Applying a Bayesian Network methodology to an offshore gas turbine driven power generator to demonstrate the cause and effect relationship of the turbine running over-speed and the associated switchboard failures.

This paper investigates the benefits of applying a Bayesian Network in quantitative risk assessment of the integrity of an offshore gas turbine driven generator. The focus of the research is based on the potential failures and incidents associated with an offshore gas turbine running overspeed and failures within the switchboard. The potential consequences that follow said failures, such as fire, explosion and damage to mechanical equipment are also factored into the analysis. A methodology is outlined in order to construct a coherent BN model. This methodology consists of several steps, starting with identifying variables, to then constructing a qualitative BN model from these variables. The methodology culminates in validation of the BN model. A case study, regarding individual and combined component failures is also applied to demonstrate and validate the methodology. The Bayesian network allows the cause-effect relationships to be modelled through clear graphical representation. Similarly, the model can accommodate for continual updating of failure data. Partial validity of the model is demonstrated against some benchmark axioms. It is vital to maintain that the model must remain practical and close to reality from the perspective of gathering data and generating results

Empirical model for forecast the Peruvian sea surface temperature

En el presente trabajo se estudia un modelo empírico basado en el volumen de agua cálida en el Pacífi co ecuatorial que se aplica para hacer previsiones de temperatura superfi cial del mar frente a Perú, lo cual sirve como una herramienta de alerta temprana de los efectos de El Niño. La relación del volumen de agua cálida con la profundidad de la isoterma de 20 °C es mayor en el Pacífi co central en la latitud cero. Los cambios de este volumen afectan después varios meses la temperatura superfi cial del mar frente a Perú, particularmente cuando este volumen presenta anomalías positivas. El modelo logra estimar el momento en que se inicia el aumento de temperature superfi cial del mar asociado a los efectos de El Niño en la Región Niño 1 costera, el momento de ocurrencia del pico de los eventos, y las tendencias a mediano plazo. Palabras claves: Modelo empírico, volumen de agua cálida, Pacífi co Ecuatorial, temperature superfi cial, El Niño. In the present work an empirical model based on the warm water volume in the Equatorial Pacific Ocean is studied as a tool to forecast variations of sea surface temperature off the coast of Perú, which will be useful as a tool for giving early warnings of El Niño effects. The relation between the warm water volume and the depth of the 20°C isotherm is greater in the Central Pacific along latitude 0°. Several months later the changes of this volume affect the sea surface temperature off Perú particularly when its anomalies are positive. The model estimates the time when sea surface temperature begins to rise associated with El Niño effects in the coastal Niño 1 Region, the time when the event peaks, and the medium term trends. Keywords: Empirical model, warm water volume, Equatorial Pacifi c Ocean, surface temperature, El Niñ

A proactive approach to quantitative assessment of disruption risks of petroleum refinery operation

Petroleum refinery consists of numerous process units in operation, which are subjected to diverse accident risks in day-to-day operations under extreme operating conditions. Due to the complexity of petroleum refinery operations, any failure can lead to major accident and a huge financial loss for a petroleum refining company. However, petroleum refinery operations can be disrupted by various risk elements from the organization, technical, operational and external latent conditions. Risk elements are often inherent in operations, which can be based on uncertain knowledge, oversight and lack of perception of interactive events that can lead to disruption. In order to circumvent events that can cause disruption in a petroleum refinery, the criticality of the risk elements and their attributes that are associated with Petroleum Refinery Process Units (PRPU) operations need to be investigated. Therefore, there is a need to identify and assess the most critical risk elements and attributes that can interact to cause the disruption of operational reliability and availability of a petroleum refinery process unit. Hence, this article proposes a robust fuzzy linguistic assessment methodology for identification and assessment of PRPU risk elements and their attributes. The methodology deals with the main challenges of utilising expert's subjective judgements, in terms of the assessment of PRPU risk elements under uncertain situations. The result of the evaluation and ranking of PRPU risk elements and their attributes can provide salient risk information to duty holders and decision makers in the petroleum refinery in order to prioritise resources for risk management of the most critical attributes of the risk elements. © 2020 Elsevier Lt

