Cleaner Engineering and Technology

(1)

Analyzing the influencing factors of Port State Control for a cleaner environment via Bayesian network model

Item Type Article

Authors Chuah, Lai Fatt;Mohd Rof'ie, Nur Ruzana;Mohd Salleh, Nurul Haqimin;Abu Bakar, Anuar;Oloruntobi, Olakunle;Othman, Mohamad Rosni;Mohamed Fazlee, Umi Syahirah;Mubashir, Muhammad;Asif, Saira

Citation Chuah, L. F., Mohd Rof’ie, N. R., Mohd Salleh, N. H., Abu Bakar, A., Oloruntobi, O., Othman, M. R., Mohamed Fazlee, U. S., Mubashir, M., & Asif, S. (2023). Analyzing the influencing factors of Port State Control for a cleaner environment via Bayesian network model. Cleaner Engineering and Technology, 14, 100636. https://

doi.org/10.1016/j.clet.2023.100636 Eprint version Publisher's Version/PDF

DOI 10.1016/j.clet.2023.100636

Publisher Elsevier BV

Journal Cleaner Engineering and Technology

Rights Archived with thanks to Cleaner Engineering and Technology under a Creative Commons license, details at: http://

creativecommons.org/licenses/by/4.0/

Download date 2023-12-01 08:08:46

Item License http://creativecommons.org/licenses/by/4.0/

Link to Item http://hdl.handle.net/10754/691904

(2)

Cleaner Engineering and Technology 14 (2023) 100636

Available online 17 April 2023

Analyzing the influencing factors of Port State Control for a cleaner environment via Bayesian network model

Lai Fatt Chuah

^a^,^*

, Nur Ruzana Mohd Rof ’ ie

^a^,^**

, Nurul Haqimin Mohd Salleh

^a

, Anuar Abu Bakar

^b

, Olakunle Oloruntobi

^a

, Mohamad Rosni Othman

^c

,

Umi Syahirah Mohamed Fazlee

^a

, Muhammad Mubashir

^d

, Saira Asif

^e

aFaculty of Maritime Studies, Universiti Malaysia Terengganu, Terengganu, Malaysia

bFaculty of Ocean Engineering and Informatics, Universiti Malaysia Terengganu, Malaysia

cFaculty of Sciecne and Defence Technology, Universiti Pertahanan Nasional Malaysia, Kuala Lumpur, Malaysia

dPhysical Science and Engineering Division, Advanced Membranes and Porous Materials Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

eFaculty of Sciences, Department of Botany, PMAS Arid Agriculture University, Rawalpindi, Punjab, 46300, Pakistan

A R T I C L E I N F O Keywords:

Bayesian network Port State Control Cleaner environment Maritime safety

A B S T R A C T

Port State Control (PSC) is a critical inspection mechanism used to regulate and remove substandard foreign ships in national ports, with the aim of ensuring compliance with safety and pollution regulations to prevent threats to the environment. With the heavy and concentrated traffic volumes at ports, executing efficient and effective PSC inspections has become increasingly challenging. This study investigates the risk factors of ship detention and identifies the most critical factor for detention to strengthen maritime safety and environmental protection towards cleaner environment. Using six years dataset with a total inspection of 178,153 from 2010 to 2015, a Bayesian network model was developed to analyze the influencing factors of inspection that lead to detention viz. The flag State, ship type, recognized organization, inspection authority and ship age. The results indicate that the flag State has the greatest influence, followed by ship type, recognized organization, inspection authority and ship age in descending order of importance. These findings guide PSC officers and ship owners in identifying critical areas to enhance maritime safety, promote environmental sustainability and achieve a cleaner environment. A similar approach can be applied to PSC inspection records from other years for further analysis.

1. Introduction

The maritime industry has made significant contributions to global economic prosperity by engaging in both national and international trade (Oloruntobi et al., 2023a). The international shipping industry is a crucial component of the global economy (Oloruntobi et al., 2023b), responsible for more than 90% of business activity and employing over 1.6 ×10⁶seafarers through its fleet of 92,647 merchant ships (Chuah et al., 2021a). Maritime shipping is a safer, cheaper, greener and more energy-efficient mode of transportation than others (Chuah et al., 2023).

Catastrophic maritime accidents such as ship collisions, fires, ground- ings and oil spills (Chuah et al., 2022a) can seriously impact the sustainability of international trade and result in significant property losses.

Both the Amoco Cadiz oil spill and the grounding of the Aegean Sea

resulted in disastrous consequences for the environment. The Amoco Cadiz spill alone leaked an astounding 230,000 t of crude oil into the sea, causing severe harm to marine life, habitats and coastlines (Chuah et al., 2022b). The grounding of the Aegean Sea caused pollution and significant damage to the local tourism industry, affecting the livelihoods of many individuals who depended on the industry for their income. Both incidents underscore the devastating impact that oil spills and marine accidents can have on the environment and local communities. Shipping pollution has also gained attention in recent years, as the greenhouse gases (Ameen et al., 2023; Arshad et al., 2023; Ali et al., 2023; Asif et al., 2021) and pollutants emitted by ships contribute to global climate change (Bokhari et al., 2016a, 2016b; Cao et al., 2023; Cheah et al., 2016; Mohd Shamsuddin et al., 2015; Munir et al., 2023; Karim et al., 2022) and acidification (Wang et al., 2021; Abbasi et al., 2023; Ahmad

* Corresponding author.

** Corresponding author.

E-mail addresses: [email protected] (L.F. Chuah), [email protected] (N.R. Mohd Rof’ie).

Contents lists available at ScienceDirect

Cleaner Engineering and Technology

journal homepage: www.sciencedirect.com/journal/cleaner-engineering-and-technology

https://doi.org/10.1016/j.clet.2023.100636

Received 30 March 2023; Received in revised form 12 April 2023; Accepted 16 April 2023

(3)

et al., 2023; Alsaiari et al., 2023; Bokhari et al., 2020). Sustainable development of the maritime transport industry is vital for promoting international trade and driving world economic prosperity while mini- mizing the industry’s impact on the environment.

To promote sustainable development and safeguard the marine environment, the shipping and marine transportation industries require strict regulations. The International Maritime Organization (IMO) and local governments have implemented global and regional conventions for this purpose. To ensure that ships meet the required safety and environmental standards, various measures have been put in place, including Port State Control (PSC) inspection, recognized organization (RO) and flag State administration. These measures work in conjunction with shipowners to control the number of substandard ships in operation and ensure compliance with relevant regulations, both at the international level and within local jurisdictions. By working together, these entities play a critical role in promoting safety and environmental responsibility in the maritime industry (Yang et al., 2018).

The use of substandard ships can have significant negative impacts on both the sustainability of international trade and maritime safety.

