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This paper reports on the reliability data analysis and modelling of offshore oil platform plant. We first analysed the effectiveness of preventive maintenance to the plant concerned, and then identified the key sub‐units and major preventive maintenance activities to be modelled. A modelling technique called the delay time is then used to determine the optimal periodic inspection intervals. The analysis showed that preventive maintenance is generally effective, but a slight decrease of the periodic inspection intervals is favourable.

The authors consider systems that generate damage to environment as they get older and degrade. The purpose of this paper is to develop an optimal condition-based maintenance strategy for such systems in situations where they have a finite operational time requirement. The authors determine simultaneously the optimal number of inspections and the threshold level of environmental damage which minimize the total expected cost over the considered finite time horizon.

The environmental degradation level is monitored through periodic inspections. The authors model the environmental degradation process due to the equipment’s degradation by the Wiener process. A mathematical model and a numerical procedure are developed. Numerical calculations are performed and the influence of the variation of key parameters on the optimal solution is investigated.

Numerical tests indicate that as the cost of the penalty related to the generation of an excess damage to environment increases, inspections should become more frequent and the threshold level should be lowered in order to favor preventive actions reducing the probability to pay the penalty.

Given the complexity of the cost function to be minimized, it is difficult to derive analytically the optimal solution. A numerical procedure is designed to obtain the optimal condition-based maintenance policy. Also, the developed model is based on the assumption that the degradation follows a process with stationary independent increments. This may not be appropriate for all types of degradation processes.

The proposed optimal maintenance policy may be relevant and very useful in the perspective of green operations. In fact, this paper offers to decision-makers a comprehensive approach to implement a green maintenance policy and to rapidly understand the net effect of the maintenance policy with respect to environmental regulation requirements.

The main contribution consists in the modeling and optimization of the condition-based maintenance policy over a finite time horizon. Indeed, existing condition-based maintenance models over an infinite time horizon are not applicable for systems with a finite operational time requirement.

The purpose of this paper is the simultaneous determination of optimal replacement threshold and inspection scheme for a system within condition-based maintenance (CBM) framework.

A proportional hazards model (PHM) is used for risk of failure and a Markovian process to model the system covariates. Total expected long-run cost (including replacement, inspection and downtime costs) is formulated in terms of replacement threshold and inspection scheme. Through an iterative procedure, for all different values of replacement thresholds, their associated optimal inspection scheme is determined using an effective search algorithm. By evaluating the corresponding costs, the optimal replacement threshold and its associated optimal inspection scheme are, then, identified.

The mathematical formulation, that takes into account all different costs, required for the simultaneous determination of optimal replacement threshold and optimal inspection scheme for an item subjected to CBM using PHM is provided. The proposed approach is compared against classical age policy and one state-of-the-art policy through a numerical example. The results show that the proposed approach outperforms other comparing policies.

In practical situations where CBM is implemented, inspections and downtime often incur cost. Under such circumstances, findings of this paper can be utilized for the determination of optimal replacement threshold and optimal inspection scheme so that the CBM cost is minimized.

In most of the reported researches, it is often assumed that inspections have no cost and/or that the time for replacements (either preventive or at failure) is negligible. In the contrary, in this paper the author takes all cost factors including inspection costs, replacement time(s) and their associated downtime costs into account in the simultaneous determination of optimal replacement threshold and optimal inspection scheme.

The main purpose of this paper is to present an optimal economic solution for a different adaptive sampling method that is highly intuitive in its nature: the normal sampling intervals (NSI) method.

Considering costs associated with sampling, false alarms and imperfect operation per unit of time, the paper presents a new optimal simple solution that minimizes the expected total cost per cycle. This NSI method involves the density function of the standard normal variable, assuming that the distribution of averages is normal or approximately normal (on the basis of the central limit theorem). It depends on a single scale parameter while other methods depend on various parameters.

When this expected total cost associated with the new NSI method is compared with the fixed (FSI) and variable sampling intervals (VSI) methods, in identical situations, it may be seen that, in general, it is lower (and may be much lower) and, also, that it is lower for a wider range of changes in terms of quality. This feature is particularly important because, in practice, the degree of change that occurs is not known, so this greater robustness in terms of performance is relevant.

In the practice, the minimization of total expected costs is an important point of view in the life of companies, concerning quality and statistical process control (SPC). The paper holds that this NSI method has a great degree of potential, in particular considering that in industrial processes there is growing recourse to automated systems for the collection and analysis of samples, and thus there are no special additional costs associated with labour, management or administration.

The great advantages of this NSI method are its highly intuitive nature and the fact that it enables generally much better results to be achieved as compared with the use of FSI and VSI methods. An optimal economic solution for this NSI method is presented in this paper.

The purpose of this study is to propose and model an inspection and preventive maintenance policy for randomly failing systems that alternate operating and idle periods according to their mission profile.

A maintenance policy is defined and modeled mathematically. The paper focuses on finding the age T for inspection which maximizes the stationary availability of the system.

Except for the case of only self‐announcing failures, there always exists a finite optimal strategy T*. Two sufficient conditions for the uniqueness of such an optimum are also derived.

Many productive systems alternate operating and inactive periods, their failures may be self‐announcing or not self‐announcing (detected only through inspection). This paper presents a maintenance strategy for such systems in order to maximize their stationary availability. The proposed strategy suggests submitting the system to inspection when its age reaches T units of time.

This paper states a general expression of the system stationary availability which is considered as the performance criterion. Conditions of existence and uniqueness of an optimal strategy are developed.

The purpose of this paper is to present an overview of storage tank incidents and the causes of the incidents. The paper also seeks to present a brief overview on Abu Dhabi Company for Onshore Oil Operations (ADCO) experience of Jebel Dhanna (JD) export terminal.

