Risk Analysis on FGH Terminal Using Importance Index and Bowtie Analysis Methods ^†

Abstract

FGH terminal is an operator that provides container services with an integrated and standardized network system. Activities at the FGH terminal have a high risk. There are accidents of workers being hit by trucks carrying containers, trucks crashing into road dividers, trucks crashing into electric poles, container damage, and even death. Thus, it is necessary to conduct a risk analysis to reduce the risk or even eliminate the existing risks. Risk analysis using the Importance Index (IMPI) method is carried out to assess risks by calculating the Frequency Index and Severity Index values, identifying the causes and consequences of risks that are classified as significant, analyzing the causes and impacts of risks and preventive actions and recovery actions from existing risks, and then will be described in a bowtie diagram. Based on risk identification, there are three variables: machine or equipment, human and environmental variables, and 45 indicators. Risk assessment using the IMPI method found 4 risks classified as significant, 12 risks classified as moderate, and 29 low categories.

1. Introduction

Risk is a combination of the possibilities that occur from an event [1]. Risk management is a method to manage risks and take advantage of opportunities to achieve goals [2]. Risk management is also a systematic approach that includes culture, processes, and structures to determine actions that can reduce risk [3]. The implementation of risk management must be well structured to help organizations or companies in a better system and help organizations or companies in the risk management system to be more efficient and effective [4].

Activities at the FGH terminal have high risks, such as accidents, workers being hit by trucks carrying containers, trucks crashing into road dividers, trucks hitting electric poles, container damage, and death. A work accident is an unexpected and unwanted event that can disrupt the process of an ongoing activity [5]. This risk can cause huge losses for the company because it must be responsible for material damage to death caused by accidents in its work area [6]. Overcoming this risk and loss requires a system that can control risk, namely, risk management.

A study by [7] analyzed occupational safety and health using the bowtie method at PT X. The study’s results showed three significant risk variables: employees exposed to hot iron, employees inhaled/exposed to chemicals and noise, and two high variables: employees exposed to hot steam and employees exposed to bursts of fire.

The study conducted by [8] analyzed the risk of work accidents using the bowtie analysis method on the One Galaxy Surabaya project. The results of this study indicate that there are dominant work accident risks, namely, piling work with the hazard of lifting piles using TC, the risk of breaking each other, casting work with the hazard of casting at height, and workers falling from a height.

This study uses two methods, the Importance Index, which assesses risks, and the bowtie analysis, to describe the causes and impacts of risks as well as actions to prevent and mitigate them. This method provides a strategy to control these risks both preventively based on the causes of risk and recovery based on the consequences of risk [9].

2. Method

In addition to questionnaires and direct observation, this study also uses interview techniques that involve expert judgment, ranging from business processes to proposed improvements. Expert judgment is considered an organizational asset because it can provide input to plan and estimate important project activities [10].

The subjects were managers of management systems, HSSE, Customer Development, operations, and engineering support. The data used in this study were primary and secondary. Primary data consisted of observations, interviews, and questionnaires, while secondary data consisted of risk management books, risk analysis journals, company history, and organizational structure.

The data collection technique involves direct interviews, observations in the field, and questionnaire distribution to related parties. The study flow is as follows:

Risk management aims to coordinate activities and control and manage the organization based on risk orientation [11]. Risk is an inseparable part of the growth factor of an organization/company, whether it comes from internal or external factors [12]. A risk is an event that leads to uncertainty that occurs within a specific time span that causes a loss, both small and large, which affects a company’s survival [13]. The types of risks include strategic and policy, operational, compliance, fraud, and financial risks, which can be seen in Figure 1.

Figure 1. Study flow chart.

Risk assessment is a process to determine work activities, estimate work actions, determine whether they have a fatal impact, and make decisions to overcome these causes [14]. Data processing uses the Importance Index (IMPI) method for risk assessment by calculating the Frequency Index and Severity Index. The Frequency Index is the percentage value of the probability or frequency of occurrence of a risk calculated based on respondents’ answers [9]. The Frequency Index value can be calculated using the following formula and Frequency scale in Table 1:

$$\mathrm{FI} (\%)={\displaystyle \frac{{\sum }_1^5{a}_i{n}_i}{5N}}\times 100$$

(1)

Table 1. Frequency scale.

Scale	Category	Criteria
1	Extremely rare	Occurs <2 times
2	Rare	Occurs 2–3 times
3	Sometime	Occurs 3–4 times
4	Often	Occurs 4–5 times
5	Frequent	Occurs >5 times

Means:

FI: Frequency Index

$a_i$: The score given by the respondent with value i

$a_i$ = 1, 2, 3, 4, 5

$n_i$: Number of respondents who answer with value i

$N$: Number of respondents

The Severity Index is the percentage value of the impact of the occurrence of a risk in terms of losses experienced [9]. The Severity Index value can be calculated with the following formula and Severity scale in Table 2:

$$\mathrm{SI} (\%)={\displaystyle \frac{{\sum }_1^5{a}_i{n}_i}{5N}}\times 100$$

(2)

Table 2. Severity scale in AS/NZS 4360 standard [14].