A Comprehensive Review of Modern Cold Chain Shipping Solutions

Packaging is one of the most important factors affecting the overall cold chain efficiency. This paper aims to examine the current trends of cold chain packaging by conducting a comprehensive review on the current commercially available cold chain shipping solutions. A conceptual model of the cold chain shipping solutions including the structure, categories and components is proposed to provide analytical comparisons with the existing literature. It is found that the shipping solutions can improve the overall cold chain performance in many aspects which include improving temperature control performance, flexibility, safety, sustainability and knowledge sharing of the cold chains. Despite all the advantages, there are still limitations and challenges posed which are also discussed. This is the first paper presenting an overview of commercially available cold chain shipping solutions. It not only contributes to the literature by presenting new knowledge but is also beneficial for all the stakeholders in cold chain packaging by providing practical information and guidelines

Characteristics, Challenges, and Opportunities of Vaccine Cold Chain

Purpose: Main attention regarding vaccine supply chain has been drawn on strategic decision level with a limited concentration on tactical and operational levels. Temperature maintenance along the vaccine supply chain remains to be one of the challenging logistical problems. The purpose of this paper is to understand the characteristics, challenges and opportunities of the vaccine cold chain today and how emerging technologies (e.g. vaccine vial monitoring, thermostable vaccines and new packaging systems) affect its development and implementations that can be done before the availability of new technologies. Design/methodology/approach: Literature review is done on the topic of vaccine cold chain, with the key search word of vaccine cold chain. Supporting resources include the official websites of the World Health Organisation (WHO) and Covid-19 vaccine manufacturers. Findings: The gap between the existing literature and the potential requirements; Trend to future research on vaccine cold chain. Research limitations/implications: Contents about strategic decision level of vaccine supply chain are excluded. Practical implications: Pending for empirical studies; Does not consider cost-effectiveness and environmental impacts on the vaccine supply chain. Originality/value: The number of vaccines has expanded in the past years due to improved immunization programs across the world, and the vaccines for the Covid-19 pandemic have the nature of high demand and pressuring time requirement, posing a need for improvement on the existing cold chain. Many existing pieces of literature on this topic are case-specific or scenario-based, and more general operation management insights are important as well, which can be beneficial to the decision-makers in the vaccine supply chain

Assessing performance using maturity model: a multiple case study of public health supply chains in Nigeria

Purpose: This study aims to determine the factors and dynamic systems behaviour of essential medicine stockout in public health-care supply chains. The authors examine the constraints and effects of mental models on medicine stockout to develop a dynamic theory of medicine availability towards saving patients’ lives. Design/methodology/approach: This study uses a mixed-method approach. Starting with a survey method, followed by in-depth interviews with stakeholders within five health-care supply chains to determine the dynamic feedback leading to stockout and conclude by developing a network mental model for medicines availability. Findings: The authors identified five constraints and developed five case mental models. The authors develop a dynamic theory of medicine availability across cases and identify feedback loops and variables leading to medicine availability. Research limitations/implications: The need to include mental models of stakeholders like manufacturers and distributors of medicines to understand the system completely. Group surveys are prone to power dynamics and bias from group thinking. This survey’s quantitative output could minimize the bias. Originality/value: This study uniquely uses a mixed-method of survey method and in-depth interviews of experts to assess the essential medicine stockout in Nigeria. To improve medicine availability, the authors develop a dynamic network mental model to understand the system structure, feedback and behaviour driving stockouts. This research will benefit public policymakers and hospital managers in designing policies that reduce medicine stockout

Emergency logistics for wildfire suppression based on forecasted disaster evolution

