Repair Duration Research Articles

Identification of Unit Replacement Based on Long-Run Repair Average Cost Rate (Acr) Based on Truncated Exponential Failure Model

Earlier, authors presented [1] and published [2] investigated failure nature, repair pattern and reliabilities of hydro power generators, using simple statistical tools and simulation techniques respectively. It is identified that analysis of hydro power generators require a special approach by dividing the repair into two categories based on the repair duration. That is i) Minor repairs (Repair hours less than or equal a threshold value T) and ii) Major Repairs (Repair hours greater than a threshold value T).This approach is specially introduced by authors [1, 2] and obtained good fit of “truncated exponential failure model”. Through this proposed model reliabilities are estimated and conclusions were drawn. In the above work, we have assumed that the system after repair is ‘as good as new’. On the basic assumption that the system after repair is not ‘as good as new’ and also the successive working times are stochastically decreasing while, the successive repair time's are stochastically increasing and are exposing to exponential truncated failure law. Under these assumptions, an optimal replacement policy T in which we replace the system when the repair time (working time) reaches T. It can be determined that an optimal repair replacement policy T* such that the long run average cost per unit time is minimized. It can also be derived an explicit expression of the long-run average cost and the corresponding optimal replacement policy T* can be determined analytically. Numerical results are provided to support the theoretical results.

Some Remarks on the Asymptotic Behavior of the Empirical Availability Function

We consider the asymptotic behavior of the empirical availability function, which is an important reliability characteristic of technical, communication, information, or transport systems. Our main focus is the case of violation of the classical assumptions of homogeneity of failure flow or the existence of the expectation of failure-free performance or repair duration. Both the classical situation dealing with samples with nonrandom size and the situation where the number of available observations is unknown beforehand, that is, the sample size is random, are considered. In a special situation where the sample size has a negative binomial distribution, an analogue of the law of large numbers is proved for random sums of not necessarily identically distributed random variables describing conditions for the convergence of the distributions of negative binomial random sums to generalized gamma distributions. Thus, a simple limit scheme is proposed, within which generalized gamma distributions turn out to be...

Design of Advanced Power Distribution Networks Including DGs and D-FACT Devices

This paper presents an application of a multi-objective seeker-optimization-algorithm (MOSOA) for solving multi-objective design of advanced power distribution systems (PDS) considering fixed cost, non-linear variable cost and reliability as the objective functions including DGs (distributed generations) and D-FACT (distribution-FACT) devices. The proposed planning methodology uses contingency-load-loss index (CLLI) for reliability evaluation, which is independent of failure rate and fault repair duration of the feeder branches. To enhance the reliability and efficiency of existing PDS, planning strategy includes distribution automation devices such as automatic recloser (RA). Performance of the proposed approach is assessed and illustrated on a 54-bus PDS, considering real-time design practices. Furthermore, a qualitative comparison is made with NSGA-II, showing the efficacy of the proposed planning approach.

Implementation of multi-objective seeker-optimization-algorithm for optimal planning of primary distribution systems including DSTATCOM

Abstract This paper develops an approach based on a multi-objective seeker-optimization-algorithm (MOSOA) for designing of an advanced power distribution system (PDS) including distribution static compensator (DSTATCOM). The proposed planning methodology uses a contingency-load-loss index (CLLI) for reliability evaluation, which is independent of the failure rate and fault repair duration of the feeder branches, which is difficult to obtain in practice. To enhance the reliability and operation efficiency of the conventional power distribution system, the proposed approach includes distribution automation devices such as automatic reclosers (RAs) in the planning strategy. The proposed study simultaneously obtains the optimal placement and sizing of the DSTATCOM in reactive power compensation for system voltage control to avoid the voltage violation problem. The effectiveness of the proposed algorithm is tested on a 54-bus distribution system, considering real-time design practices. The information gained from the pareto-optimal solution is shown to be useful for final decision making of a PDS. Furthermore, a qualitative comparison is made with NSGA-II, showing the efficiency of the proposed planning approach. The presented results show the accuracy and efficiency of the proposed method.