Scale	Description	Mean
1	Insignificant	No injury, little financial loss
2	Minor	Minor injury, little financial loss, disruptive to health
3	Moderate	Moderate injury, medical treatment required moderate financial loss
4	Major	Severe injury, major loss, production interruption
5	Catastrophic	Fatal, huge losses and far-reaching impacts, cessation of all activities

Means:

SI: Severity Index

$a_i$ The score given by the respondent with value i

$a_i$ = 1, 2, 3, 4, 5

$n_i$: Number of respondents who answer with value i

$N$: Number of respondents

Importance Index (IMPI) is a risk assessment method that refers to the Frequency Index and Impact Index of risk occurrence [15]. The formula for this method is as follows:

$$\mathrm{SI} (\%)={\displaystyle \frac{{\sum }_1^5{a}_i{n}_i}{5N}}\times 100$$

(3)

Means:

FI: Frequency Index

SI: Severity Index

Risks that need to be mitigated are those classified as significant and high. The classification in risk assessment is as follows in Table 3:

Table 3. Risk score classification [9].

No.	Category	Criteria
1	Low	0–20
2	Moderate	21–40
3	Significant	41–60
4	High	61–100

The bowtie analysis method describes the causes and impacts of risks and preventive and recovery actions. The bowtie analysis is a bowtie-shaped diagram that describes or visualizes risk events [16]. The bowtie analysis is a combination of two techniques, namely, the fault tree analysis (FTA) technique and the event tree analysis (ETA) technique [16]. The bowtie method considers barriers to prevent accidents, such as safety measures, training, and equipment design [17]. The bowtie analysis diagram is shown in Figure 2.

Figure 2. Bowtie diagram [18].

Bowtie’s analysis focuses on the barriers between causes and risks, as well as risks and their consequences. The input of bowtie analysis is an understanding of the causes and consequences of risk and the constraints and controls that can prevent, reduce, and stimulate the risk. The output of bowtie analysis is a simple diagram image that shows the main path of risks and obstacles to prevent or reduce unwanted consequences or stimulate and promote desired consequences [19].

3. Findings and Discussion

The following Table 4 are risk identification methods based on the actual conditions at the FGH terminal, which have three variables and 45 indicators.

Table 4. Risk identification of FGH terminal.

Variable	Code	Indicator
Machine/Equipment	F1	Container damage during unloading, stacking, or transfer to truck
	F2	Container contents fall or spill during the transfer process
	F3	Refer container damaged by electrical short circuit
	F4	Loading and unloading equipment damaged (broken, scratched, bent, etc.)
	F5	Uncontrolled loading and unloading equipment when lifting containers
	F6	RTG sling broke
	F7	Sling CC (container crain) broke
	F8	Truck crashes guardrail
	F9	Truck crashes container
	F10	Truck crashes into electricity pole
	F11	Truck crashes into the entrance/exit gate
	F12	Truck/other equipment fell into the sea
	F13	Truck/other equipment overturned while loading and unloading
	F14	Reach stacker crashes the container
	F15	Reach stacker crashes into an electricity pole
	F16	Reach stacker crashes into a guardrail
	F17	Forklift crashes into road divider
	F18	Forklift crashes container
	F19	Forklift crashes electricity pole
	F20	Fire due to an electrical short circuit
	F21	Inadequate RTG that slows down loading and unloading activities
	F22	Inadequate CC that slows down loading and unloading activities
	F23	Inadequate head trucks that slow down loading and unloading activities
	F24	Inadequate reach stacker that slows down loading and unloading activities
	F25	Inadequate forklifts that slow down loading and unloading activities
	F26	Machine capacity that does not match the workload
	F27	Inadequate machine maintenance, thus the tools used experience a decrease in performance
	F28	Inadequate fuel for loading and unloading machinery/equipment
	F29	Lack of lighting when loading and unloading at night
Human	G1	Worker falls from the CC (container crain)
	G2	Worker falls from t the top of container
	G3	Worker crushed by a container
	G4	Worker crushed by equipment
	G5	Worker hit by a forklift
	G6	Worker crushed by the truck
	G7	Worker crushed by reach stacker
	G8	Worker crushed by RTG
	G9	Worker crushed by CC
	G10	Worker electrocuted due to short circuit
	G11	Worker behavior is not following existing SOPs
	G12	Worker hit by equipment falling from a top
	G13	lack of manpower
Environment	H1	Docks that are dirty or cause environmental pollution from container contents
	H2	A dusty loading and unloading yard
	H3	Potholed and muddy loading and unloading yards

The risk assessment questionnaire was given to the Management System Manager, HSSE and Customer Care, one operation support person, and one engineering person. After distributing questionnaires to get the Importance Index value, it is necessary to calculate the Frequency Index and Severity Index of each risk first, which can be seen in Table 5.

