Imperfect maintenance model for estimating aircraft fleet availability

2017 ◽  
Vol 89 (2) ◽  
pp. 338-346 ◽  
Author(s):  
Aleksandar Knezevic ◽  
Ljubisa Vasov ◽  
Slavisa Vlacic ◽  
Cedomir Kostic

Purpose The purpose of this paper is to define conditions under which improved availability of fleet of G-4 jet trainers is obtained, and optimization of intermediate-level maintenance through imperfect maintenance model application. This research has been conducted based on available knowledge, and experience gained by performing intermediate-level maintenance of Serbian Air Force aircrafts. Design/methodology/approach Analysis of the data collected from daily maintenance reports, and the analysis of maintenance technology and organization, was performed. Based on research results, a reliability study was performed. Implementation of imperfect maintenance with its models of maintenance policies (especially a quasi-renewal process and its treating of reliability and optimal maintenance) was proposed to define new maintenance parameters so that the greater level of availability could be achieved. Findings The proposed methodology can potentially be applied as a simple tool to estimate the present maintenance parameters and to quickly point out some deficiencies in the analyzed maintenance organization. Validation of this process was done by conducting a reliability case study of G-4 jet trainer fleet, and numerical computations of optimal maintenance policy. Research limitations/implications The methodology of the availability estimation when reliability parameters were not tracked by the maintenance organization, and optimization of intermediate-level maintenance, has so far been applied on G-4 jet trainers. Moreover, it can be potentially applied to other aircraft types. Originality/value Availability estimation and proposed optimization of intermediate maintenance is based on a survey of data for three years of aircraft fleet maintenance. It enables greater operational readiness (due to a military rationale) with possible cost reduction as a consequence but not as a goal.

2014 ◽  
Vol 25 (3) ◽  
pp. 415-435 ◽  
Author(s):  
Siew-Hong Ding ◽  
Shahrul Kamaruddin ◽  
Ishak Abdul Azid

Purpose – An optimal maintenance policy is key to the improvement of the availability and reliability of a system at an acceptable level without a significant increase in investment. However, the selection process is a complicated task because it requires in-depth knowledge on maintenance policies and on the technical requirements of maintenance. The difficulties and complexity of the selection process arise from the combination of conflicting maintenance constraints such as available spares, size of workforce, and maintenance skills. The paper aims to discuss these issues. Design/methodology/approach – The proposed maintenance policy selection (MPS) model is separated into three major phases. The first phase identifies the critical system (CS) based on failure frequency. The failure mechanism in the CS is then analyzed by using a failure mode and effect analysis in the second phase. In the third phase, a multi-criteria decision making method, called the technique for order of preference by similarity to ideal solution, is adopted to identify an optimal maintenance policy that can minimize the failures. Findings – Through a case study, preventive maintenance was selected as the optimal maintenance policy for the reduction of system failures. The results obtained from the case study not only provide evidence of the feasibility and practicability of the developed model, but also test the acceptability and rationale of the developed model from the industry perspective. Valuable knowledge and experience from employees were extracted and utilized through the proposed model to rank the optimal maintenance policy based on the capability to reduce failure. Originality/value – The practicality of the MPS model is justified through an implementation in the palm oil industry. The application of the MPS model can also be extended to other manufacturing industries.


Author(s):  
Qingan Qiu ◽  
Baoliang Liu ◽  
Cong Lin ◽  
Jingjing Wang

This paper studies the availability and optimal maintenance policies for systems subject to competing failure modes under continuous and periodic inspections. The repair time distribution and maintenance cost are both dependent on the failure modes. We investigate the instantaneous availability and the steady state availability of the system maintained through several imperfect repairs before a replacement is allowed. Analytical expressions for system availability under continuous and periodic inspections are derived respectively. The availability models are then utilized to obtain the optimal inspection and imperfect maintenance policy that minimizes the average long-run cost rate. A numerical example for Remote Power Feeding System is presented to demonstrate the application of the developed approach.


Author(s):  
Yunyi Kang ◽  
Feng Ju

In this work, we develop preventative maintenance policies on two-machine-and-one-buffer production systems with machines subject to multi-stage degradation. Condition-based maintenance policies are generated for both machines, with consideration on both the machine degradation stages and the buffer level. Moreover, the policies are flexible, allowing a machine to be recovered to any better operating state, while merely recovering to the best operating state is possible in many previous work. A Markov decision model is formulated to find the optimal maintenance policy and computational experiments show that the policies improve the performance of a system in finite production runs.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huthaifa AL-Smadi ◽  
Abobakr Al-Sakkaf ◽  
Tarek Zayed ◽  
Fuzhan Nasiri

PurposeThe purpose of this study is to minimize cost and minimize building condition. Weibull distribution approach was employed to generate deterioration curves over time. The third floor of Concordia University’s Engineering And Visual Arts (EV) Complex in Montreal, Canada, served as a case study to test the maintenance model and determine the optimal maintenance activities to be performed.Design/methodology/approachThis research has demonstrated that there is insufficient fund allocation for the maintenance of non-residential buildings. Therefore, this research focused on designing and developing a maintenance optimization model that provides the type of spaces (architectural system) in a building. Sensitivity analysis was used to calculate weights to validate the model. Particle swarm optimization, based explicitly on multiple objectives, was applied for the optimization problem using MATLAB.FindingsFollowing 100 iterations, 13 non-dominant solutions were generated. Not only was the overall maintenance cost minimized, but the condition of the building was also maximized. Moreover, the condition prediction model demonstrated that the window system type has the most rapid deterioration in educational buildings.Originality/valueThe model is flexible and can be modified by facility managers to align with the required codes or standards.


