Jørn Vatn
Norwegian University of Science and Technology
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Featured researches published by Jørn Vatn.
Reliability Engineering & System Safety | 1996
Jørn Vatn; Per Hokstad; Lars Bodsberg
This paper presents an approach for identifying the optimal maintenance schedule for the components of a production system. Safety, health and environment objectives, maintenance costs and costs of lost production are all taken into consideration, and maintenance is thus optimized with respect to multiple objectives. Such a global approach to maintenance optimization requires expertise from various fields, e.g., decision theory, risk analysis and reliability and maintenance modelling. Further, a close co-operation between management, maintenance personnel and analysts is required to achieve a successful result. In the past this has been a major obstacle to the extensive use of proper maintenance optimization methods in practice, and techniques to promote the communication between the involved parties of the optimization process is an essential element in the suggested approach. A simple step by step presentation of the required modelling is provided. Contrary to most current methods of RCM (Reliability Centered Maintenance), the approach is based on an analytic model, and therefore gives a sound framework for carrying out a proper maintenance optimization. The approach is also flexible as it can be carried out at various levels of detail, e.g., adopted to available resources and to the managements willingness to give detailed priorities with respect to objectives on safety vs production loss.
Reliability Engineering & System Safety | 2006
Luca Podofillini; Enrico Zio; Jørn Vatn
Abstract Nowadays, efforts are being made by the railway industry for the application of reliability-based and risk-informed approaches to maintenance optimisation of railway infrastructures, with the aim of reducing the operation and maintenance expenditures while still assuring high safety standards. In particular, in this paper, we address the use of ultrasonic inspection cars and develop a methodology for the determination of an optimal strategy for their use. A model is developed to calculate the risks and costs associated with an inspection strategy, giving credit to the realistic issues of the rail failure process and including the actual inspection and maintenance procedures followed by the railway company. A multi-objective optimisation viewpoint is adopted in an effort to optimise inspection and maintenance procedures with respect to both economical and safety-related aspects. More precisely, the objective functions here considered are such to drive the search towards solutions characterized by low expenditures and low derailment probability. The optimisation is performed by means of a genetic algorithm. The work has been carried out within a study of the Norwegian National Rail Administration (Jernbaneverket).
Reliability Engineering & System Safety | 2011
Ingrid Bouwer Utne; Per Hokstad; Jørn Vatn
Failures in critical infrastructures may be hazardous to population, economy, and national security. There can be strong interdependencies between various infrastructures, but these interdependencies are seldom accounted for in current risk and vulnerability analyses. To reduce probability and mitigate consequences of infrastructure failures, these interdependencies have to be assessed. The objective of this paper is to present a method for assessing interdependencies of critical infrastructures, as part of a cross-sector risk and vulnerability analysis. The method is based on a relatively simple approach applicable for practitioners, but may be extended for more detailed analyses by specialists. Examples from a case study with the Emergency Preparedness Group of the city of Oslo, Norway, are included.
ieee international conference on probabilistic methods applied to power systems | 2006
Thomas M Welte; Jørn Vatn; J Heggest
In this paper a reliability model is presented which can be used for scheduling and optimization of maintenance and renewal. The deterioration process of technical equipment is modeled by a Markov chain. A framework is proposed how the parameters in the Markov process can be estimated based on a description of the technical condition of components and systems in hydro power plants according to the Norwegian Electricity Industry Association. A time dependent solution of the Markov model is presented. Imperfect periodic inspection can be modeled by the proposed approach. The length of the inspection interval depends on the system condition revealed by the previous inspection. The model can be used to compute performance measures and operational costs over a finite time horizon. Finally, simulation results for a dataset for a Norwegian hydro power plant are presented
Reliability Engineering & System Safety | 1998
Jørn Vatn
Abstract The petroleum activities on the Norwegian Continental Shelf are subject to regulations issued by the Norwegian Petroleum Directorate. One important issue in these regulations is the use of acceptance criteria, and this paper discusses some philosophical aspects of acceptance criteria for risk, and the role of statistical decision theory within safety management. Statistical decision theory has been applied in several studies within the nuclear industry, but has not been fully adopted within the petroleum activity. The discussion concludes by listing important measures to manage the acceptable risk problem.