Table 5. Frequency survey results and Severity Index.

Code		FI			SI
	X1	X2	X3	X1	X2	X3
F1	3	4	3	4	3	3
F2	1	1	1	3	1	3
F3	1	1	1	3	2	2
F4	3	3	4	4	3	3
F5	2	1	1	2	2	1
F6	1	1	1	2	3	2
F7	1	1	1	3	2	3
F8	3	2	3	2	2	2
F9	3	2	3	3	2	2
F10	3	2	3	3	3	3
F11	3	3	3	3	3	2
F12	1	1	1	3	3	2
F13	1	1	1	3	3	2
F14	1	1	1	2	3	3
F15	3	3	2	2	3	2
F16	2	3	2	3	4	2
F17	2	3	2	2	2	2
F18	1	1	1	2	2	2
F19	1	1	1	2	3	1
F20	2	3	3	3	2	3
F21	3	2	2	4	3	4
F22	1	1	1	2	2	2
F23	2	1	2	2	2	3
F24	1	1	1	2	2	2
F25	1	1	1	3	3	3
F26	1	1	2	2	3	2
F27	1	2	2	2	3	3
F28	1	1	2	3	3	3
F29	1	1	2	4	3	2
G1	3	3	3	4	3	4
G2	1	1	1	3	4	3
G3	1	1	1	4	3	4
G4	1	1	1	4	4	4
G5	2	1	1	4	4	4
G6	1	1	1	3	3	3
G7	1	1	1	3	3	4
G8	1	1	1	4	3	4
G9	1	1	1	3	3	4
G10	1	1	1	3	3	4
G11	1	1	1	4	3	4
G12	4	3	4	2	3	2
G13	1	1	1	3	3	3
H1	2	2	3	3	2	2
H2	2	2	2	1	2	2
H3	3	4	4	3	3	3

Source: Result of data processing.

Means:

X1: Respondent 1

X2: Respondent 2

X3: Respondent 3

• Calculation of Frequency Index code F1:

  $$\mathrm{FI} (\%)={\displaystyle \frac{{\sum }_1^5{a}_i{n}_i}{5N}}\times 100$$

  $$\mathrm{FI} (\%)={\displaystyle \frac{{\sum }_1^5\left(1\times 0\right)+\left(2\times 0\right)+\left(3\times 2\right)+\left(4\times 1\right)+(5\times 0)}{5\times 3}}\times 100$$

  $$\mathrm{FI} (\%)={\displaystyle \frac{10}{15}}\times 100$$

  $$\mathrm{FI} (\%)=66.67\%$$
• Calculation of Severity Index code F1:

  $$\mathrm{SI} (\%)={\displaystyle \frac{{\sum }_1^5{a}_i{n}_i}{5N}}\times 100$$

  $$\mathrm{SI} (\%)={\displaystyle \frac{{\sum }_1^5\left(1\times 0\right)+\left(2\times 0\right)+\left(3\times 2\right)+\left(4\times 1\right)+(5\times 0)}{5\times 3}}\times 100$$

  $$\mathrm{SI} (\%)={\displaystyle \frac{10}{15}}\times 100$$

  $$\mathrm{SI} (\%)=66.67\mathrm{\%}$$
• Calculation of Importance Index code F1:

  $$\mathrm{IMPI}={\displaystyle \frac{\mathrm{F}\mathrm{I}\left(\mathrm{\%}\right)\times \mathrm{S}\mathrm{I}(\mathrm{\%})}{100}}$$

  $$\mathrm{IMPI}={\displaystyle \frac{66.67\times 66.67}{100}}$$

  $$\mathrm{IMPI}=44.44$$

The following is a recap of the Importance Index assessment of each risk, which can be seen in Table 6.

Table 6. The calculation results of the Importance Index.