This paper aims to develop a two-layer emergency logistics system with a single depot and multiple demand sites for wildfire suppression and disaster relief. For the first layer, a fire propagation model is first built using both the flame-igniting attributes of wildfires and the factors affecting wildfire propagation and patterns. Second, based on the forecasted propagation behavior, the emergency levels of fire sites in terms of demand on suppression resources are evaluated and prioritized. For the second layer, considering the prioritized fire sites, the corresponding resource allocation problem and vehicle routing problem (VRP) are investigated and addressed. The former is approached using a model that can minimize the total forest loss (from multiple sites) and suppression costs incurred accordingly. This model is constructed and solved using principles of calculus. To address the latter, a multi-objective VRP model is developed to minimize both the travel time and cost of the resource delivery vehicles. A heuristic algorithm is designed to provide the associated solutions of the VRP model. As a result, this paper provides useful insights into effective wildfire suppression by rationalizing resources regarding different fire propagation rates. The supporting models can also be generalized and tailored to tackle logistics resource optimization issues in dynamic operational environments, particularly those sharing the same feature of single supply and multiple demands in logistics planning and operations (e.g., allocation of ambulances and police forces). © 2017 The Author(s

Utilising Bayesian networks to demonstrate the potential consequences of a fuel gas release from an offshore gas-driven turbine

This research proposes the application of Bayesian networks in conducting quantitative risk assessment of the integrity of an offshore gas driven turbine, used for electrical power generation. The focus of the research is centred on the potential release of fuel gas from a turbine and the potential consequences that follow the said release, such as fire, explosion and damage to equipment within the electrical generation module. The Bayesian network demonstrates the interactions of potential initial events and failures, hazards, barriers and consequences involved in a fuel gas release. This model allows for quantitative analysis to demonstrate partial verification of the model. The verification of the model is demonstrated in a series of test cases and through sensitivity analysis. Test case 1 demonstrates the effects of individual and combined control system failures within the fuel gas release model; 2 demonstrates the effects of the 100% probability of a gas release on the Bayesian network model, along with the effect of the gas detection system not functioning; and 3 demonstrates the effects of inserting evidence as a consequence and observing the effects on prior nodes.© IMechE 2018

Benefits for the bunker industry in adopting blockchain technology for dispute resolution

The bunker industry has faced negative perception to their trust and credibility in recent times. This is further compounded by the need for the industry to answer new challenges to meet the requirement of the International Maritime Organization 2020. The aim of this work is to illustrate how blockchain technology may be adopted for aiding in bunker dispute resolution. To demonstrate how blockchain may aid in disputes within the bunker industry, this paper first examines the existing bunker supply process, which involves the formation of contracts under English law, the Bunker Delivery Notes, the different types of disputes that may arise during a bunker transaction and the methods of dispute resolution utilised by the industry. Furthermore, the current literature in relation to blockchain technology and blockchain smart contracts is examined. Finally, interviews and surveys within the industry have been conducted to identify the benefits, and challenges, in adopting blockchain technology. The research found that blockchains may benefit the bunker supply chain resolving the effective resolution of bunker quality disputes. Furthermore, blockchains may also serve as a verification tool for electronic bunker delivery notes, which may aid quality and quantity bunker disputes as well as compliance with the new International Maritime Organisation 2020 requirements. As a result, despite the research having shown blockchain to be situationally dependent and having an element of legal uncertainty, blockchain does offer a solution to aid in bunker disputes and for improving the trust and credibility within the bunker industry

Utilizing the Evidential Reasoning approach to determine a suitable wireless sensor network orientation for asset integrity monitoring of an offshore gas turbine driven generator

This research proposes the most ideal Wireless Sensor Network (WSN) topology for remote integrity monitoring of an offshore gas turbine driven generator. The intention is to design the structure of a number of WSNs within the electrical generation system with varying connection types and methods of relaying data. The research is concerned only with the design of the WSNs, i.e. the hardware and orientation of the sensor nodes and not the software, programming or data protection. This will potentially provide a good base, once an ideal WSN design is determined, to expand the network further incorporating more criteria and develop the necessary software to complete the WSN. The work applies the Evidential Reasoning approach to a number of WSN topologies in order to determine the most suitable based upon an outlined set of performance criteria. Axiom based validation of the methodology is also provided within the analysis