Such ships are often poorly maintained and do not meet the required safety and environmental standards, making them more susceptible to accidents and other hazardous incidents. Substandard ships can contribute to increase pollution levels (Chuah et al., 2022c) and other environmental concerns (Bokhari et al., 2019; Aziz et al., 2023; Chuah et al., 2022d; Rashidi et al., 2023), which can have far-reaching consequences for marine life and habitats (Chuah et al., 2021b). It is essential to promote the use of ships that meet the required safety and environmental standards in order to ensure the sustainability of international trade and protect the safety as well as the well-being of those working in the maritime industry. To control such ships and ensure compliance with safety and pollution regulations, port authorities carry out PSC inspections. PSC inspections are carried out on ships that lack proper certification or display a visible defect or fault. These inspections are much more detailed and comprehensive in nature, aimed at identifying any serious deficiencies on board the ship. If any such issues are found, the ship is not allowed to depart until the necessary rectifications have been made. It is important to note that a significant proportion of port calls worldwide, around 17%, are made to ports in the Asia-Pacific region, representing 94 different flag administrations (Chuah et al., 2016, 2021a).

As ports handle a constant flow of ships, PSC inspections play a vital role in enhancing maritime safety. Ship risk profiles, target factors and inspection area design are instrumental in selecting ships for inspection.

Thorough examinations of eligible ships aim to prevent potential harm to the environment (Cao, 2023; Malik et al., 2019; Cao et al., 2021;

Chuah et al., 2017) and improve maritime safety by identifying and detaining substandard ships with detainable deficiencies and various risk factors. There have been a limited number of studies that have specifically examined risk-based PSC inspections, and even fewer have attempted to quantitatively analyze the interactions between the various factors that can influence the effectiveness of these inspections. Despite the importance of this issue for ensuring maritime safety and environmental responsibility, more research is needed to better understand how risk-based PSC inspections can be optimized and how various factors can be prioritized to achieve the best outcomes. By conducting further research in this area, it may enhance the effectiveness of PSC inspections and improve the overall safety and sustainability of the maritime industry.

This article aims to accurately identify the key factors that influence inspection that led to detention by analyzing the Tokyo Memorandum of Understanding (MoU) inspection database from 2010 to 2015. The article intends to utilize Bayesian network (BN) model to rank the identified influencing factors of inspection that lead to detention in Asia- Pacific ports, with a particular emphasis on flag State, ship type, RO, authority and ship age.

This research is organized as follow. Section 2 presents a

comprehensive literature review of PSC inspections in various regions with a focus on ship performance characteristics. In Section 3 describes the study’s methodology and provides an overview of the data collection procedure. The findings of the study are presented and discussed in Section 4, Section 5 concludes the study with a summary of its findings and a discussion of further research needs. This coherent study contributes significantly to the literature on PSC inspections and can guide future efforts to enhance the safety and environmental performance of ships.

2. Literature review

Ship detention is a top concern in ensuring maritime safety and environmental protection. When a ship is detained at a port, delays can force shipping lines to choose alternative ships, resulting in increased operating costs. Legal action by shipowners to recover losses also underscores the need for research into ship detention via PSC, as evidenced by several scholars. Chen et al. (2022) identified PSC regulations, the ISM, fire safety measures and emergency systems as critical factors in ship detentions in the Tokyo MoU region.

The maritime industry is integral to the global economy, as it facil- itates 90% of international goods. This industry provides a cost- effective, energy-efficient and eco-friendly transportation mode for goods and people, which is essential for global trade (Asif et al., 2019;

Oloruntobi et al., 2023b). It is crucial that ships adhere to relevant regulations and meet international standards to reap these benefits fully.

Compliance with these standards not only ensures the safety and well-being of maritime workers but also contributes to industry sustainability and protects the marine environment (Gul et al., 2022;

Khanra et al., 2022; Li et al., 2022). It is imperative to prioritize and increase awareness of compliance with international maritime regulations to foster safer, more sustainable and environmentally conscious shipping practices. PSC inspections are critical in identifying substandard ships to prevent marine accidents and pollution (Hanninen and Kujala, 2014). Well-known accidents such as the Exxon Valdez and the Herald and Estonia passenger ferry cases have highlighted the importance of maritime safety. PSC inspections are essential in reducing the frequency of accidents by identifying the factors that increase the risk of ship detention. The findings can enhance the inspection and detention processes of substandard ships operating in international waters consistent with Chuah et al. (2022b).

PSC is a crucial step in eliminating substandard ships. According to the MoU on PSC in the Asia-Pacific (Tokyo MoU, 2022), cooperation among State members and harmonization of PSC activities plays a crucial role in establishing an effective regime in the region to reduce substandard ships. There are nine conventions serve as the baseline to enhance environmental protection and maritime safety. These include the International Safety Management System (ISM), Maritime Labour Convention (MLC), Merchant Shipping (Minimum Standards) Conven- tion (ILO no 147, 1976), International Convention on Tonnage Mea- surement of Ships (TONNAGE 69), Convention on the International Regulations for Preventing Collisions at Sea (COLREG 72), International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW 78), International Convention on Load Lines (LOADLINES 66), MARPOL 73/78 and International Convention for the Safety of Life at Sea (SOLAS 74/78).

IMO Resolution A.1138(31), procedures for PSC (2019), stipulates that a ship may be classified as substandard if its machinery, equipment, operational safety or hull falls significantly below the standards required by the relevant conventions. If a ship’s crew fails to conform to the safe manning document, it may also be regarded as substandard. This underscores the importance of adhering to the relevant conventions and ensuring that the crew is properly trained and equipped to operate the ship safely and effectively. By following these guidelines, it is possible to enhance the safety and environmental performance of ships, thereby promoting sustainable and responsible maritime practices (S¸anlıer,

(4)

2020). PSC originated from the Hague Memorandum in 1978, which was established after the Amoco Cadiz accident involving a large oil tanker. The Paris MoU was the first PSC system to emerge in 1982, with support from the IMO. In the 1990s, stricter regulations were implemented, emphasizing the improvement of living and working conditions on ships, pollution prevention and life safety at sea. As a result, the PSC system was successfully established. PSC security checks are carried out on ships entering ports in nine regional PSC regimes worldwide, including the Persian Gulf (Riyadh MoU-2004), the Indian Ocean (In- dian Ocean MoU-1998), the Mediterranean Sea (Mediterranean MoU-1997), Black Sea (Black Sea MoU-2000), West and Central Africa (Abuja MoU-1999), Caribbean region (Caribbean MoU-1996), Asia-Pa- cific (Tokyo MoU-1993), Latin America (Vina Del Mar Agreement-1992) and Europe and the North Atlantic (Paris MoU-1982). These regional regimes are all recognized as intergovernmental organizations with observer status by the IMO (Chuah et al., 2022b).

The agreement for the establishment of the Tokyo MoU, which is responsible for PSC inspections in the Asia-Pacific region, was signed on December 1, 1993 and became effect on April 1, 1994. It consists of 21 authorities, including Australia, Malaysia, Republic of Korea, Canada, Hong Kong, Fiji, Japan, Vanuatu, Thailand, Viet Nam, Russian Federa- tion, Chile, Marshall Islands, New Zealand, Indonesia, Philippines, Panama, China, Singapore, Peru and Papua New Guinea. The Asia Pa- cific computerized information system (APCIS) is used to collect PSC inspection data from the Tokyo MoU member Authorities and provide information exchange of PSC data within the region (Chuah et al., 2022b). APCIS is developed and hosted by the Asia Pacific maritime information and advisory services (APMIAS) under the supervision of the Ministry of Transport of the Russian Federation, based in Moscow.

The system assists PSC officers in selecting ships for inspection purposes and provides effective exchange of the PSC inspection history through a comprehensive database system (Chuah et al., 2022b).

