Optimal Replacement Strategy Research Articles

Estimation of ratio of population means in two-occasion successive sampling

ABSTRACTThis article considers the problem of estimation of the ratio of population means at the current occasion based on the samples selected over two occasions. Using auxiliary information on both the occasions, some classes of estimators have been proposed. Properties of the proposed estimators have been studied and their respective optimum replacement strategies are discussed. The gains in efficiency of the proposed classes of estimators over the direct estimator where no past information is used are computed. Theoretical results have been interpreted through empirical studies which are followed by suitable recommendations.

On the use of multi-auxiliary variables to neutralize the effect of non response in two-occasion successive sampling

ABSTRACTIn this work, we have suggested some linear combinations of generalized ratio type estimators in estimation of current population mean when non response occur in two occasion successive sampling. Information on multi-auxiliary variables has been used and sub-sampling of non respondents technique is utilized to cope with the negative effect of non response. Properties of the suggested estimation procedures have been examined and suitable optimum replacement strategies are discussed. Empirical studies are carried out to justify the proposition of estimators. Suitable recommendations have been made.

Optimal scheduling for replacing perimeter guarding unmanned aerial vehicles

Guarding the perimeter of an area in order to detect potential intruders is an important task in a variety of security-related applications. This task can in many circumstances be performed by a set of camera-equipped unmanned aerial vehicles (UAVs). Such UAVs will occasionally require refueling or recharging, in which case they must temporarily be replaced by other UAVs in order to maintain complete surveillance of the perimeter. In this paper we consider the problem of scheduling such replacements. We present optimal replacement strategies and justify their optimality.

Optimizing capital investments under technological change and deterioration: A case study on MRI machine replacement

ABSTRACTWe study the multiple style and type parallel asset replacement problem (MST-PRES), which determines an optimal policy for keeping or replacing a group of assets that operate in parallel under a limited budget. Operating assets generally suffer from deterioration, which results in high operation and maintenance (O&M) cost and decreased salvage value, and technological improvements make it possible for new assets to operate more efficiently at a lower cost. In order to address these issues, we formulate a multi-objective mixed-integer programming (MIP) model that minimizes fixed and variable costs of purchasing new assets, O&M cost, inventory cost, and penalty cost for unmet demand minus salvage values, while considering technological advances and deterioration as a gain and loss in capacity, respectively. We apply our model to a case study involving two different styles of assets: a full-body magnetic resonance imaging (MRI) machine and a smaller extremity magnetic resonance imaging (eMRI) machine. Each has two types: high-field and low-field. We perform computational experiments and analyses using key model parameters and illustrate optimal replacement strategies considering the impact of technological advances and deterioration. Results show that the proposed MIP model provides valuable insights and strategies for companies, decision makers, and government entities on the capital asset management.

Using Reliability Modeling and Accelerated Life Testing to Formulate a Cost Model of Photovoltaic Systems with Different Architectures

As the number of photovoltaic (PV) systems grows annually and ages, the importance of long term reliability to the levelized cost of electricity (LCOE) has become increasingly clear. Likewise innovative PV system architectures being considered present opportunities for differentiation and growth into new markets, but still need to have a model for system reliability in order to justify their LCOE. Other benefits of reliability modeling include setting reliability goals for individual failure modes, determining optimum replacement and maintenance strategies, as well as prioritizing which failure modes require the most consideration in terms of research and testing. Physics of failure and materials properties are key inputs to the outcome of these models. This paper presents the results of reliability models based on accelerated testing, field data and theoretical calculations that were undertaken in order to determine the cost model of reliability of PV systems of different system architectures. Three examples for PV modules are presented here (bypass diodes, solder joints and microinverters) and are used to show how understanding of the reliability of systems based upon materials properties can be used to formulate models for lifetime and costs.

Searching effective rotation patterns for population median using exponential type estimators in two-occasion rotation sampling

ABSTRACTThe present article is an attempt to explore the rotation patterns using exponential ratio type estimators for the estimation of finite population median at current occasion in two occasion rotation sampling. Properties of the proposed estimators including the optimum replacement strategies have been elaborated. The proposed estimators have been compared with sample median estimator when there is no matching from previous occasion as well with the ratio type estimator proposed by Singh et al. (2007) for second quantile. The behaviors of the proposed estimators are justified by empirical interpretations and validated by means of simulation study with the help of some natural populations.

Chain-type ratio estimator in successive sampling using multi-auxiliary information

ABSTRACTThe present work is an attempt to make use of several auxiliary variables at both the occasions for improving the precision of estimates at the current occasion on two occasions of successive sampling. Chain-type ratio estimator has been proposed for estimating the population mean at current occasion in two occasions rotation (successive) sampling. Theoretical properties of the proposed estimator have been investigated. The proposed estimator has been compared with simple mean estimator when there is no matching and with the ratio estimator in successive sampling when information is available on one auxiliary variable on both the occasions. Optimum replacement strategy has also been discussed. Theoretical results have been justified through empirical investigation.

