Nonparametric adaptive age replacement with a one-cycle criterion

Age replacement of technical units has received much attention in the reliability literature over the last four decades. Mostly, the failure time distribution for the units is assumed to be known, and minimal costs per unit of time is used as optimality criterion, where renewal reward theory simplifies the mathematics involved but requires the assumption that the same process and replacement strategy continues over a very large (‘infinite’) period of time. Recently, there has been increasing attention to adaptive strategies for age replacement, taking into account the information from the process. Although renewal reward theory can still be used to provide an intuitively and mathematically attractive optimality criterion, it is more logical to use minimal costs per unit of time over a single cycle as optimality criterion for adaptive age replacement. In this paper, we first show that in the classical age replacement setting, with known failure time distribution with increasing hazard rate, the one-cycle criterion leads to earlier replacement than the renewal reward criterion. Thereafter, we present adaptive age replacement with a one-cycle criterion within the nonparametric predictive inferential framework. We study the performance of this approach via simulations, which are also used for comparisons with the use of the renewal reward criterion within the same statistical framework.     

Long-term predictive opportunistic replacement optimisation for a small multi-component system using partial condition monitoring data to date

The advanced condition monitoring tools and sensors have changed the decision making on maintenance in modern manufacturing. To face the change, an integrated ‘prognostics-replacement’ framework is proposed to optimise the replacement decision from component-level layer into production system-level layer by using condition monitoring data in this paper. Some special situations such as no failure or suspension histories of many of same or similar components for prognosis, etc., are considered. A novel degradation prediction model is introduced and the failure risk of a component is estimated based on its degradation level and service time. A total current-term cost rate function is defined to determine the replacement clusters and time for performing replacement from an integrated and economic view. A conservative window is used to adjust the replacement time and overcome the prognostic results varying at different inspection time in a long task. To optimise the replacement clusters effectively, a random-keys genetic algorithm (GA) based on convex set theory is developed. The proposed framework is validated by different small systems. Two commonly adopted replacement policies are compared. Sensitive analysis is conducted and the results show the outperformance of our proposed framework.     

Maintenance and replacement policies under technological obsolescence

The technological obsolescence of a unit is characterized by the existence of challenger units displaying identical functionalities, but with higher performances. This paper aims to define and model in a realistic way, possible maintenance policies of a system including replacement strategies when one type of challenger unit is available. The comparison of these possible strategies is performed based on a Monte Carlo estimation of the costs they incur.     

Sensor-driven prognostic models for equipment replacement and spare parts inventory

Accurate predictions of equipment failure times are necessary to improve replacement and spare parts inventory decisions. Most of the existing decision models focus on using population-specific reliability characteristics, such as failure time distributions, to develop decision-making strategies. Since these distributions are unaffected by the underlying physical degradation processes, they do not distinguish between the different degradation characteristics of individual components of the population. This results in less accurate failure predictability and hence less accurate replacement and inventory decisions. In this paper, we develop a sensor-driven decision model for component replacement and spare parts inventory. We integrate a degradation modeling framework for computing remaining life distributions using condition-based in situ sensor data with existing replacement and inventory decision models. This enables the dynamic updating of replacement and inventory decisions based on the physical condition of the equipment.     

Reliability analysis of MTRC's proposed power SCADA system

The Mass Transit Railway Corporation (MTRC) is in the process of replacing its two existing centralized power and environmental SCADA systems and combining them into a single integrated SCADA system with a distributed architecture. As part of this replacement project, the existing dedicated point-to-point communication links to the remote terminal units will be replaced with an FDDI WAN. An objective of this replacement project is to improve the overall reliability of the control system. This paper presents a system reliability analysis demonstrating the reliability improvement gained by this replacement project. The analysis covers all the major components of the control system, including the SCADA system, the communication network, the remote terminal units and the power system. © 1998 John Wiley & Sons, Ltd.     

Study of loading policies for unequal strength shared-load system

This paper presents three policies for load assignment among unequal strength units based on: (1) maximizing the mean time between failure (MTBF) of the system (Policy A); (2) requiring all active units to fail simultaneously (Policy B); and (3) simply taking the same load for all active units (Policy C). The traditional shared-load k-out-of-n: G system performs satisfactorily if at least k of the total n units are up, with load being shared among the surviving units. One of the advantages in such a system is that the active units play the role of both an actuator and a sensor. Thus we have enough time to make corrective replacement of failed units while the system is still kept on duty. We use examples to show that policies A and B have almost the same MTBF (the difference is within 1%), which is much more superior than Policy C. Two indices are used for the selection of valve k, with given number of total units. One is called the effectiveness factor, while the other is the tolerance factor. The former concerns with the effectiveness of load assignments among the surviving units. The latter deals with the time buffer when one more unit fails.     