During PSC inspections, a team of qualified PSC officers conducts a thorough evaluation of the inspected ship’s condition, beginning with certificate and document checks as noted by Chuah et al. (2022b). If any required certificates are missing or obvious defects are identified, a more detailed inspection is carried out. The inspection team prepares a detailed report that includes information on any deficiencies detected, such as the ship’s name, IMO number maritime mobile service identity (MMSI) number, callsign, RO, flag State, date keel laid, deadweight, tonnage, name of ship master, statutory certificate particular (issued RO, surveyed RO, date of issue, date of expire, date of survey and surveyed port), place of inspection, PSC officer’s name and company data (Chuah et al., 2022b). If any deficiencies are found to pose a threat to maritime safety or the environment at the port, the ship is detained and a report containing the detention date and location is filed. Any identified deficiency items shall be corrected and resolved before the ship is permitted to continue its navigation.

Hanninen and Kujala (2014) developed a BN model that identifies critical areas of inspection that are strongly associated with ship accidents, such as safety of navigation, fire safety and life-saving appliances.

They also introduced the concept of hidden variables to model accident causation mechanisms or system variability. The dataset used in their analysis is limited and not all areas have been inspected in all cases.

Yang et al. (2018) proposed a data-driven BN approach to analyze risk factors influencing PSC inspections and predict ship detention probability, using inspection data of bulk carriers in seven major European countries from 2005 to 2008 under the Paris MoU. The studies identified key risk factors affecting PSC inspections, including the number of deficiencies, type of inspection, RO and ship age. Their BN models demonstrated abilities to predict detention probabilities under different circumstances, providing valuable insights for port authorities to opti- mize their inspection regulations and resource allocation. The findings may not be generalizable to other type of ships or regions. Yang et al.

(2021) used a larger dataset of 49,328 inspection records from 2015 to 2017 from the Paris MoU online inspection database. The study

proposed a new ship detention risk control methodology by incorporating a data-driven BN into the technique for order preference by similarity to an ideal solution (TOPSIS) method. The methodology generates decision criteria from root risk variables and considers established strategies adopted by ship-owners in their ship detention risk control. The study found that ship age, flag and RO are the most significant factors affecting the detention rate of bulk carriers. The methodology’s application only applies to bulk carriers and its effectiveness for other types of ships needs further verification.

After examining existing research, a variety of approaches were found to be used to assess and gain insight into the factors that affect maritime safety. These methods include selection and discretization, and a number of relevant studies have been summarized in the literature, as shown in Table 1. BN model was used for risk analysis, which showed the ability to infer causality and allowed for analysis of the importance and relationships among risk factors. BN has seen increasing use in the context of maritime safety, covering a wide range of areas such as navigational safety, accident analysis and prevention, risk-based ship design, oil spill prevention and PSC inspections. One drawback of BN model is the requirement for abundant data in the form of prior probabilities, which can be difficult to obtain due to the inaccessibility of secured data.

There has been insufficient research conducted on the interaction of various factors in risk-based PSC inspections, making it challenging to gather the necessary data for BN models. Implementing a risk-based PSC inspection study can provide ship owners and port authorities with a method to analyze PSC inspections. By obtaining information on defined nodes, the BN-based PSC model can be used to assess the probability of detention for the ship. Backward risk diagnosis can be used to identify the most critical factor leading to detention. While numerous studies have evaluated the factors influencing safety, research on risk-based PSC inspections has been limited. Most studies on maritime safety have focused on ship navigation, with only a few utilizing PSC inspection data and quantitatively analyzing the significant factors.

To address this gap, this paper thoroughly examines PSC inspection data from 2010 to 2015 in the Tokyo MoU region, identifying and prioritizing the influencing factors of inspection that lead to detention in Asia-Pacific ports using the BN model. The study focuses on factors such as flag State, ship type, RO, authority and ship age. These insights can be valuable to policymakers, facilitating the development of more effective regulations, policies and ship selection criteria. This approach can identify high-risk eligible ships that may result in detention, significantly contribute in enhancing the maritime transportation safety, mitigating the risk of accidents, losses and benefiting the maritime industry as well as the environment and all stakeholders involved.

3. Materials and methods

For this study, data was gathered from PSC inspections conducted by authorized inspectors in the Tokyo MoU region, which includes 21 maritime authorities. Eligible foreign ships calling at ports in the Asia- Pacific region underwent these inspections to ensure compliance with safety and pollution regulations, including living and working conditions, pollution control and safety on board. This data was collected using the APCIS system, which is a database that stores information about ship inspections.

The study used a BN model to evaluate the significance of various factors for PSC inspections. BN is a graphical probabilistic model that establishes connections between cause and effect by assessing the in- terconnections among a web of nodes based on conditional probability (McCann et al., 2006). BN model was created using NeticaTM software (www.norsys.com) and was based on a generic model. The model comprised nodes, states, parent nodes (input nodes), child nodes (conditional nodes), links (arrows) and conditional probability tables (CPTs) (Tighe et al., 2013). Nodes represented variables in the model and were categorized into different states, such as numerical ranges or ranks. For

(5)

this study, nodes represented factors that influence inspection that led to detention viz. flag State, ship type, RO, authority and ship age. Parent nodes provided information to other nodes, while child nodes received information from parent nodes. Links represented causal pathways between parent and child nodes in a graphical manner, indicating the di- rection of influence among variables. CPTs described conditional probabilities between the occurrence of states in parent nodes and the resulting probabilities of states in child nodes. In this study, CPTs were calculated using factor-specific data.

This study used the BN model to evaluate the factors that influence inspection that led to detention. BN model enabled researchers to quantitatively analyze probabilistic relationships between factors and their impact on PSC inspection outcomes, thereby shedding light on the relative importance of various factors influencing inspection that led to detention. Fig. 1 presents the methodology employed.

3.1. Steps for assessing the influencing factors of inspection that lead to detention

The developed framework outlines five steps for assessing the influencing factors of inspection that lead to detention. Step 1 involves identifying the influencing factors based on data collected from various sources, such as a literature review and inspection records. In Step 2, the states of each node are defined using linguistic terms, ranks, or

numerical values. Step 3 involves constructing a generic model for the influencing factors that lead to detention. Step 4 quantifies the strength of dependency between each child node and its associated parents by assigning a CPT. Step 5 evaluates the identified influencing factors based on the calculated conditional probabilities of all nodes and ranks them accordingly.

3.1.1. Identifying the influencing factors of inspection that lead to detention (step 1)

The identification of influencing factors that lead to detention involved collecting data from inspection records on ship inspections in the APCIS and conducting an extensive literature review before identifying the critical factors. The five main criteria identified as influencing factors are flag State, ship type, RO, inspecting authority and ship age.

These factors can be incorporated into a generic model that can be modified or adjusted to suit the decision-making process.

3.1.2. Defining the states of the nodes (step 2)

This step involves defining the states of each factor (node) in the BN model established for assessing the influencing factors for inspection that lead to detention. The purpose of discretizing the nodes into states or ranks is to assign appropriate prior probabilities based on the literature review, which affects the complexity of calculations (CPT and Bayes’ chain rule). It is important to carefully define a consistent Table 1

Risk factors identification.

Author Area of study Type of

research MoU Risk factors identified Yang et al.