A General Procedure for Estimating Population Variance in Successive Sampling using Fuzzy Tools

This paper de fines a general class of estimators for estimating population variance on current occasion in two occasion successive sampling. Detail behaviors of the proposed class of estimators have been studied and its optimum replacement strategy has also been discussed. The proposed class of estimators has been compared with the sample variance estimator and the results obtained are demonstrated through empirical studies. Categorization of the dominance ranges of the proposed estimation strategies are deployed through defuzzi cation tools which are followed by suitable recommendations.

An improved estimation procedure of population mean in two-occasion successive sampling

ABSTRACTIn this paper an attempt to estimate the current population mean in two-occasion successive sampling has been made. A modified regression-type estimator has been proposed. Optimum replacement strategy of the proposed estimator has been formulated. The proposed estimator is compared with sample mean estimator when there is no matching from the previous occasion and the optimum natural successive sampling estimator. Empirical studies are carried out and suitable recommendations have been made.

Estimation under non response when it occurs on both occasions in two-occasion successive sampling

ABSTRACTThe present paper is an attempt to analyze the effect of non response at both occasions in two-occasion successive sampling. Using the sub-sampling of non respondent technique, exponential type estimators have been proposed to estimate the current population mean. Properties of the proposed estimators are examined and respective optimum replacement strategies are suggested. Empirical studies are carried out to evaluate the performances of the proposed estimators. Results are interpreted and suitable recommendations have been made.

Multivariate Rotation Design for Population Mean in Sampling on Successive Occasions

This article deals with the problem of estimation of the population mean in presence of multi-auxiliary information in two occasion rotation sampling. A multivariate exponential ratio type estimator has been proposed to estimate population mean at current (second) occasion using information on p-additional auxiliary variates which are positively correlated to study variates. The theoretical properties of the proposed estimator are investigated along with the discussion of optimum replacement strategies. The worthiness of proposed estimator has been justified by comparing it to well-known recent estimators that exist in the literature of rotation sampling. Theoretical results are justified through empirical investigations and a detailed study has been done by taking different choices of the correlation coefficients. A simulation study has been conducted to show the practicability of the proposed estimator.

Cost optimization model following extended renewing two-phase warranty

In this paper, we study an extended warranty model under which the customer is offered an additional warranty period after the original two-phase warranty expires. Under the original two-phase warranty, the warranty period is divided into two non-overlapping subintervals, one of which is for replacement warranty, and the other is for minimal repair warranty. If the system failure occurs during the original warranty period, the failed system is either replaced or minimally repaired by the manufacturer, and if the failure occurs during the extended warranty period, only the minimal repair is conducted. For the system failure during the replacement warranty period, the failed system is replaced by a new one, and the warranty term is renewed anew. Following the expiration of extended warranty, the customer is solely responsible for maintaining the system for a fixed length of time period and replaces the system at the end of such a maintenance period. During the maintenance period, only the minimal repair is given for each system failure. Such a maintenance model can be considered as a generalization of several existing maintenance models which can be obtained as special cases. The main purpose of this article is to determine, from the customer’s perspective, the optimal length of maintenance period after the extended warranty expires. As the criterion to determine the optimal replacement strategy, we adopt the expected cost rate per unit time during the life cycle of the system. Given the cost structures incurred during the life cycle of the system, we formulate the expected cost and the expected length of life cycle to obtain the expected cost rate. The uniqueness of optimal solution for the decision variable is verified when the life distribution of the system shows an increasing failure rate. Numerical examples are provided to illustrate the proposed optimal replacement strategy.

A Class of Estimators for Population Median in Two Occasion Rotation Sampling

The present work deals with the problem of estimation of finite population median at current occasion, in two occasion successive (rotation) sampling. A class of estimators has been proposed for the estimation of population median at current occasion, which includes many existing estimators as a particular case. Asymptotic properties including the asymptotic convergence of proposed class of estimators are elaborated. Optimum replacement strategies are also discussed. The proposed class of estimators at optimum condition is compared with the sample median estimator when there is no matching from the previous occasion as well as with some other members of the class. Theoretical results have been justified through empirical interpretation with the help of some natural populations. 2000 AMS Classification: 62D05

Assessment of Exponential Methods of Estimation Under Nonresponse in Two-Occasion Successive Sampling

This article deals with the problem of estimation of current population mean when nonresponse occurs on the current (second) occasion in two-occasion successive sampling. Using the subsampling of nonrespondent technique, exponential-type estimators of current population mean have been proposed and their properties are examined. Optimum replacement strategies for the proposed estimators have been suggested and empirical studies are carried out to assess the performances of the proposed estimators. Results are interpreted and suitable recommendations are made.