Major hazard installations (MHIs) store large quantities of flammable material in storage tanks. Storage tanks represent important capital assets and are often critical operational items. The failure of a tank can have several undesirable effects such as endangering personnel, affecting the environment and interrupting the operator's business. The storage tank incidents and ADCO's experience on operating of an export terminal are collected from several sources such as technical articles, text books, internet web sites, and internal reports. The incidents and the causes of the incidents are reviewed and summarised. The ADCO's experience in operation of a crude oil tank farm are outlined.

The world has witnessed 480 tank fire incidents in the period 1951‐2003. The major cause of storage tank fire incidents was due to lightning. The leaks and the spills from the tanks were due to corrosion, operation, improper or lack of maintenance, poor design and/or maintenance of piping systems, fire and explosion. Although several studies have been carried out to record the tank incidents and the causes of the incidents the studies were not comprehensive. Many tank fire incidents that occurred have not been recorded in the previous studies. ADCO have been operating the JD crude oil terminal for more than three decades without a major incident. This was achieved through the design, operation and maintaining of the tanks in accordance with international standards, periodical studies by expert consultancy, and regular development of the control and protection systems with up‐to‐date technology.

The findings highlight that an international storage tank incidents database should be established to compile the scattered data in one site. The tank incidents database encourges the MHIS to publish tank incidents. The database can assist MHIs as well as the research institutes to learn lessons from the incidents. MHIs publishing articles is one of the means of sharing and exchanging the experience with similar installations and institutes.

The purpose of this paper is to determine a nearly optimal inspection sequence for a series system consisting of two components subject to gradual deterioration and whose failures are not self-announcing and can be detected only through inspection.

The problem is tackled in the context of condition-based maintenance (CBM) with a maintenance model in the class of the control-limit policies for which the maintenance decision is made following inspection by comparison of the deterioration level to critical thresholds. A mathematical model is developed to express the total expected cost per time unit as a function of the inspection instants.

For any given series system composed of two components with known critical deterioration threshold levels, and for any given set of costs related to inspection, inactivity due to failure, and preventive and corrective replacements of each component, a nearly optimal inspection sequence of the system is derived such as the total expected cost is reduced.

Due to the complexity of the cost model with the inspection instants (×1, ×2, ×3, …) being the decision variables, it has not been possible to derive the optimal solution. A quasi-optimal sequence of inspection times is derived along with the corresponding total average cost per time unit.

In many practical situations in which CBM is implemented, a tradeoff between inspection costs and inactivity and replacement costs has to be balanced when determining the intervals between successive inspections at which the degradation level of the components should be assessed and compared to predetermined critical threshold levels. Inspecting too often would increase inspection costs but in the same time it would also increase the probability to avoid a failure and end up with a preventive replacement, whereas not inspecting often enough would increase the probability to end up with a failure increasing replacement and inactivity costs.

While the inspection problem has been largely treated for single component systems, inspection policies become much more complex when considering multi-component systems. A two-component series system is considered in this paper.

To present an entirely new technology to be used in the in‐service inspection of storage tanks for hazardous products in several different industries.

Current interior storage oil tank plate inspection is a very expensive and time‐consuming task. The related tasks involve high cost, several hazards to environment and the operators involved in the cleaning jobs. Several research areas were investigated during the development of this tool, fundamentally robotics and non‐destructive test tools. Initial trials in laboratory were complemented with a field test program in near‐real conditions.

A new design of tool for in‐service inspection of such equipments proved to be feasible to be constructed and operated and in accordance with current safety regulations.

New robotics application in non‐destructive testing methodologies for application in in‐service storage equipments. The internal conditions possible to find in the interior of a storage tank, like fixtures, properties of the stored products (inflammable and aggressive), sludge and sand on the bottom, no ambient light, etc., are significant challenges to the development of such a tool.

Developed a robotized tool for inspection of the floor and walls of in‐service tanks, in order to allow an evaluation of the condition of the plates of these tanks, avoiding the long period, hazards and high costs necessary for creating the conditions for reality out of service inspection.

The novelty of the RobTank Inspec project could be evaluated from the two or three existing competitors in the world, and the results of the surveys undertaken.

The combined effects of several complex phenomena cause the deterioration of elements in steel hydraulic structures (SHSs) within the US lock system: corrosion, cracking and fatigue, impact and overloads. Predicting the future condition state of these structures by the use of current condition state inspection data can be achieved through the probabilistic chain deterioration model. The purpose of this study is to derive the transition probability matrix using final elements modeling of a miter gate.

If predicted accurately, this information would yield benefits in determining the need for rehabilitation or replacement of SHS. However, because of the complexity and difficulties on obtaining sufficient inspection data, there is a lack of available condition states needed to formulate proper transition probability matrices for each deterioration case.

This study focuses on using a three-dimensional explicit finite element analysis (FEM) of a miter gate that has been fully validated with experimental data to derive the transition probability matrix when the loss of flexural capacity in a corroded member is simulated.

New methodology using computational mechanics to derive the transition probability matrices of navigation steel structures has been presented.

The difficulty of deriving the transition probability matrix to perform a Markovian analysis increases when limited amount of inspection data is available. The used state of practice FEM to derive the transition probability matrix is not just necessary but also essential when the need for proper maintenance is required but limited amount of the condition of the structural system is unknown.

Markov models find optimum inspection intervals for phased deterioration of monitored complex components in a system with severe down time costs. The number of (pseudo)‐phases can be increased, but in most cases, simple models tracking actual states and their perception by the user will suffice, because of paucity of data and near‐constant rates. The matrix is cyclic; it includes renewal and regression to earlier states, simplifying solution and matching observation. An example involves roller bearings in paper mills with three phases, no defect, possible defect, and final deterioration towards failure. In the last phase, continuous monitoring is used.