(2018) Risk-based PSC inspection based on

data-driven BN model Quantitative Paris Type of inspection, RO, inspection group, age of ship and number of deficiencies.

Wang et al.

(2021) Relationships among the risk factors

influencing PSC inspection Quantitative Tokyo Ship type, RO, inspection location, safety of navigation, working and labor conditions, medical cases, fire safety, social security and gross tonnage.

Chuah et al.

(2022d) Assessment maritime safety and

environment using PSC data Quantitative Tokyo Inspection authority, flag State, RO, ship type, ship age and deficiencies type.

Sanlier (2020) Analysis of PSC inspection in Black Sea

Region Quantitative Black Sea

Region Type of ship, its age, the flag State it belongs to, the authority responsible for inspection, the RO and the type of deficiencies.

Yan et al.

(2021) PSC and its ship selection Quantitative Tokyo Generic factors (age of ship, company, flag, RO and type of ship), dynamic factors and historical factors (number of deficiencies and detentions).

Chen et al.

(2022) Analysis on detention defects according

to association rules Quantitative Paris Type of ship, life saving appliances, safety of navigation, fire safety and ISM.

Fig. 1. Proposed framework for assessing the influencing factors of inspection that lead to detention.

(6)

number of states for each node, such as using an identical number and term for linguistic variables, to ensure simplicity in the evaluation process. In this study, two states, "high" and "low," are used and desig- nated for all nodes in the model.

3.1.3. Developing the generic influencing factors model (step 3)

This study presents a generic evaluation model that can be tailored to the needs of a specific industry or organization. Based on the identified influencing factors, a BN model was constructed to evaluate the factors affecting PSC inspection, as illustrated in Fig. 2. The model can be adjusted or modified according to the user’s preferences.

3.1.4. Determining the conditional probabilities (step 4)

The conditional probabilities in the BN model are determined by calculating the frequency distribution for each input (parent) node using factor-specific data obtained from the inspection records. The strength of the dependency of each child node to its associated parents is quan- tified through a CPT, which is used to calculate the distribution of the daughter node. In Netica, the CPTs are displayed as matrices, containing the probabilities of all possible combinations of child node and parent node states. Each possible combination is represented as a row and the probabilities are summed to 100%. The completion of the conditional probability tables can be achieved using various methods, depending on the available data.

3.1.5. Evaluation of the influencing factors inspection that lead to detention (step 5)

After completing the CPTs, the BN model can be executed and the evaluation of the results can be carried out. The results are presented in two linguistic terms, namely "high" and "low". These results can be used to determine the frequency values of each influencing factor in relation to the ranking of the variables can be obtained.

4. Results and discussion

BN structure in Fig. 3 is created based on the generic network model and parameter learning is performed to obtain the conditional probability distribution of nodes. The influencing factors of inspection that lead to detention are then determined and computed as a set of {(Low, 0.444), (High, 0.556)}, based on the two linguistic terms assigned to each factor.

The BN structure created in Fig. 3 shows that the node "flag State" has the highest probability of contributing to PSC inspection, with a computed probability of {(Low, 0.204), (High, 0.796)}. This indicates that flag State is the most influential factor in determining whether a ship will undergo PSC inspection. The ranking of the influencing factors that lead to detention, in order of importance, are "flag State", "ship type", "RO", "authority" and "ship age".

The high probability (0.796) of the "flag State" node in the BN structure implies that certain flag States of ships are more likely to undergo PSC inspection compared to others, possibly due to variations in regulatory compliance, safety standards or performance records. The

"ship type" node, ranked second, indicates that different types of ships may have different risk profiles impacting their probability of inspection. The "RO" node suggests that the RO of a ship also influences inspection probability. The "authority" (inspection authority) node highlights that different inspection authorities may have varying practices affecting inspection likelihood. The "ship age" node indicates that older ships may be more prone to inspection due to technical flaws or non-compliance with updated regulations. These factors, in order of influence, are: "flag State", "ship type", "RO", "authority" and "ship age", and have significant implications for the shipping industry’s operational costs, compliance requirements and risk profile.

Fig. 2. Generic influencing factors model.

Fig. 3. BN model of influencing factors of inspection that lead to detention in Netica.

(7)

4.1. Flag State

According to the Black-Grey-White (BGW) list for assessing flag performance, ships on the list have different probabilities of undergoing PSC inspections. While ships on the black and grey lists are more likely to undergo inspections due to their high record of ship detentions, the number of ships flying the white-listed flag is much higher. This resulted in a higher overall probability for white-listed ships than for those on the black and grey lists. After using Netica to calculate the CPT, the flag State probability was determined to be {(Low, 0.204), (High, 0.796)}, with the white list being the biggest contributor to this probability, as shown in Fig. 4.

The status of the "flag State" influencing factor in Netica was set to 1, causing a cascade of updates and changes to the probabilities of the entire network and relevant nodes. As a result, the probability of "high"

in the "Influencing factors " node increased from the initial 0.556 to 0.596. This indicates that if a ship is on the BGW list, prioritizing and attending to the "flag State" factor could increase its likelihood of undergoing PSC inspection.

This finding highlight that the flag of registration is a more significant factor than others, such as ship type, RO, authority and ship age, in determining the likelihood of a ship being subjected to PSC inspection.

The finding was consistent with Chuah et al. (2023) These other factors are still significant and should also be considered. The study also found that some flag States have been using PSC inspections as a political tool, which can influence the professional judgement of PSC officers and result in unjust inspections due to a country’s policies.

The "flag State" holds significant influence in determining the inspection that could lead to detention, likely due to its reputation and performance, including its representation on the white list. Changes to the "flag State" node in Netica resulted in updates to other nodes, underscoring the need for a comprehensive approach in evaluating factors affecting PSC inspections. While "flag State" is crucial, the study emphasized the significance of other factors such as ship type, RO, authority and ship age. Ship type can impact compliance and safety standards, while the reputation of RO and authority may affect inspection likelihood. Ship age can impact structural integrity and compliance.

Adopting a holistic approach is essential for developing effective strategies.

The study also raised concerns about potential political influence on

PSC inspections by certain flag States, which could compromise fairness and integrity. The use of PSC inspections as a political tool may result in unjust inspections based on external factors rather than objective safety and compliance criteria. Promoting transparency, accountability and international cooperation is crucial in ensuring that PSC inspections are conducted objectively and in accordance with established regulations and guidelines.

4.2. Ship type

The "ship type" has been identified as the second most influential factor in PSC inspections, with a CPT of {(Low, 0.312), (High, 0.688)}, as shown in Fig. 3. When its status probability was set to 1 in Fig. 5, the probability of "high" in "Influencing factors of inspection that lead to detention" increased from 0.556 to 0.618 through Netica’s automatic updating function. This suggests that the ship’s probability of undergoing PSC inspection could be influenced by its inspection and detention records, depending on its type. The major ship types that contribute to the probability value of {(Low, 0.312), (High, 0.688)} are general and bulk cargo, container ships, oil and chemical tankers.

The research findings indicate that certain types of ships are major contributors to the likelihood of "ship type" being a significant factor in PSC inspections. General and bulk cargo ships, container ships, oil and chemical tankers are identified as the ship types requiring additional attention and scrutiny during inspections to ensure compliance with safety and environmental regulations.