Reliability Engineering & System Safety | 2008
Chang Kwang Pil; Marvin Rausand; Jørn Vatn
The paper gives an introduction to reliability assessment of reliquefaction systems for boil-off gas (BOG) on LNG carriers with focus on redundancy optimization and maintenance strategies. The reliability modeling is based on a time-dependent Markov approach. Four different system options are studied, with varying degree of redundancy. Failures in the reliquefaction system may require flaring of the BOG, and the associated cost is compared with the cost of introducing redundancy and the cost of onboard maintenance. A model for maintenance optimization is developed and exemplified on a main unit of the reliquefaction system. Reliability and maintenance cost data for reliquefaction systems on LNG ships are very scarce. The input data have been collected from the best available data sources and adjusted by expert judgement. A tailor-made computer program has been developed and may be supplied to interested readers.
Reliability Engineering & System Safety | 2010
Jørn Vatn; Terje Aven
Abstract The starting point for this paper is a traditional approach to maintenance optimization where an object function is used for optimizing maintenance intervals. The object function reflects maintenance cost, cost of loss of production/services, as well as safety costs, and is based on a classical cost–benefit analysis approach where a value of prevented fatality (VPF) is used to weight the importance of safety. However, the rationale for such an approach could be questioned. What is the meaning of such a VPF figure, and is it sufficient to reflect the importance of safety by calculating the expected fatality loss VPF and potential loss of lives (PLL) as being done in the cost–benefit analyses? Should the VPF be the same number for all type of accidents, or should it be increased in case of multiple fatality accidents to reflect gross accident aversion? In this paper, these issues are discussed. We conclude that we have to see beyond the expected values in situations with high safety impacts. A framework is presented which opens up for a broader decision basis, covering considerations on the potential for gross accidents, the type of uncertainties and lack of knowledge of important risk influencing factors. Decisions with a high safety impact are moved from the maintenance department to the “Safety Board” for a broader discussion. In this way, we avoid that the object function is used in a mechanical way to optimize the maintenance and important safety-related decisions are made implicit and outside the normal arena for safety decisions, e.g. outside the traditional “Safety Board”. A case study from the Norwegian railways is used to illustrate the discussions.
Archive | 2008
Narve Lyngby; Per Hokstad; Jørn Vatn
This chapter provides a review of ageing/degradation models relevant for railway tracks. Recent models for maintenance/renewal optimization used in railways will also be presented. Further, some of the methods/techniques are applied in a few case studies, using actual data. Finally some future trends are outlined.
Reliability Engineering & System Safety | 1992
Jørn Vatn
Abstract This paper presents a new method for identification of minimal cut sets in a fault tree. The (non-minimal) cut sets are found by a modification of the well-known MOCUS algorithm. These cut sets are stored in a virtual tree structure which requires far less core space than the MOCUS cut set matrix. The minimal cut sets are found by traversing this virtual tree a number of times. In the first cycle, all cut sets of order one are identified. In the next cycle, all cut sets of order two are identified and compared with the cut sets of order one to exclude non-minimal stes. This procedure is continued until all minimal cut sets are identified. The procedure is very fast. Compared to the standard MOCUS program the computer time is reduced by at least a factor of ten.
Reliability Engineering & System Safety | 1997
Jørn Vatn
Abstract Maintenance optimisation is rarely discussed from a decision theoretical point of view. It is believed that maintenance programmes may benefit from using decision theory in a more formal manner. In decision theory there is a sharp line of demarcation between establishing requirements and preferences on one side, and methods for seeking an optimal solution in accordance with the requirements and preferences on the other side. We discuss requirements and preferences concerning maintenance, and how to model these by value and utility functions. Next we discuss how to choose the optimum set of maintenance actions. Influence diagrams are introduced to visualise the relation between maintenance actions, system characteristics and value functions. Finally an illustrative example is given.