On the use of several auxiliary variables in estimation of current population mean in successive sampling

ABSTRACTThe present work intends to put emphasis on the role of several auxiliary variables on both the occasions to improve the precision of estimates at current occasion in two-occasion successive sampling. Utilizing the readily available information on several auxiliary variables on both occasions and the information on study variable from the previous occasion, an efficient estimation procedure of population mean on current occasion has been suggested. Optimum replacement strategy and the efficiencies of the proposed estimator have been discussed. Empirical studies are carried out, and appropriate recommendations have been put forward for practical applications.

Some estimation procedures using a linear model in successive sampling

ABSTRACTIn successive sampling some recent works depict the use of super-population models where information on stable auxiliary variable over occasions has been utilized. Stability character of auxiliary variable may not sustain, if the duration between occasions is large. To cope with such situations, the present work is an attempt to develop some estimation procedures by utilizing the information on two independent auxiliary variables through a linear super-population model. Some estimators are proposed to estimate the current population mean in two occasions successive (rotation) sampling. Optimum replacement strategies are formulated and performances of the proposed estimators have been discussed. Results are interpreted through empirical studies.

Some Effective Rotation Patterns in Estimation of Population Mean in Two-Occasion Successive Sampling

This article is an attempt to explore some effective rotation patterns in estimation of current population mean in two occasions successive sampling. Utilizing the readily available information on an auxiliary variable on both occasions and the information on study variable from the previous occasion, some efficient estimation procedures have been suggested. Optimum replacement strategies and the efficiencies of the proposed estimators have been discussed. Empirical studies are carried out and suitable recommendations are made.

Optimal replacement strategy for stochastic deteriorating system with random wear limit under periodic inspections

In this paper, we examine the preventive maintenance policies for systems/items which are degraded continuously in time and the degree of deterioration that can be observed through periodic inspection. The items will be replaced preventively if the wear process exceeds a limit at periodic inspection or replaced immediately on failure. The limit is assumed to be random in taking individual variation to withstand damages or unmeasurable variables latent to failure into account. Continuous wear process is modeled via a gamma process. We derive an optimal wear limit for preventive replacement so that the long-run total expected cost per unit time is minimized. The proposed method is applied to a problem of block mat inspection for the barrier’s seabed protection.

Risk based integrity modeling of offshore process components suffering stochastic degradation

PurposeThe purpose of this paper is to develop a risk‐based integrity model for the optimal replacement of offshore process components, based on the likelihood and consequence of failure arising from time‐dependent degradation mechanisms.Design/methodology/approachRisk is a combination of the probability of failure and its likely consequences. Offshore process component degradation mechanisms are modeled using Bayesian prior‐posterior analysis. The failure consequences are developed in terms of the cost incurred as a result of failure, inspection and maintenance. By combining the cumulative posterior probability of failure and the equivalent cost of degradations, the operational life‐risk curve is produced. The optimal replacement strategy is obtained as the global minimum of the operational risk curve.FindingsThe offshore process component degradation mechanisms are random processes. The proposed risk‐based integrity model can be used to model these processes effectively to obtain an optimal replacement strategy. Bayesian analysis can be used to model the uncertainty in the degradation data. The Bayesian posterior estimation using an M‐H algorithm converged to satisfactory results using 10,000 simulations. The computed operational risk curve is observed to be a convex function of the service life. Furthermore, it is observed that the application of this model will reduce the risk of operation close to an ALARP level and consequently will promote the safety of operation.Research limitations/implicationsThe developed model is applicable to offshore process components which suffer time‐dependent stochastic degradation mechanisms. Furthermore, this model is developed based on an assumption that the component degradation processes are independent. In reality, the degradation processes may not be independent.Practical implicationsThe developed methodology and models will assist asset integrity engineers/managers in estimating optimal replacement intervals for offshore process components. This can reduce operating costs and resources required for inspection and maintenance (IM) tasks.Originality/valueThe frequent replacement of offshore process components involves higher cost and risk. Similarly, the late replacement of components may result in failure and costly breakdown maintenance. The developed model estimates an optimal replacement strategy for offshore process components suffering stochastic degradation. Implementation of the developed model improves component integrity, increases safety, reduces potential shutdown and reduces operational cost.

Applications of probability model to analyze the effects of electric vehicle chargers on distribution transformers

Society's increased concern over green house gas emission and the reduced cost of electric vehicle technologies has increased the number of electric vehicles (EV) and plug-in hybrid vehicles on the road. Previous studies into the effects of electric vehicles on the electric system have focused on transmission, generation, and the loss of life of distribution transformers. This paper focuses specifically on identifying distribution transformers that are most susceptible to excessive loading due to the implementation of electric vehicles. The authors use a binomial probability model to calculate the probability that a specific distribution transformer will experience excessive loading. Variables to the function include the existing peak transformer demand, number of customers connected to the transformer, and the most common EV charger demand. Also included in the paper is an optimization approach that utilizes the results from the binomial function to determine the optimal replacement strategy to minimize replacement costs. An extension of the approach is also utilized to explore the effectiveness of EV targeted demand side management programs. The authors apply the described algorithms to 75 000 distributions transformers within a distribution system located in Denver, Colorado, USA.