The study highlights the influence of a ship’s inspection and detention records on its probability of undergoing PSC inspections. Ships with a history of detentions or non-compliance are more likely to undergo inspections, particularly if they belong to ship types associated with higher risk profiles. This underscores the importance of ship operators and owners prioritizing compliance and safety measures, especially for ships classified as general and bulk cargo, container ships, oil and chemical tankers, to minimize the risk of PSC inspections and associated delays and costs.

The study reveals that "ship type" is the second most influential factor in PSC inspections, with certain ship types being more likely to undergo inspections. It is essential to implement robust compliance and safety measures to mitigate risks and avoid the consequences of non- compliance. The findings also suggests that further analysis of ship

Fig. 4. PSC inspection that lead to detention prediction when “flag State” precedence.

(8)

type-specific factors affecting PSC inspections could inform targeted strategies and policies for effective inspection processes in the maritime industry.

4.3. RO

After computing the CPT in Netica, the probability of "RO" was found to be {(Low, 0.551), (High, 0.449)}, with "High Performance" RO contributing the most (Fig. 6). When the status probability of the "RO"

node is set to 1, the probability value of "high" in the "Influencing factors of inspection that lead to detention" increases from 0.556 to 0.666. Since the majority of fleets entering Asia-Pacific Ports are under IACS (Inter- national Association of Classification Societies) classification, the performance level of IACS and non-IACS may differ, which can affect the contribution of "RO" to the probability value of PSC inspection. Both IACS and non-IACS are considered for this factor and are divided based on their performance level (Low, Medium and High Performance).

The research findings reveal that the RO node has a significant influence on the likelihood of PSC inspections that lead to detention, with

"High Performance" RO contributing the most to the probability values.

This highlights the critical role of the RO’s performance level in determining the probability of a ship undergoing PSC inspections. The study found that when the "RO" status probability was set to 1 in the BN model, the probability value of "high" in the "Influencing factors of inspection that lead to detention" node increased significantly, indicating a sub- stantial impact.

The research highlights that the majority of fleets entering Asia- Pacific ports fall under the IACS classification. The performance level of RO can differ, depending on whether they are IACS or non-IACS. The findings noted that both IACS and non-IACS are considered factors in the BN model.

The study’s implications for ship operators and owners are crucial.

The findings emphasize the importance of carefully considering the performance level of the RO associated with their ships, as it can significantly affect the probability of undergoing PSC inspections. Ships with a "High Performance" RO are more likely to undergo inspections, while those with a "Low Performance" RO are less likely. Selecting a reputable and high-performing RO for ship operations is crucial to Fig. 5.PSC inspection prediction when “ship type” precedence.

Fig. 6. PSC inspection prediction when “RO” precedence.

(9)

minimize the risk of PSC inspections and ensure compliance with safety and environmental regulations.

4.4. Authority

According to research findings, the "authority" node has a significant influence on the number of PSC inspections and detentions. The computed status probability of "authority" was found to be {(Low, 0.571), (High, 0.429)}, indicating that different inspecting authorities have varying impacts on the outcome of PSC inspections. When the probability of "authority" is set to 1 in the BN model, the probability value of "high" in the "Influencing factors of inspection that lead to detention" node increases from 0.556 to 0.670, indicating a notable impact (Fig. 7).

The research findings suggest that the performance of RO appointed by inspecting authorities can significantly affect the probability of ships undergoing PSC inspections. The inspecting authorities listed in the study include countries such as Vietnam, Vanuatu, Thailand, China, Singapore, Russian Federation, Malaysia, Republic of Korea, Japan, Indonesia, Marshall Islands, New Zealand, Panama, Philippines, Peru, Papua New Guinea, Hong Kong, Fiji, Chile, Canada and Australia. This highlights the importance of the regulatory practices and statutory services provided by the RO in accordance with international maritime regulations.

Ship operators and owners need to be aware of the performance and reputation of the RO appointed by inspecting authorities in different regions and countries, as it can have a significant impact on the probability of ship inspections and detentions. Understanding the influence of inspecting authorities on PSC inspections can help ship operators and owners proactively manage risks, ensure compliance with regulatory requirements and improve ship performance to avoid disruptions in their operations.

The research findings also underscore the need for harmonization and consistency in the implementation of international maritime regulations to avoid inconsistencies and variances in the frequency and outcome of PSC inspections. It also emphasizes the importance of maintaining strong partnerships and communication channels between ship operators, owners, ROs and inspecting authorities to ensure compliance with international maritime regulations and reduce the likelihood of ship detentions during PSC inspections.

This study highlights the significance of the performance level of ROs, categorized as Low, Medium and High Performance, in impacting

the probability of ships undergoing PSC inspections. It emphasizes the importance of selecting reputable and reliable RO for ship classification and statutory services, as the performance of the RO can influence the overall compliance record of the ship and, consequently, the probability of PSC inspections and detentions.

This research findings also suggest that a multifactorial approach is necessary to manage maritime safety effectively. Proactive measures, such as effective risk management, compliance with international maritime regulations and strategic partnerships with reliable ROs and inspecting authorities, can help ship operators and owners minimize disruptions in their operations, ensure ship safety, compliance and up- hold the highest standards of maritime safety. Further research and analysis in this area can provide valuable insights for improving the effectiveness of PSC inspections and enhancing maritime safety outcomes worldwide.

4.5. Ship age

Fig. 8 illustrates that when the status probability of the node "ship age" is set to 1, which was previously computed as {(Low, 0.584), (High, 0.416)}, the probability value of "high" in "Influencing factors of inspection that lead to detention" significantly increases from 0.556 to 0.672. This indicates that the probability of a ship undergoing PSC inspection is influenced by its age. Specifically, ships aged between 5 and 20 years are more likely to be subjected to PSC inspection, with a probability value of (Low, 0.511), (High, 0.489).

This finding highlights the importance of considering ship age as a significant factor in maritime safety management. Ship operators and owners should be aware of the potential impact of ship age on the likelihood of PSC inspections and take appropriate measures to ensure compliance with regulations and standards to mitigate the risks associated with ageing ships.

An explanation could be that older ships are more likely to experi- ence wear and tear, corrosion and other structural or operational problems, which could increase their risk of noncompliance with safety and regulatory requirements. Consequently, maritime authorities may prioritize inspections of older ships to ensure compliance with safety regulations and standards.

As regulations and standards evolve over time, older ships may be subject to increased scrutiny by PSC inspectors. For example, newer ships may be constructed to comply with updated environmental regulations, whereas older ships may not have been retrofitted to meet these

Fig. 7.PSC inspection prediction when “authority” precedence.

(10)

new requirements. This could result in inspections of older ships to ensure their compliance with updated regulations. The availability and implementation of maintenance and inspection practices may differ between older and newer ships. Older ships may have different maintenance and inspection schedules, and they may struggle to maintain the same level of safety and regulatory compliance as newer ships. This may also contribute to the increased likelihood of PSC inspections for older ships.

It is important to note that other factors, such as the type of ship, its operational history, the flag State and previous inspection and detention records, may also influence the results. A comprehensive analysis of multiple factors is required to fully comprehend the intricate relation- ship between PSC inspections and ship age.

