Propulsion Monitoring System for Digitized Ship Management: Preliminary Results from a Case Study

Aiello, Giuseppe; Giallanza, Antonio; Vacante, Salvatore; Fasoli, Stefano; Mascarella, Giuseppe

doi:10.1016/j.promfg.2020.02.018

Cited by 21 publications

(5 citation statements)

References 8 publications

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“…The Federal Government of Germany showcased IR 4.0 as a novel, emerging strategy which facilitates industrial and logistics networks to thoroughly utilize the internationally accessible information and communications systems for an automated interchange of valuable data [14,15]. Aiello et al [16] presented a decision support structure including automated data collection and analysis methods to evaluate the accurate functioning of the propulsion monitoring system of a ship and for early discovery of nascent breakdowns. In another study, Aiello et al [17] conducted a gap analysis between existing business patterns and the next-generation digitalized shipping industry.…”

Section: The Emergence Of Ir 40mentioning

confidence: 99%

Real-Time Implementation of a Fully Automated Industrial System Based on IR 4.0 Concept

Salah¹

2021

Actuators

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With the advent of modern communication and control strategies, existing industrial enterprises are now being transformed as per Industrial Revolution (IR) 4.0 standards to maximize production rates and monetary gains. To cope with the pace of the modern technological revolution, the Government of Saudi Arabia has launched “Vision 2030”. This research article presents the full automation process of an existing production line at the College of Engineering, King Saud University, as per “Vision 2030” guidelines. Initially, a production line was designed to produce flavored yogurt bottles from a user-defined flavor and plain yogurt mixture. The research project was completed in two phases. During phase I, smart sensing, control, and automation equipment were used to minimize human intervention, the so-called semi-automated mode of operation. A bottle-feeding mechanism and robotic arms were later integrated to eliminate human intervention during the second phase. Moreover, during phase II, Node-RED, Telegram Bots, and a Raspberry Pi 4 controller were used to achieve IoT-based monitoring and control as per Industry 4.0 requirements. A comparative performance analysis was conducted between semi-automated and fully automated modes of operation to demonstrate the benefits of the fully automated operational mode. The performance of the fully automated system was found to be superior in comparison with the semi-automated system.

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Section: The Emergence Of Ir 40mentioning

confidence: 99%

Real-Time Implementation of a Fully Automated Industrial System Based on IR 4.0 Concept

Salah¹

2021

Actuators

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“…At the moment, most of the research in the field of smart factories is focused on the planning and sustainability of production ( Aiello et al, 2020 ; Oztemel & Gursev, 2020 ; Zhang et al, 2022 ), as well as on the shortening of the supply chain, partially due to the current geopolitical events in the world ( Anbesh et al, 2021 ; Zheng et al, 2021 ; Asokan et al, 2022 ; Herawati et al, 2021 ; Little & Sylvester, 2022 ; Mandičák et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Addressing Internet of Things security by enhanced sine cosine metaheuristics tuned hybrid machine learning model and results interpretation based on SHAP approach

Dobrojević

Živković

Chhabra

et al. 2023

PeerJ Computer Science

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An ever increasing number of electronic devices integrated into the Internet of Things (IoT) generates vast amounts of data, which gets transported via network and stored for further analysis. However, besides the undisputed advantages of this technology, it also brings risks of unauthorized access and data compromise, situations where machine learning (ML) and artificial intelligence (AI) can help with detection of potential threats, intrusions and automation of the diagnostic process. The effectiveness of the applied algorithms largely depends on the previously performed optimization, i.e., predetermined values of hyperparameters and training conducted to achieve the desired result. Therefore, to address very important issue of IoT security, this article proposes an AI framework based on the simple convolutional neural network (CNN) and extreme machine learning machine (ELM) tuned by modified sine cosine algorithm (SCA). Not withstanding that many methods for addressing security issues have been developed, there is always a possibility for further improvements and proposed research tried to fill in this gap. The introduced framework was evaluated on two ToN IoT intrusion detection datasets, that consist of the network traffic data generated in Windows 7 and Windows 10 environments. The analysis of the results suggests that the proposed model achieved superior level of classification performance for the observed datasets. Additionally, besides conducting rigid statistical tests, best derived model is interpreted by SHapley Additive exPlanations (SHAP) analysis and results findings can be used by security experts to further enhance security of IoT systems.

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“…Hence, in a ship many parameters should be controlled or monitored (Aiello et al, 2020). These parameters include the navigation control equipment on bridge, the speed and position of vessel, the cargo equipment, and the cargo spaces at loading, unloading or in transfer period.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Ships Operation using Integrated Automation Systems

Dagkinis

Psomas

Platis

2022

Int. Jour. Res. Dev

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Global shipping for becoming sustainable will have to organize the ships and each field of shipping industry, in accordance efficient management and operation principles. This will require the adoption of new techniques and the transformation of companies, their ships, systems, and management practices. A modern automation and control system is a fully integrated system covering many aspects of the ship operation. Whether for cargo, passenger or special-purpose ships, Integrated Automation Systems meets every requirement in shipping and offers decisive advantages over the entire "life" of a ship. The adaptation can suit perfectly to the special requirements in shipping and creates the prerequisites for maximum economy, reliability, and safety on board. Integrated Automation includes the propulsion plant operation, power management operation on the auxiliary engines, auxiliary machinery operation, cargo loading and unloading operation, navigation and administration of maintenance and purchasing of spares. The study focuses on implementation of IAS and its contribution in ship's performance and safety. The proposed model incorporates different failure rates for the different sensors of the Integrated Automation system as well as repair actions that need to be performed. The system can experience various levels of deterioration and when a failure occurs, a repair procedure is carried out and the system is restored to its initial fully operational state. A numerical example based on the empirical data is used to illustrate the proposed model. Received: 23 September 2022 / Accepted: 28 November 2022 / Published: 20 December 2022

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Propulsion Monitoring System for Digitized Ship Management: Preliminary Results from a Case Study

Cited by 21 publications

References 8 publications

Real-Time Implementation of a Fully Automated Industrial System Based on IR 4.0 Concept

Real-Time Implementation of a Fully Automated Industrial System Based on IR 4.0 Concept

Addressing Internet of Things security by enhanced sine cosine metaheuristics tuned hybrid machine learning model and results interpretation based on SHAP approach

Enhanced Ships Operation using Integrated Automation Systems

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