Reliability Modelling of Multiple Repairable Units

This paper proposes a model selection framework for analysing the failure data of multiple repairable units when they are working in different operational and environmental conditions. The paper provides an approach for splitting the non‐homogeneous failure data set into homogeneous groups, based on their failure patterns and statistical trend tests. In addition, when the population includes units with an inadequate amount of failure data, the analysts tend to exclude those units from the analysis. A procedure is presented for modelling the reliability of a multiple repairable units under the influence of such a group to prevent parameter estimation error. We illustrate the implementation of the proposed model by applying it on 12 frequency converters in the Swedish railway system. The results of the case study show that the reliability model of multiple repairable units within a large fleet may consist of a mixture of different stochastic models, that is, the homogeneous Poisson process/renewal process, trend renewal process, non‐homogeneous Poisson process and branching Poisson processes. Therefore, relying only on a single model to represent the behaviour of the whole fleet may not be valid and may lead to wrong parameter estimation. Copyright © 2015 John Wiley & Sons, Ltd.     

A Petri net-based modelling of replacement strategies under technological obsolescence

The technological obsolescence of a unit is characterised by the existence of challenger units displaying identical functionalities, but with higher performances. Though this issue is commonly encountered in practice, it has received little consideration in the literature. Previous exploratory works have treated the problem of replacing old-technology items by new ones, for identical components facing a unique new generation of items. This paper aims to define, in a realistic way, possible replacement policies when several types of challenger units are available and when the performances of these newly available units improve with time.Since no fully generic model can exist in maintenance optimisation, a modular modelling of the problem, allowing easy adaptations to features corresponding to specific applications is highly desirable. This work therefore proposes a modular Petri net model for this problem, underlying a Monte Carlo (MC) estimation of the costs incurred by the different possible replacement strategies under consideration.     

A framework for evaluating hydrogen control and management

The present paper presents a new framework for assessing accident management strategies using decision trees. The containment event tree (CET) model considers characteristics associated with the implementation of each strategy. It is constructed and quantified using data obtained from NUREG-1150, other probabilistic risk assessments, and the MAAP4 calculations. The proposed framework for evaluating hydrogen control strategies is based on the concept of a measure using a risk triplet. Ulchin units of nuclear power plants 3 and 4 are used as the reference plant. On the basis of best-estimate assessment, it is shown that it is beneficial to execute hydrogen igniters rather than to do nothing with respect to expected value of hydrogen concentration in the containment during an accident. The proposed approach is shown to be flexible in that it can be applied to various accident management strategies based on the timing of mitigation. The advantage of using the CET for assessing an accident management strategy lies with its capability for modeling both the positive and negative aspects associated with progression of the accident, which may in turn affect the containment failure mode.     

Modelling rail vehicle brake pad wearout and replacement

Inspections of rail vehicle multiple units are scheduled in British Rail mainly subject to the recommended interval between inspections of brake pads. This paper presents the development of a model of brake pad wear based on regression analysis and its subsequent use in the consideration of replacement and inspection strategies. The current scrapping size of 11 mm on motor vehicles proved to be too high for it was possible to extend pad life by as much as a third by reducing the scrapping size to 7 mm. On trailer vehicles it was found that the current scrapping size of 6 mm was satisfactory.     

Acquisition of new technology information for maintenance and replacement policies

In this paper, we propose the first model that considers the option to acquire information on the profitability of a new technology that is not yet available on the market for asset maintenance and replacement decisions. We consider the uncertainty of future asset characteristics by incorporating information acquisition decisions into a non-stationary Markov decision process framework. Using this framework, we optimise asset maintenance and replacement decisions as well as the optimal timing of new technology adoption. Through mathematical analyses, the monotone properties and convexity of the value function and optimal policy are deduced. Deeper numerical analyses highlight the importance of considering the acquisition of information on future technology when formulating a maintenance and replacement policy for the asset. We also deduce a non-intuitive result: an increase in the arrival probability of new technology does not necessarily make the acquisition of additional information more attractive.     

A summary of maintenance policies for a finite interval

It would be an important problem to consider practically some maintenance policies for a finite time span, because the working times of most units are finite in actual fields. This paper converts the usual maintenance models to finite maintenance models. It is more difficult to study theoretically optimal policies for a finite time span than those for an infinite time span. Three usual models of periodic replacement with minimal repair, block replacement and simple replacement are transformed to finite replacement models. Further, optimal periodic and sequential policies for an imperfect preventive maintenance and an inspection model for a finite time span are considered. Optimal policies for each model are analytically derived and are numerically computed.     

A Dynamic Memory Allocation Optimization Mechanism Based on Spark

Spark is a distributed data processing framework based on memory. Memory allocation is a focus question of Spark research. A good memory allocation scheme can effectively improve the efficiency of task execution and memory resource utilization of the Spark. Aiming at the memory allocation problem in the Spark2.x version, this paper optimizes the memory allocation strategy by analyzing the Spark memory model, the existing cache replacement algorithms and the memory allocation methods, which is on the basis of minimizing the storage area and allocating the execution area according to the demand. It mainly including two parts: cache replacement optimization and memory allocation optimization. Firstly, in the storage area, the cache replacement algorithm is optimized according to the characteristics of RDD Partition, which is combined with PCA dimension. In this section, the four features of RDD Partition are selected. When the RDD cache is replaced, only two most important features are selected by PCA dimension reduction method each time, thereby ensuring the generalization of the cache replacement strategy. Secondly, the memory allocation strategy of the execution area is optimized according to the memory requirement of Task and the memory space of storage area. In this paper, a series of experiments in Spark on Yarn mode are carried out to verify the effectiveness of the optimization algorithm and improve the cluster performance.     