5. Conclusion and further research

PSC inspections play a crucial role in assessing whether inspected ships meet the required standards and identifying any deficiencies that may result in further inspection or detention by the PSC. From the findings, it was noted that several factors other than deficiencies discovered during the PSC inspection have led to ship detentions. For this reason, conducting a comprehensive study to accurately identify the factors that influence PSC inspections is essential to reducing ship detentions and ensuring substandard ships do not operate in open seas. The PSC’s identification of these factors can help narrow down the selection of ships for inspection and improve the effectiveness of inspections in Asia-Pacific ports.

This study used Netica, a BN-based software, to establish the BN for analyzing the influencing factors of inspection that lead to detention in Asia-Pacific ports. BN is one of the most effective tools to use when dealing with uncertainties and probabilities, which enabled this study to produce results with mathematical consistency as well as graphical structures that identified problems clearly and intuitively using probability theory. The results showed that the BN is effective for influencing factors analysis as it can quickly and precisely identify the key causes for PSC inspection while ranking them simultaneously. By identifying the influencing factors of inspection that lead to detention and their strength through rank, prioritization was then executed. This study further established a generic model of influencing factors by combining data collected from inspection and ship detention records in the APCIS of the Tokyo MoU with a literature review for clear visualization purposes.

The result further showed that the flag State is the most influential

factor, which can cause detention compared to other factors. The following are ranked in order of importance: "flag State", "ship type",

"RO", "authority" and "ship age". This new research provides valuable insights for PSC authorities to prioritize risk factors and predict which ships are likely to undergo inspection and detention. Port authorities can now use the identified risk factors to filter ships that require inspection, resulting in a more effective and time-efficient workflow for the PSC.

These identified risk factors could assist in detecting detainable ships and ensure maritime safety from substandard ships. By investigating the risk factors associated with ship detention after a PSC inspection, this research can now provide guidance to ships in ensuring safe navigation and adhering to standard operating procedures. By calculating the rate of each risk factor that leads to ship detention, the importance of these elements in arrests can be established.

Future research can expand on the current study by including additional potential influencing factors of inspection that lead to detention, such as the type of deficiencies identified during inspection, and analyzing the relationships between the selected factors to develop a more precise and inclusive model. As the BN model relies on probability theory, its dependability can be strengthened by incorporating more extensive and comprehensive data as well as conducting sensitivity analyses in Netica. The findings of this study serve as a warning to ship owners and operators to ensure the maintenance of their ships, obtain necessary certificates, documentation and follow standard operations to prevent the detention of their ships during PSC inspections.

While this study provides valuable insights into risk factors associated with ship detentions in the context of PSC inspections, there are limitations that future research could address by expanding the dataset, exploring additional risk factors, assessing effectiveness, examining different regions, exploring economic and operational implications on the shipping industry. This study covers a limited time period; future research should include more recent years and other influencing factors, such as ship size, condition, crew competency and operational factors should be explored for a comprehensive understanding. The generaliz- ability of findings to different regions or ports with different characteristics or regulatory frameworks should be assessed and the effectiveness of PSC inspections in achieving intended outcomes should be investigated. It is further recommended that the economic costs and benefits of PSC inspections for ship owners and their impact on shipping operations, trade routes and industry competitiveness be critically explored.

Flag States are important in ensuring PSC inspections by Fig. 8.PSC inspection prediction when “ship age” precedence.

(11)

implementing targeted measures for high-risk States such as closer monitoring, increased inspections and stricter enforcement. Ship type is another influential variable, requiring tailored inspection protocols and guidelines based on risk profiles and operational characteristics. ROs play a significant role by maintaining robust oversight and monitoring for competence and impartiality, including strengthening accreditation and auditing processes and promoting transparency and accountability.

The inspection authority needs consistent and standardized practices, including coordination, information sharing, best practices and adequate training and resources. Ship age is also significant, which may necessitate proactive measures such as targeted maintenance, retrofit- ting and modernization efforts to address challenges associated with older ships. Policy recommendations of this study include strengthening regulatory oversight of flag States; developing tailored inspection protocols for different ship types; enhancing accreditation and auditing processes for RO; implementing measures to address challenges with older ships; and promoting coordination and information sharing among inspection authorities.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

Data will be made available on request.

Acknowledgements

The authors gratefully acknowledge the valuable input from experts in the Ministry of Higher Education Malaysia, maritime sector and Universiti Malaysia Terengganu (UMT). Heartfelt appreciation to the Ministry of Transportation Malaysia, Prof. Dr. Wan Mohd Norsani Wan Nik, Nurul Akma Abdullah, Assoc. Prof. Ts. Dr. Kasypi Mokhtar, Assoc.

Prof. Dr. Noreha Hashim, Dr. Rudiah Md Hanafiah, Noorasiah Moidu, Suzana Shamsuddin, Nor Bahyah Mohamed, Nur Afiqah Wal’ Affa Elmin, Muhammad Aiman Razali, Siti Nur Hazlinda Hasbu, Rohaida Ariffin, Nurul Atirah Zaidi, Siti Asmah Asmayudin, Dr. Loy Kak Choon, Chew Kuan Lian, Teh Bee Bee, Timmy Chuah Tim Mie and Ong Shying Weei for their support.

References

Abbasi, T.U., Ahmad, M., Asma, M., Rozina, Munir, M., Zafar, M., Katubi, K.M., Alsaiari, N.S., Yahya, A.E.M., Mubashir, M., Chuah, L.F., Bokhari, A., 2023. High efficient conversion of Cannabis sativa L. biomass into bioenergy by using green tungsten oxide nano-catalyst toward s carbon neutrality. Fuel, 126796. https://doi.

org/10.1016/j.fuel.2022.126796.

Ahmad, T., Iqbal, J., Azmi Bustam, M., Babar, M., Tahir, M.B., Sagir, M., Irfan, M., Asgharf, H.M.A., Hassan, A., Riaz, A., Chuah, L.F., Bokhari, A., Mubashir, M., Show, P.L., 2023. Performance evaluation of phosphonium based deep eutectic solvents coated cerium oxide nanoparticles for CO²capture. Environ. Res. 222, 115314 https://doi.org/10.1016/j.envres.2023.115314.

Ali, F., Mehmood, S., Ashraf, A., Saleem, A., Younas, U., Ahmad, A., Bhatti, M.P., Eldesoky, G.E., Aljuwayid, A.M., Habila, M.A., Bokhari, A., Mubashir, M., Chuah, L.

F., Chong, J.W.R., Show, P.L., 2023. Ag− Cu embedded SDS nanoparticles for efficient removal of toxic organic dyes from water medium. Ind. Eng. Chem. Res.

https://doi.org/10.1021/acs.iecr.2c03460.

Alsaiari, M., Bokhari, A., Chuah, L.F., Mubashir, M., Harraz, F.A., Almohana, A.I., Show, P.L., Awasthi, M.K., Rizk, M.A., 2023. Synthesis of methyl esters from Hippophae rhamnoides via pilot scale hydrodynamic cavitation intensification reactor. Renew. Energy 205, 238–247. https://doi.org/10.1016/j.

renene.2023.01.072.