Code	FI (%)	SI (%)	IMPI	Description
F1	66.67	66.67	44.44	Significant
F2	20.00	46.67	9.33	Low
F3	20.00	46.67	9.33	Low
F4	66.67	66.67	44.44	Significant
F5	26.67	33.33	8.89	Low
F6	20.00	46.67	9.33	Low
F7	20.00	53.33	10.67	Low
F8	53.33	40.00	21.33	Moderate
F9	53.33	46.67	24.89	Moderate
F10	53.33	60.00	32.00	Moderate
F11	60.00	53.33	32.00	Moderate
F12	20.00	53.33	10.67	Low
F13	20.00	53.33	10.67	Low
F14	53.33	46.67	24.89	Moderate
F15	46.67	60.00	28.00	Moderate
F16	46.67	40.00	18.67	Low
F17	20.00	40.00	8.00	Low
F18	20.00	40.00	8.00	Low
F19	53.33	53.33	28.44	Moderate
F20	46.67	73.33	34.22	Moderate
F21	20.00	40.00	8.00	Low
F22	33.33	46.67	15.56	Low
F23	20.00	40.00	8.00	Low
F24	20.00	60.00	12.00	Low
F25	26.67	46.67	12.44	Low
F26	33.33	53.33	17.78	Low
F27	26.67	60.00	16.00	Low
F28	26.67	60.00	16.00	Low
F29	60.00	73.33	44.00	Significant
G1	20.00	66.67	13.33	Low
G2	20.00	73.33	14.67	Low
G3	20.00	80.00	16.00	Low
G4	26.67	80.00	21.33	Moderate
G5	20.00	60.00	12.00	Low
G6	20.00	66.67	13.33	Low
G7	20.00	73.33	14.67	Low
G8	20.00	66.67	13.33	Low
G9	20.00	66.67	13.33	Low
G10	20.00	73.33	14.67	Low
G11	73.33	46.67	34.22	Moderate
G12	20.00	60.00	12.00	Low
G13	46.67	46.67	21.78	Moderate
H1	40.00	33.33	13.33	Low
H2	73.33	60.00	44.00	Significant
H3	73.33	53.33	39.11	Moderate

Source: Result of data processing.

The Risk Description:

Significant: At risk, which requires immediate action in order to reduce or even eliminate the negative impact on organizational goals.

Moderate: Moderate risk, which requires SOP monitoring so that the risk does not develop into a serious risk.

Low: Low risk, the consequences of the risk are very small or manageable.

Based on Table 6, there are 29 low categories, 12 moderate categories, and 4 significant categories, namely, code F1 (container damage during unloading, stacking, or transferring to trucks), code F4 (loading and unloading equipment is damaged), code F29 (lack of lighting during loading and unloading at night), and H2 (different loading and unloading fields).

Proposed improvements using bowtie diagram analysis. Discussions with experts determine the significance of mitigation. Risks classified as significant are depicted in the bowtie analysis diagram because they can significantly impact the goals, success, or safety of a project or organization in reputation, finance, and human safety. After determining the cause and impact of existing risks, what will be analyzed next is determining preventive and recovery actions. Preventive action is used to stop the cause, while recovery action is used to stop the impact.

Bowtie diagrams of each significant category risk, namely, code F1 (container damage during unloading, stacking, or transferring to trucks), code F4 (damaged loading and unloading equipment), code F29 (lack of lighting during loading and unloading at night), and code H2 (dusty loading and unloading field), can be seen in Figure 3, Figure 4, Figure 5 and Figure 6.

Figure 3. Bowtie diagram F1.

Figure 4. Bowtie diagram F4..

Figure 5. Bowtie diagram F29.

Figure 6. Bowtie diagram H2.

4. Conclusions

Activities at the FGH terminal have high risks, such as accidents, workers being hit by trucks carrying containers, trucks crashing into road dividers, trucks hitting electricity poles, container damage, and death. This risk can cause enormous losses for the company because it must be responsible for material damage and death caused by accidents in its work area.

This study aims to reduce and eliminate existing risks. Prevention and handling of risks at the FGH terminal are contained in a bowtie diagram, where when handling risk code F1, risk codes F2 and F3 can be handled, then by preventing risk code F4, risk codes F5, F6, F7, F26, F27, and G11 can also be handled.

Based on the identification results above, the conclusion is that there are 3 variables and 45 indicators. The machine/equipment variable has 29 indicators with risk codes F1, F2, F3, F4, F5, F6, F7, F8, F9, F10, F11, F12, F13, F14, F15, F16, F17, F18, F19, F20, F21, F22, F23, F24, F25, F26, F27, F28, and F29. The human variables have 13 indicators with risk codes G1, G2, G3, G4, G5, G6, G7, G8, G9, G10, G11, G12, and G13. There are 3 indicators of environmental variables with risk codes H1, H2, and H3. The results of data processing are that using the Importance Index (IMPI) method there are four significant category risks, namely, code F1, container damage during unloading, stacking, or transferring to trucks; code F4, namely, damaged loading and unloading equipment (broken and bent); code 29, namely, lack of lighting when loading and unloading at night; and code H2, namely, the dusty loading and unloading field. Risk prevention and handling can be seen in the bowtie diagram, which is expected to be applied to the FGH terminal to reduce or eliminate existing risks.