Reliability of Erasure Coded Storage Systems: A Combinatorial-Geometric Approach

We consider the probability of data loss, or equivalently, the reliability function for an erasure coded distributed data storage system under worst case conditions. Data loss in an erasure coded system depends on probability distributions for the disk repair duration and the disk failure duration. In previous works, the data loss probability of such systems has been studied under the assumption of exponentially distributed disk failure and disk repair durations, using well-known analytic methods from the theory of Markov processes. These methods lead to an estimate of the integral of the reliability function. Here, we address the problem of directly calculating the data loss probability for general repair and failure duration distributions. A closed limiting form is developed for the probability of data loss and it is shown that the probability of the event that a repair duration exceeds a failure duration is sufficient for characterizing the data loss probability. For the case of constant repair duration, we develop an expression for the conditional data loss probability given the number of failures experienced by a each node in a given time window. We do so by developing a geometric approach that relies on the computation of volumes of a family of polytopes that are related to the code. An exact calculation is provided and an upper bound on the data loss probability is obtained by posing the problem as a set avoidance problem. Theoretical calculations are compared to simulation results.

A knowledge-based evolutionary proactive scheduling approach in the presence of machine breakdown and deterioration effect

This paper considers proactive scheduling in response to stochastic machine breakdown under deteriorating production environments, where the actual processing time of a job gets longer along with machine's usage and age. It is assumed that a job's processing time is controllable by allocating extra resources and the machine breakdown can be described using a given probability distribution. If a machine breaks down, it needs to be repaired and is no longer available during the repair. To absorb the repair duration, the subsequent unfinished jobs are compressed as much as possible to match up the baseline schedule. This work aims to find the optimal baseline sequence and the resource allocation strategy to minimize the operational cost consisting of the total completion time cost and the resource consumption cost of the baseline schedule, and the rescheduling cost consisting of the match-up time cost and additional resource cost. To this end, an efficient multi-objective evolutionary algorithm based on elitist non-dominated sorting is proposed, in which a support vector regression (SVR) surrogate model is built to replace the time-consuming simulations in evaluating the rescheduling cost, which represents the solution robustness of the baseline schedule. In addition, a priori domain knowledge is embedded in population initialization and offspring generation to further enhance the performance of the algorithm. Comparative results and statistical analysis show that the proposed algorithm is effective in finding non-dominated tradeoff solutions between operational cost and robustness in the presence of machine breakdown and deterioration effect.

Multi‐objective design of advanced power distribution networks using restricted‐population‐based multi‐objective seeker‐optimisation‐algorithm and fuzzy‐operator

This study proposes a method for designing advanced power distribution system (PDS) including distributed generations, using a combination of fundamental loop generator and multi-objective seeker-optimisation algorithm (MOSOA). The proposed approach reduces the searching space using fundamental loop generator technique to obtain initial feasible solutions which is further improved by SOA to generate new set of solutions with improved aptitude. The proposed methodology uses a contingency-load-loss-index for reliability evaluation, which is independent of the estimation of failure rate and fault repair duration of feeder branches. This planning strategy includes distribution automation devices such as automatic reclosers (RAs) to enhance the reliability of PDS. The proposed algorithm generates a set of non-dominated solution by simultaneous optimisation of two conflicting objectives (economic cost and system reliability) using Pareto-optimality-based trade-off analysis including a fuzzy-operation to automatically select the most suitable solution over the Pareto-front. The performance of the proposed approach is assessed and illustrated on 54-bus and 100-bus PDS, considering realtime design practices. Extensive comparisons are made against some well-known and efficient MO algorithms such as fast non-dominated sorting genetic algorithm-II, MO particle- swarm-optimisation and MO immunised-particleswarm-optimisation. Simulation results show that the proposed approach is accurate and efficient, and a potential candidate for large-scale PDS planning.