Ameen, M., Zafar, M., Ramadan, M.F., Ahmad, M., Makhkamov, T., Bokhari, A., Mubashir, M., Chuah, L.F., Show, P.L., 2023. Conversion of novel non-edible Bischofia javanica seed oil into methyl ester via recyclable zirconia-based phytonanocatalyst: a circular bioeconomy approach for eco-sustenance. Environ.

Technol. Innov., 103101 https://doi.org/10.1016/j.eti.2023.103101.

Arshad, S., Ahmad, M., Munir, M., Sultana, S., Zafar, M., Dawood, S., Rozinai, Alghamdi, A.M., Asif, S., Bokhari, A., Mubashir, M., Chuah, L.F., Show, P.L., 2023.

Assessing the potential of green CdO2 nano-catalyst for the synthesis of biodiesel using non-edible seed oil of Malabar Ebony. Fuel 333 (2), 126492. https://doi.org/

10.1016/j.fuel.2022.126492.

Asif, S., Ahmad, M., Bokhari, A., Chuah, L.F., Zafar, M., Sultana, S., Mir, S., 2019. In:

Rastegari, A., Yadav, A., Gupta, A. (Eds.), Prospects of Renewable Bioprocessing in Future Energy Systems. Biofuel and Biorefinery Technologies, vol. 10. Springer, Cham, pp. 201–217. https://doi.org/10.1007/978-3-030-14463-0_7.

Asif, S., Klemes, J.J., Mukhtar, A., Saqib, S., Chuah, L.F., Bokhari, A., 2021.

Intensification of biodiesel synthesis in a cavitation system from Xanthium Spinosum oil. Chem. Eng. Trans. 86, 151–156. https://doi.org/10.3303/CET2186026.

Aziz, T., Haq, F., Farid, A., Kiran, M., Faisal, S., Ullah, A., Ullah, N., Bokhari, A., Mubashir, M., Chuah, L.F., Show, P.L., 2023. Challenges associated with cellulose composite material: facet engineering and prospective. Environ. Res. 223, 115429 https://doi.org/10.1016/j.envres.2023.115429.

Bokhari, A., Chuah, L.F., Michelle, L.Z.Y., Asif, S., Shahbaz, M., Akbar, M.M., Inayat, A., Jamil, F., Naqvi, S.R., Yusup, S., 2019. Microwave enhanced catalytic conversion of canola-based methyl ester: optimization and parametric study. In: Azad, A.K., Rasul, M. (Eds.), Advanced Biofuels: Applications, Technologies and Environmental Sustainability. Woodhead Publishing Series in Energy, pp. 153–166. https://doi.org/

10.1016/B978-0-08-102791-2.00006-4.

Bokhari, A., Yusup, S., Asif, S., Chuah, L.F., Michelle, L.Z.Y., 2020. Process intensification for the production of canola-based methyl ester via ultrasonic batch reactor:

optimization and kinetic study. In: Singh, L., Yousuf, A., Mahapatra, D.M. (Eds.), Bioreactors Sustainable Design and Industrial Applications in Mitigation of GHG Emissions. Elsevier Inc, pp. 27–42. https://doi.org/10.1016/B978-0-12-821264- 6.00003-6.

Bokhari, A., Yusup, S., Chuah, L.F., Kamil, R.N.M., 2016a. Relative efficiency of esterified rubber seed oil in a hydrodynamic cavitation reactor and purification via distillation column. Chem. Eng. Trans. 52, 775–780. https://doi.org/10.3303/CET1652130.

Bokhari, A., Yusup, S., Chuah, L.F., Kamil, R.N.M., 2016b. Vacuum distilled post blend crude palm and rubber seed oil methyl esters: optimisation and parametric studies.

Procedia Eng 148, 479–486. https://doi.org/10.1016/j.proeng.2016.06.489.

Cao, D., 2023. An Investigation on Surface Coated Continuous Flax Fiber Reinforced Natural Sandwich Composites by Vacuum-Assisted Material Extrusion Process.

https://doi.org/10.13140/RG.2.2.26091.41760.

Cao, D., Malakooti, S., Kulkarni, V.N., Ren, Y., Lu, H., 2021. Nanoindentation measurement of core–skin interphase viscoelastic properties in a sandwich glass composite. Mech. Time-Dependent Mater. 25, 353–363.

Cao, Y., Sun, Y., Han, N., Li, X., Wang, Q., Sun, K., Si, W., Wang, F., Zhao, X., Bokhari, A., Mubashir, M., Chuah, L.F., Show, P.L., 2023. Novel highly active and selective Co- NS-C efficient ORR catalyst derived from in-situ egg gel pyrolysis. Fuel 333 (1), 126432. https://doi.org/10.1016/j.fuel.2022.126432.

Cheah, K.W., Yusup, S., Chuah, L.F., Bokhari, A., 2016. Physio-chemical studies of locally sourced non-edible oil: prospective feedstock for renewable diesel production in Malaysia. Procedia Eng. 148, 451–458. https://doi.org/10.1016/j.

proeng.2016.06.460.

Chen, Y.L., Lou, N.Y., Liu, G.L., Luan, Y., Jiang, H., 2022. Risk analysis of ship detention defects based on association rules. Mar. Pol. 142, 105123 https://doi.org/10.1016/j.

marpol.2022.105123.

Chuah, L.F., Abd Aziz, A.R., Yusup, S., Klemeˇs, J.J., Bokhari, A., 2016. Waste cooking oil biodiesel via hydrodynamic cavitation on a diesel engine performance and greenhouse gas footprint reduction. Chem. Eng. Trans. 50, 301–306. https://doi.

org/10.3303/CET1650051.

Chuah, L.F., Bokhari, A., Yusup, S., Saminathan, S., 2017. Optimisation on pretreatment of kapok seed (Ceiba pentandra) oil via esterification reaction in an ultrasonic cavitation reactor. Biomass Convers. Biorefin. 7 (1), 91–99. https://doi.org/

10.1007/s13399-016-0207-9.

Chuah, L.F., Mohd Salleh, N.H., Osnin, N.A., Alcaide, J.I., Abdul Majid, M.H., Abdullah, A.A., Bokhari, A., Jalil, E.E.A., Klemes, J.J., 2021a. Profiling Malaysian ship registration and seafarers for streamlining future Malaysian shipping governance. Austr. J. Mar. Ocean Affairs 13 (4), 225–261. https://doi.org/10.1080/

18366503.2021.1878981.

Chuah, L.F., Klemes, J.J., Bokhari, A., Asif, S., 2021b. A review of biodiesel production from renewable resources: chemical reactions. Chem. Eng. Trans. 88, 943–948.

https://doi.org/10.3303/CET2188157.

Chuah, L.F., Chew, K.W., Bokhari, A., Mubashir, M., Show, P.L., 2022a. Biodegradation of crude oil in seawater by using a consortium of symbiotic bacteria. Environ. Res., 113721 https://doi.org/10.1016/j.envres.2022.113721.

Chuah, L.F., Mokhtar, K., Abu Bakar, A., Othman, M.R., Osman, N.H., Bokhari, A., Mubashir, M., Abdullah, M.A., Hasan, M., 2022b. Marine environment and maritime safety assessment using Port State Control database. Chemosphere 304, 135245.

https://doi.org/10.1016/j.chemosphere.2022.135245.

