents in 2018 were analyzed by regular and irregular workers, differences were per age, employment period, and company size. In South Korea, workers often leave their companies when they are in their 50 s and it is difficult for older workers to get regular jobs again; therefore, most get irregular jobs [37, 38]. Because many older workers work as irregular workers who are more vulnerable to industrial accidents, in the analysis of industrial forklift accidents, the proportion of injured workers in their 40 s and 50 s was high among regular workers; however, the proportion of injured workers in their 50 s and 60 s was high among irregular workers.

When the characteristics of industrial accidents were analyzed by employment period, both regular and irregular workers with less employment showed a higher ratio of industrial accidents. Especially, irregular workers with less than six months of employment accounted for 84.9%of irregular workers’ forklift accidents. This reflects the characteristic of short-term employment among irregular workers [38]. This result also reflects the fact that workers with a short employment period are likely to be exposed to various risks because they are not yet familiar with the working environment [39].

When the characteristics of forklift accidents by company size were analyzed, both regular and irregular workers in companies with 49 or fewer workers had a high ratio of industrial accidents. In South Korea, the safety management of small companies is poor because the Occupational Safety and Health Act requires a safety manager only for companies with 50 or more workers. The current result reconfirmed the fact that small companies have a higher industrial accident rate than medium to large companies owing to frequent turnover, poor work skills/experience, limited budget, and a lack of safety education [40].

When the forklift accidents by industrial accident type were compared between regular and irregular workers, there was no difference between them. Furthermore, there was no difference in accidents by forklift work process between regular and irregular workers. This means that the industrial accident types by work process are similar regardless of worker type. Therefore, regardless of employment type, this means that recurrence prevention measures should be established and conducted for industrial accident types with the highest risks to effectively reduce industrial forklift accidents.

The Occupational Safety and Health Act of South Korea prescribes many safety-related regulations to prevent industrial forklift accidents; however, many accidents still occur—the most among all single ind-ustrial machines. To achieve a visible reduction in the number of industrial forklift accidents, it is nec-essary to deal first-hand with hazards that cause frequent and fatal injuries. The current risk assessment revealed that caught-in accidents during loading/unloading or collision accidents during forward or backward driving had the highest risk, followed by falling, struck-by, and collision accidents during loa-ding/unloading and caught-in accidents during forward driving. In other words, among the work processes, loading/unloading work and forward- and backward-driving work were the riskiest. By industrial accident type, collision accidents had the highest risk, followed by caught-in, struck-by, and falling accidents.

For obtaining a better understanding of the characteristics of forklift accidents, data spanning several years should be analyzed. However, owing to the limitations with respect to data collection, this study analyzed the characteristics of forklift accidents using only data from 2018.

Based on the above results, measures that address the work, employers, and workers are required to reduce industrial forklift accidents. First, concerning work, it is necessary to strictly separate between the forklift movement route and the worker movement route or ensure the route is controlled by a work supervisor. When the movement paths of forklifts and workers inevitably intersect, it is necessary to install a signal lamp and a breaker to prevent contact between forklifts and workers. If it is not possible to separate the pathway owing to the nature of the workplace, the work supervisor should have full control. A means of effective communication between the work supervisor and a forklift operator is also required. In addition, to prevent caught-in or struck-by accidents during loading/unloading work, it is important to prevent the cargo from being tilted to one side. It is also crucial to provide a time margin for workers to escape from the collapsing cargo using appropriate tools or jigs during loading/unloading work.

Second, concerning employers, guidance, inspection, and support to strengthen the health and safety awareness of employers is required in companies with 49 or fewer workers. For said employers with a poor financial status, it is necessary to provide assistance through the industrial accident prevention fund to install facilities that can address the above aspects.

Third, concerning workers, intensive safety and health education and training are required for workers who have been employed for less than 6 months.

In sum, the current analysis of the characteristics of forklift accidents is meaningful in that it can be used as basic data for the establishment of accident prevention measures in companies or in governmental policy.

Conflict of interest

None to report.

Funding

No funding was received to conduct this research.

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