2 resultados para Strikes

em AMS Tesi di Laurea - Alm@DL - Università di Bologna


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Natural hazards affecting industrial installations could directly or indirectly cause an accident or series of accidents with serious consequences for the environment and for human health. Accidents initiated by a natural hazard or disaster which result in the release of hazardous materials are commonly referred to as Natech (Natural Hazard Triggering a Technological Disaster) accidents. The conditions brought about by these kinds of events are particularly problematic, the presence of the natural event increases the probability of exposition and causes consequences more serious than standard technological accidents. Despite a growing body of research and more stringent regulations for the design and operation of industrial activities, Natech accidents remain a threat. This is partly due to the absence of data and dedicated risk-assessment methodologies and tools. Even the Seveso Directives for the control of risks due to major accident hazards do not include any specific impositions regarding the management of Natech risks in the process industries. Among the few available tools there is the European Standard EN 62305, which addresses generic industrial sites, requiring to take into account the possibility of lightning and to select the appropriate protection measures. Since it is intended for generic industrial installations, this tool set the requirements for the design, the construction and the modification of structures, and is thus mainly oriented towards conventional civil building. A first purpose of this project is to study the effects and the consequences on industrial sites of lightning, which is the most common adverse natural phenomenon in Europe. Lightning is the cause of several industrial accidents initiated by natural causes. The industrial sectors most susceptible to accidents triggered by lightning is the petrochemical one, due to the presence of atmospheric tanks (especially floating roof tanks) containing flammable vapors which could be easily ignited by a lightning strike or by lightning secondary effects (as electrostatic and electromagnetic pulses or ground currents). A second purpose of this work is to implement the procedure proposed by the European Standard on a specific kind of industrial plant, i.e. on a chemical factory, in order to highlight the critical aspects of this implementation. A case-study plant handling flammable liquids was selected. The application of the European Standard allowed to estimate the incidence of lightning activity on the total value of the default release frequency suggested by guidelines for atmospheric storage tanks. Though it has become evident that the European Standard does not introduce any parameters explicitly pointing out the amount of dangerous substances which could be ignited or released. Furthermore the parameters that are proposed to describe the characteristics of the structures potentially subjected to lightning strikes are insufficient to take into account the specific features of different chemical equipment commonly present in chemical plants.

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In this paper, a joint location-inventory model is proposed that simultaneously optimises strategic supply chain design decisions such as facility location and customer allocation to facilities, and tactical-operational inventory management and production scheduling decisions. All this is analysed in a context of demand uncertainty and supply uncertainty. While demand uncertainty stems from potential fluctuations in customer demands over time, supply-side uncertainty is associated with the risk of “disruption” to which facilities may be subject. The latter is caused by external factors such as natural disasters, strikes, changes of ownership and information technology security incidents. The proposed model is formulated as a non-linear mixed integer programming problem to minimise the expected total cost, which includes four basic cost items: the fixed cost of locating facilities at candidate sites, the cost of transport from facilities to customers, the cost of working inventory, and the cost of safety stock. Next, since the optimisation problem is very complex and the number of evaluable instances is very low, a "matheuristic" solution is presented. This approach has a twofold objective: on the one hand, it considers a larger number of facilities and customers within the network in order to reproduce a supply chain configuration that more closely reflects a real-world context; on the other hand, it serves to generate a starting solution and perform a series of iterations to try to improve it. Thanks to this algorithm, it was possible to obtain a solution characterised by a lower total system cost than that observed for the initial solution. The study concludes with some reflections and the description of possible future insights.