Availability estimation and management for complex processing systems

“Availability” is the terminology used in asset intensive industries such as petrochemical and hydrocarbons processing to describe the readiness of equipment, systems or plants to perform their designed functions. It is a measure to suggest a facility’s capability of meeting targeted production in a safe working environment. Availability is also vital as it encompasses reliability and maintainability, allowing engineers to manage and operate facilities by focusing on one performance indicator. These benefits make availability a very demanding and highly desired area of interest and research for both industry and academia. In this dissertation, new models, approaches and algorithms have been explored to estimate and manage the availability of complex hydrocarbon processing systems. The risk of equipment failure and its effect on availability is vital in the hydrocarbon industry, and is also explored in this research. The importance of availability encouraged companies to invest in this domain by putting efforts and resources to develop novel techniques for system availability enhancement. Most of the work in this area is focused on individual equipment compared to facility or system level availability assessment and management. This research is focused on developing an new systematic methods to estimate system availability. The main focus areas in this research are to address availability estimation and management through physical asset management, risk-based availability estimation strategies, availability and safety using a failure assessment framework, and availability enhancement using early equipment fault detection and maintenance scheduling optimization

Utilizaçãoda metodologia "RAMS" na análise de barreiras de segurança de instalações industriais de risco elevado

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201

APPLICATION OF FORMAL SAFETY ASSESSMENT FOR DRY DOCKING EVOLUTION

This research has evaluated the rules, guidelines and regulations related to docking a ship in floating-graving yards. Historical failure data analysis is carried out to identify associated components, equipment and the area of defects related to ship docking evolution problems. The current status of ship docking evolution is reviewed and possible sources which cause accidents are recognised. The major problems identified in this research are associated with risk modelling under circumstances where high levels of uncertainty exist. Following the identification of research needs, this work has developed several analytical models for the application of Formal Safety Assessment (FSA). Such models are subsequently demonstrated by their corresponding case studies with regards to application of FSA for ship docking evolution. Firstly, in this research a generic floating-graving docking model is constructed for the purpose of hazard identification and risk estimation. The hazards include various scenarios, identified from literature reviewed as the major contributors to ship docking failures. Then risk estimation is carried out utilising fault tree (FT) – FSA where there is sufficient data. Secondly, with increased lack of data, risk estimation is carried out using FT-Bayesian network (BN) where interdepencies exists amongst identified hazards. This risk estimation method is validated with the appropriate case study identified. Thirdly, fuzzy rule base and evidential reasoning approaches are used for risk estimation in terms of three risk parameters to select the major causes of component failure that can lead to pontoon deck failure in a floating dock. Possible risk control options (RCOs) are introduced, based on their effectiveness, to select the best RCO for minimising the risks. Finally, a cost benefit assessment is conducted to select the best risk control option using BN, where selections are based on economic terms. The four subjective novel FSA application methodologies in ship docking evolution are constructed from existing theoretical techniques and applied to real situations where data collection is otherwise not possible. The construction of the novel methodologies and the case study applications are the major contribution to knowledge in this thesis. It is concluded that the methodologies proposed possess significant potential for the application of FSA for ship docking evolution based on the validations of their corresponding case studies, which may also be applied with domain specification knowledge tailored to facilitate FSA application in other shipping industry sectors