Vibration analysis diagnostics by continuous-time models: A case study

In this paper a forecasting system in condition monitoring is developed based on vibration signals in order to improve the diagnosis of a certain critical equipment at an industrial plant. The system is based on statistical models capable of forecasting the state of the equipment combined with a cost model consisting of defining the time of preventive replacement when the minimum of the expected cost per unit of time is reached in the future. The most relevant features of the system are that (i) it is developed for bivariate signals; (ii) the statistical models are set up in a continuous-time framework, due to the specific nature of the data; and (iii) it has been developed from scratch for a real case study and may be generalised to other pieces of equipment. The system is thoroughly tested on the equipment available, showing its correctness with the data in a statistical sense and its capability of producing sensible results for the condition monitoring programme.     

Modeling of failure in a high temperature black liquor gasifier refractory lining

Recently, in the pulp and paper industry, black liquor gasification (BLG) has been of interest as a potential replacement for the Tomlinson recovery boiler. Some commercial-scale BLG units have been developed. However, the full potential of high temperature gasifiers has not been realized because of the refractory failure. Computer simulation of existing materials will accelerate materials research in developing new refractory materials. A model based on continuum damage mechanics is presented to analyze the failure behavior of gasifier refractory lining under high temperature and chemical reactive environments by using the finite element method. This work provides a new methodology for the failure analysis of refractory material and would provide a powerful tool in the development of the high temperature gasifier refractories.     

Connecting the strategic to the tactical in SEA design: an approach to wetland conservation policy development and implementation in an urban context

Abstract

The paper presents an analytical approach to strategic environmental assessment (SEA), focused on bridging the strategic level assessment of policy objectives with tactical planning and implementation. This is done within the context of an applied SEA application for urban wetland policy development and implementation in the fast growing city of Saskatoon, Saskatchewan, Canada. An expert-based strategic assessment framework was developed and applied to assess the potential implications of alternative wetland conservation policy targets on urban planning goals, and to identify a preferred conservation policy target. Site-specific algorithms, based on wetland area and wetland sustainability, were then developed and applied to prioritize individual wetlands for conservation so as to meet policy targets within urban planning units. Results indicate a preferred wetland conservation policy target, beyond which higher conservation targets provide no additional benefit to sustainable urban development goals. The use of different implementation strategies, based on wetland area vs. wetland sustainability, provides operational guidance and choice for planners to meet the policy objectives within neighbourhood planning units, but those choices have implications for local land use and wetland sustainability.     

Clean-up time! PCB-filled transformers: environmental threat and commercial opportunity

Transformer oils based on polychlorinated biphenyls (PCBs) were widely used in industry up until the late 1970s, when it became apparent that PCBs build up in the environment and have the potential to be harmful. Bans on their use followed, so that many owners of electrical equipment containing PCBs face the immense task of replacing their units in time to meet national deadlines for phasing out these toxins. Turnkey replacement programmes are now available for PCB-filled transformers and capacitors that help their owners translate the cost of replacing their older units into long-term savings by installing more efficient, state-of-the-art equipment.     

A knowledge-based prototype for optimization of preventive maintenance scheduling

A methodology has been developed, and a prototype tool, the Maintenance Advisor, has been designed and implemented based on this methodology which would assist the scheduling and decision-making for performance of preventive maintenance activities in a plant, based on probabilistic judgedment and probabilistic inference rules. Using data on failure rates, repair times, repair costs and indirect economic costs (e.g. power replacement and accident risk), and within the imposed deterministic constrainst, the program develops an optimum (minimum expected cost) maintenance schedule for the various pieces of equipment described by the model.

The Maintenance Advisor is a frame-based object-oriented tool, programed in KEE and Lisp. Equipment and other objects are represented as complex units, containing a complete set of characteristics, data and functional capabilities. Functional relations between the units are described in terms of two relations: TYPE-OF and PART-OF. The hierarchies formed by these relations serve as the basis for probabilistic and other inferences.     

基于交货期的单机批量加工排序问题

针对钢铁、化工等工业的生产工件需分批、排序加工的特点,借助车辆路径问题的思想给出了制定批量单位的数学模型和基于禁忌搜索算法的求解方法,进一步讨论了这些批量单位在单机模式下,基于交货期的加工排序问题,给出了相应的优化模型和启发式算法。针对热轧生产进行数值仿真,取得了较为理想的成果。     

Optimum Age Replacement Policies with an Ikreasing Cost Factor

Some age replacement policies are investigated for the case in which the cost of keeping an individual unit operating in a system increases with the age of the unit. The optimum age replacement policy is the one which minimizes the average expected cost per unit time over an infinite time span. The case in which the life distribution of the units is exponential is investigated in detail, with numerical examples included.