Chuah, L.F., Bokhari, A., Asif, S., Klemeˇs, J.J., Dailin, D.J., Enshasy, H.E., Yusof, A.H.M., 2022c. A review of performance and emission characteristic of engine diesel fuelled by biodiesel. Chem. Eng. Trans. 94, 1099–1104. https://doi.org/10.3303/

CET2294183.

Chuah, L.F., Klemeˇs, J.J., Bokhari, A., Asif, S., Cheng, Y.W., Chong, C.C., Show, P.L., 2022d. A review of intensification technologies for biodiesel production. In:

Gutierrez-Antonio, C., Gomez Castro, F.I. (Eds.), Biofuels and Biorefining. Volume 2:

Intensification Processes and Biorefineries. Elsevier Inc, pp. 87–116. https://doi.org/

10.1016/B978-0-12-824117-2.00009-0.

Chuah, L.F., Mokhtar, K., Mhd Ruslan, S.M., Abu Bakar, A., Abdullah, M.A., Osman, N.H., Bokhari, A., Mubashir, M., Show, P.L., 2023. Implementation of the energy efficiency existing ship index and carbon intensity indicator on domestic ship for marine environmental protection. Environ. Res. 222, 115348 https://doi.org/10.1016/j.

envres.2023.115348.

(12)

Gul, S., Ahmad, Z., Asma, M., Ahmad, M., Rehan, K., Munir, M., Bazmi, A.A., Ali, H.M., Mazroua, Y., Salem, M.A., Akhtar, M.S., Khan, M.S., Chuah, L.F., Asif, S., 2022.

Effective adsorption of cadmium and lead using SO3H-functionalized Zr-MOFs in aqueous medium. Chemosphere 307, 135633. https://doi.org/10.1016/j.

chemosphere.2022.135633.

Hanninen, M., Kujala, P., 2014. Bayesian network modeling of Port State Control inspection findings and ship accident involvement. Expert Syst. Appl. 41, 1632–1646.

Karim, S.S., Farrukh, S., Matsuura, T., Ahsan, M., Hussain, A., Shakir, S., Chuah, L.F., Hasan, M., Bokhari, A., 2022. Model analysis on effect of temperature on the solubility of recycling of Polyethylene Terephthalate (PET) plastic. Chemosphere 307, 136050. https://doi.org/10.1016/j.chemosphere.2022.136050.

Khanra, A., Vasistha, S., Rai, M.P., Cheah, W.Y., Khoo, K.S., Chew, K.W., Chuah, L.F., Show, P.L., 2022. Green bioprocessing and applications of microalgae-derived biopolymers as a renewable feedstock: circular bioeconomy approach. Environ.

Technol. Innovat. 28, 102872 https://doi.org/10.1016/j.eti.2022.102872.

Li, M., Wang, Y., Shen, Z., Chi, M., Lv, C., Li, C., Bai, L., Thabet, H.K., El-Bahy, S.M., Ibrahim, M.M., Chuah, L.F., Show, P.L., Zhao, X., 2022. Investigation on the evolution of hydrothermal biochar. Chemosphere 307, 135774. https://doi.org/

10.1016/j.chemosphere.2022.135774.

Malik, S., Fatima, F., Imran, A., Chuah, L.F., Klemes, J.J., Khaliq, I.H., Asif, S., Aslam, M., Jamil, F., Durrani, A.K., Akbar, M.M., Shahbaz, M., Usman, M., Atabani, A.E., Naqvi, S.R., Yusup, S., Bokhari, A., 2019. Improved project control for sustainable development of construction sector to reduce environment risks. J. Clean. Prod. 240, 118–214. 10.1016/j.jclepro.2019.118214.

McCann, R.K., Marcot, B.G., Ellis, R., 2006. Bayesian belief networks: applications in ecology and natural resource management. Can. J. For. Res. 36, 3053–3062.

Mohd Shamsuddin, N.A., Yusup, S., Ibrahim, W.A., Bokhari1, A., Chuah, L.F., 2015. Oil extraction from Calophyllum inophyllum L. Via soxhlet extraction optimization using response surface methodology (RSM). In: A Paper Presented at the 10th Asian Control Conference (10th ASCC). 31 May -3 June, 2015 at Sutera Harbour Resort.

IEEE Xplore, Kota Kinabalu, Sabah, Malaysia. https://doi.org/10.1109/

ASCC.2015.7244791.

MoU, Tokyo, 2022. Memorandum of Understanding on Port State Control in the Asia- Pacific. Retrieved June 7, 2022, from Tokyo-mou.org website. http://www.tokyo -mou.org/.

Munir, M., Saeed, M., Ahmad, M., Waseem, A., Alsaady, M., Asif, S., Ahmed, A., Khan, M.

S., Bokhari, A., Mubashir, M., Chuah, L.F., Show, P.L., 2023. Cleaner production of biodiesel from novel non-edible seed oil (Carthamus lanatus L.) via highly reactive and recyclable green nano CoWO3@rGO composite in context of green energy adaptation. Fuel 332 (2), 126265. https://doi.org/10.1016/j.fuel.2022.126265.

Oloruntobi, O., Mokhtar, K., Mohd Roza, N., Gohari, A., Asif, S., Chuah, L.F., 2023a.

Effective technologies and practices for reducing pollution in warehouses - a review.

Clean. Eng. Technol., 100622 https://doi.org/10.1016/j.clet.2023.100622.

Oloruntobi, O., Mokhtar, K., Gohari, A., Asif, S., Chuah, L.F., 2023b. Sustainable transition towards greener and cleaner seaborne shipping industry: challenges and opportunities. Clean. Eng. Technol., 100628 https://doi.org/10.1016/j.

clet.2023.100628.

Rashidi, A.R., Wan Azelee, N.I., Abang Zaidel, D.N., Chuah, L.F., Bokhari, A., El- Enshasy, H., Dailin, D.J., 2023. Unleashing the potential of xanthan: a comprehensive exploration of biosynthesis, production and diverse applications.

Bioproc. Biosyst. Eng. 2870–2879. https://doi.org/10.1007/s00449-023-02870-9.

S¸anlıer, S¸., 2020. Analysis of port state control inspection data: the Black Sea Region.

Mar. Pol. 112, 103757 https://doi.org/10.1016/j.marpol.2019.103757.

Tighe, M., Pollino, C.A., Wilson, S.C., 2013. Bayesian networks as a screening tool for exposure assessment. Environ. Manag. 123, 68–76.

Wang, Y., Zhang, F., Yang, Z., Yang, Z., 2021. Incorporation of deficiency data into the analysis of the dependency and interdependency among the risk factors influencing port state control inspection. Reliab. Eng. Syst. Saf. 206, 107277 https://doi.org/

10.1016/j.ress.2020.107277.

Yan, R., Wang, S.A., Peng, C.H., 2021. Ship selection in port state control: status and perspectives. Marit. Pol. Manag. https://doi.org/10.1080/03088839.2021.1889067.

Yang, Z., Yang, Z., Yin, J., 2018. Realising advanced risk-based port state control inspection using data-driven Bayesian networks. Transport. Res. Pol. Pract. 110, 38–56.

Yang, Z., Wan, C., Yang, Z., Yu, Q., 2021. Using Bayesian network-based TOPSIS to aid dynamic port state control detention risk control decision. Reliab. Eng. Syst. Saf.

213, 107784.