A stochastic alternating renewal process model for unavailability analysis of standby safety equipment

The paper presents a stochastic approach to analyze instantaneous unavailability of standby safety equipment caused by latent failures. The problem of unavailability analysis is formulated as a stochastic alternating renewal process without any restrictions on the form of the probability distribution assigned to time to failure and repair duration. An integral equation for point unavailability is derived and numerically solved for a given maintenance policy. The paper also incorporates an age-based preventive maintenance policy with random repair time. In case of aging equipment, the asymptotic limit or average unavailability should be used with a caution, because it cannot model an increasing trend in unavailability as a result of increasing hazard rate (i.e. aging) of the time to failure distribution.

Design of an advanced electric power distribution systems using seeker optimization algorithm

The power distribution network design problem has a growing impact on secure and economical operation of distribution power system. This issue is well known as a non-linear, multi-modal and multi-objective optimization problem where global optimization techniques are required in order to avoid local minima. In this study, a new approach using seeker optimization algorithm (SOA) is proposed for distribution system planning problem with simultaneous placement of automatic reclosers (RAs), considering total system economic cost, overall system reliability, system power losses and voltage deviations as an objective functions. Normally, conventional power distribution systems (CPDS) are radial in nature and momentary fault in the system causes large area of the grid to be blacked out, which leads to huge load interruptions. Reliable distribution system minimize this effect by allowing faults to clear themselves by protection device operations such as automatic reclosers (RAs) and quickly restores the power through system reconfiguration by minimizing the loads affected. Thus, in order to prevent the system from momentary faults, simultaneous placement of RAs has been also done which leads to a design of an advanced power distribution system (APDS). Thus, the reliability issues are of major importance for effective planning of an APDS. For evaluation of reliability measure, the contingency-load-loss index (CLLI) is assessed in this paper, which is independent of the failure rate and fault repair duration of the feeder branches. The performance of the proposed algorithm is extensively assessed and comparisons are made with Particle Swarm Optimization (PSOs), Genetic Algorithm (GA) and graph theoretical approach (GTA) applied on the 54 and 100-bus primary power distribution systems. The simulation results show that the proposed approach performed better than the other listed algorithms and can be efficiently used for the optimal design of an advanced power distribution system.

Operation study of different structural options of flexible flows for car repair using simulation modeling

Purpose. The article is aimed to improve the methods of car repair organization using the search of rational structures of flexible flows. Methodology. For operation analyses of the car repair flows the simulation modeling was used. The initial data for random value generation of cars repair duration are the statistical data. They were collected at the existing car repair enterprises. Findings. Obtained results show that at the same amount of modules the flexible repair flow is more efficient. Flexible flow increases the working capacity, improves the removal of cars from one module and reduces car detention time in repair. Originality. There were identified the mechanisms, which allow establishing links between the different structural variants of flexible flow and their operational performance. Concrete data that give a fresh look to the organization of car repair production were obtained. Practical value. These results can be used in designing the new perspective enterprises for car repair and also under reconstruction or expansion of existing enterprises in order to transfer them to the flexible flow. It is recommended to incorporate the obtained results and try to put them into production during designing and construction of new car enterprises.

Markov-Based Maintenance Planning Considering Repair Time and Periodic Inspection

The equipment degradation and various maintenance decision processes with unreliable machines have been studied extensively. The traditional degradation modeling using Markov process only focuses on single machine system and ignores maintenance or repair duration. This paper is devoted to analytical and numerical study of production lines within the Markov process framework considering repair time and periodic inspection. Nonexponential holding time distributions in Markov chain are approximated by inserting multiple intermediate states based on a phase-type distribution. Overall system availability is calculated by recursively solving the balance equations of the Markov process. The results show that the optimal inspection intervals for two repairable-machine systems can be achieved by means of the proposed method. By having an adequate model representing both deterioration and maintenance processes, it is also possible to obtain different optimal maintenance policies to maximize the availability or productivity for different configurations of components.

Modeling transit vehicle repair duration and active service time

The need for dependable and flexible models of transit vehicle maintenance has been well established in the literature as a means for improving daily operations, capital planning and service quality. Stemming from the practical need to predict the duration of maintenance activities and active service time for buses, this paper uses the principles of duration modeling to address two important questions: what is the duration of vehicle maintenance activities and, given that a bus is in active service, how long will it take? We extend previous work by including exogenous factors directly affecting maintenance duration and active service time in fully parametric duration models and examine such activities for the transit system in Athens (Greece). Results indicate that vehicle age, kilometers travelled and repair type are amongst the most important determinants of maintenance duration.

Full-Scale Field Testing for Injected Foam Stabilization of Portland Cement Concrete Repairs

A series of foam-injected repairs was performed on a portland cement concrete (PCC) test section at the U.S. Army Engineer Research and Development Center. Repairs consisted of uncompacted backfill overlaid by a 9-in. rapid-setting cementitious cap. A series of injection tubes was inserted through the cap into the uncompacted debris backfill, and a two-component rigid polyurethane foam was injected into this backfill. The test matrix compared the performance of three different repairs using various volumes of injected foam. A fourth repair was constructed without injected foam as a control item. Three hours after cap construction, the repairs underwent simulated aircraft traffic with an F-15E load cart. The performance of the four repairs was measured by passes to failure. The results of traffic testing were used to evaluate foam-injection technology for rapid repair of PCC pavements. The performances of foam-injected repairs were also compared with poured foam and traditional full-depth backfill repairs, each capped with rapid-setting materials. Comparisons were made about pavement performance, costs, and total duration required for installing the repair. Results showed that injection of excessive foam was detrimental to the repair surface, because it induced cracking before traffic application, and could lead to premature development of foreign object damage. However, repairs using moderate amounts of foam and pure backfill sustained the required traffic levels, defined by the research sponsor, of 200 passes within 4 h of initiating the pavement repair. For cost and repair duration, those repairs that did not include foam were more effective.

Correspondence analysis of repair data: a case study for electric cable shovels

In mining operation, effective maintenance scheduling is very important because of its effect on the performance of equipment and production costs. Classifying equipment on the basis of repair durations is considered one of the essential works to schedule maintenance activities effectively. In this study, repair data of electric cable shovels used in the Western Coal Company, Turkey, has been analyzed using correspondence analysis to classify shovels in terms of repair durations. Correspondence analysis, particularly helpful in analysing cross-tabular data in the form of numerical frequencies, has provided a graphical display that permitted more rapid interpretation and understanding of the repair data. The results indicated that there are five groups of shovels according to their repair duration. Especially, shovels numbered 2, 3, 7, 10 and 11 required a repair duration of<1 h and maintained relatively good service condition when compared with others. Thus, priority might be given to repair them in maintenance job scheduling even if there is another failed shovel waiting to be serviced. This type of information will help mine managers to increase the number of available shovels in operation.

Development of simulation and optimization platform to analyse maintenance policies performances for manufacturing systems

In this paper, a new approach that integrates the optimization algorithms and the simulation methods is proposed to analyse maintenance strategies performances for manufacturing systems in which operating characteristics deteriorate with use and whose lifetime and repair duration are random. The simulation language RAO (resource–action–operation) is used to implement the proposed approach. Numerical examples are carried out to validate the approach flexibility and efficiency. RAO is a discrete events simulator. This tool proposes a great flexibility of modeling, that allows one to keep track of each resource's evolution and even offers animation possibilities. By exploiting the characteristic of RAO, a new simulation and optimization platform of maintenance policies is presented.

Supply disruptions with time-dependent parameters

We consider a firm that faces random demand and receives shipments from a single supplier who faces random supply. The supplier's availability may be affected by events such as storms, strikes, machine breakdowns, and congestion due to orders from its other customers. In our model, we consider a dynamic environment: the probability of disruption, as well as the demand intensity, can be time dependent. We model this problem as a two-dimensional non-homogeneous continuous-time Markov chain (CTMC), which we solve numerically to obtain the total cost under various ordering policies. We propose several such policies, some of which are time dependent while others are not. The key question we address is: How much improvement in cost is gained by using time-varying ordering policies rather than stationary ones? We compare the proposed policies under various cost, demand, and disruption parameters in an extensive numerical study. In addition, motivated by the fact that disruptions are low-probability events whose non-stationary probabilities may be difficult to estimate, we investigate the robustness of the time-dependent policies to errors in the supply parameters. We also briefly investigate sensitivity to the repair–duration distribution. We find that non-stationary policies can provide an effective balance of optimality (low cost) and robustness (low sensitivity to errors).

Underwater Wet Repair Welding and Strength Testing on Pipe-Patch Joints

The underwater wet welding method for repairing of submerged structural members has been intensively developed during the last years. It is an economical and especially more time-independent procedure. The shortened repair duration is a major advantage in regions with rough sea climate as the North Sea area. During research projects the weldability and fatigue performance of pipe-patch connections have been tested. These joints are in use for repairing of collision indents. The shape of the actual used repair patch was optimized to the requirements of underwater wet welding at high tensile strength steels as BS4360 Gr 50D. Steel materials in this grade show problems in regard to high hydrogen susceptibility, and therefore cold cracking. The fatigue behavior of the patch-welded pipe structural member has been investigated. First test series were carried out using as-welded joints. In a second part of the project, post-weld-treated connections were tested. The weld seams on these joints were partially ground or hammer peened. The test results have been evaluated by means of the hot-spot concept and then faced with actual code requirements. Extensive strain gage measurements and finite-element calculations have been carried out to provide the stress state in the structural details.

Dynamic Scheduling of a Robot Servicing Machines on a One-Dimensional Line

Abstract We examine the operation of a single robot servicing a finite set of machines lined up in succession. Each machine operates for a random time, gets blocked (or fails), waits for the robot, waits for the repair duration, starts operating again, and so on. We seek a dynamic decision rule which at any time, depending on the state of the whole system, will decide what action the robot should take: to repair the machine in front of it, or to move left or right, or to stop and wait. The objective is to maximize the average number of operating machines, over an infinite horizon. This problem arises in die practical context of a textile winding process. We model this system as a Markov Renewal Decision Process, and present a computational approach, based on dynamic programming, to approximate an optimal decision policy, under the assumption of exponential times to failure. We consider the case in which the robot can stop and change direction anywhere, and the case where the robot can stop or change direc...

Contents of volume 17

The paper presents a stochastic approach to analyze instantaneous unavailability of standby safety equipment caused by latent failures. The problem of unavailability analysis is formulated as a stochastic alternating renewal process without any restrictions on the form of the probability distribution assigned to time to failure and repair duration. An integral equation for point unavailability is derived and numerically solved for a given maintenance policy. The paper also incorporates an age-based preventive maintenance policy with random repair time. In case of aging equipment, the asymptotic limit or average unavailability should be used with a caution, because it cannot model an increasing trend in unavailability as a result of increasing hazard rate (i.e. aging) of the time to failure distribution.

Reliability of Systems with Limited Repairs

Reliability is the probability that a system functions according to specifications over a given period of time. During this period, system specifications may allow failures and repairs to occur. This paper considers systems with specifications which limit the repair process. Such systems place a limitation on either the repair duration or the number of repairs. For example, a system controlling a real-time process may go down, be repaired, and continue proper control as long as the repair duration does not exceed a specified bound. Otherwise, the system fails. We model and analyze systems with three different types of limited repairs: 1) Bounded repair time, 2) Bounded cumulative repair time, and 3) Bounded number of repairs. Examples of such models exist in real-time process control, shock models, transaction processing, and maintenance models. For each of the three types of systems with limited repairs, we derive the distributions and the mean values of the system lifetime, the cumulative operational time, and the largest continuous operational time before a complete system failure. We also consider the execution of a task on such systems. The task is preempted upon the occurence of a failure, and is resumed or repeated after repair. The probability of completion of a task with a given work requirement in the three limited downtime scenarios is derived. We study the effect of preemptive-resume versus preemptive-repeat failures on the probability of task completion.