2014 ◽  
Vol 20 (2) ◽  
pp. 98-121 ◽  
Author(s):  
Hasnida Ab-Samat ◽  
Shahrul Kamaruddin

Purpose – This paper reviews the literature on opportunistic maintenance (OM) as new advance maintenance approach and policy. The purpose of this paper is to conceptually identify common principle and thereby provide absolute definition, concept and characteristics of this policy. Design/methodology/approach – A conceptual analysis was conducted on various literatures to clarify a number of principle and concepts as a method for understanding information on OM. The analysis involves the process of separating the compound terms used in the literatures into a few parts, analyse them and then recombining them to have more clear understanding of the policy. Findings – The paper discussed the maintenance approach, genealogy, principle, concept and applications of OM both in numerical analysis and real industry. OM policy is developed based on combination of age replacement policy and block replacement policy and in practical; OM is applied as the combination of corrective maintenance which is applied when any failure occurred, with preventive maintenance (PM) – a planned and scheduled maintenance approach to prevent failure to happen. Any machine shutdown or stoppages due to failure is the “opportunity” to conduct PM even though it is not as planned. The characterization of OM was provided in order to present its theoretical novelty for researchers and practical significance for industries. Practical implications – To date, there is no publication that reviews the OM in-depth and provides clear understanding on the topic. Therefore, this paper aims to show lineage of OM and the current trend in researches. This discussion will pave the way of new research areas on this optimal maintenance policy. Clear definition and principle of OM provided in this paper will trigger interest in its practicality as well as aid industries to understand and conduct OM in operation plant. Originality/value – This paper discussed the available literature about OM in various perspectives and scopes for further understanding of the topic by maintenance management professionals and researchers. Therefore, OM can be widely studied and applied in real industry as it is an effective and optimal maintenance policy.


2019 ◽  
Vol 26 (1) ◽  
pp. 129-165
Author(s):  
Hasnida Ab-Samat ◽  
Shahrul Kamaruddin

Purpose Opportunistic maintenance (OM) policy is a prospective maintenance approach that instigates for a more effective and optimized system. The purpose of this paper is to provide the steps and methods used in model development processes for the application of the OM policy. Design/methodology/approach Dubbed as opportunistic principle toward optimal maintenance system (OPTOMS) for OM policy toward optimal maintenance system, the model is devised as a decision support system model and contains five phases. The motivation and focus of the model resolve around the need for a practical framework or model of maintenance policy for the application in an industry. In this paper, the OPTOMS model was verified and validated to ensure that the model is applicable in the industry and robust as a support system in decision making for the optimal maintenance system. Findings From the verification steps conducted in a case study company, it was found that the developed model incorporated simple but practical tools like check sheet, failure mode and effect analysis (FMEA), control chart that has been commonly used in the industry. Practical implications This paper provides the general explanations of the developed model and tools used for each phase in implementing OM to achieve an optimal maintenance system. Based on a case study conducted in a semiconductor company, the OPTOMS model can align and prepare the company in increasing machine reliability by reducing machine downtime. Originality/value The novelty of this paper is based on the in-depth discussion of all phases and steps in the model that emphasize on how the model will become practical theories in conducting an OM policy in a company. The proposed methods and tools for data collection and analysis are practical and commonly used in the industry. The framework is designed for practical application in the industry. The users would be from the Maintenance and Production Department.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Garima Sharma ◽  
Rajiv Nandan Rai

PurposeDegradation of repairable components may not be similar after each maintenance activity; thus, the classic (traditional-time based) maintenance policies, which consider preventive maintenance (PM), age-based maintenance and overhauls to be done at fixed time interval, may fail to monitor the exact condition of the component. Thus, a progressive maintenance policy (PMP) may be more appropriate for the industries that deal with large, complex and critical repairable systems (RS) such as aerospace industries, nuclear power plants, etc.Design/methodology/approachA progressive maintenance policy is developed, in which hard life, PM scheduled time and overhaul period of the system are revised after each service activity by adjusting PM interval and mean residual life (MRL) such that the risk of failure is not increased.FindingsA comparative study is then carried out between the classic PM policy and developed PMP, and the improvement in availability, mean time between failures and reduction in maintenance cost is registered.Originality/valueThe proposed PMP takes care of the equipment degradation more efficiently than any other existing maintenance policies and is also flexible in its application as the policy can be continuously amended as per the failure profile of the equipment. Similar maintenance policies assuming lifetime distributions are available in the literature, but to ascertain that the proposed PMP is more suitable and applicable to the industries, this paper uses Kijima-based imperfect maintenance models. The proposed PMP is demonstrated through a real-time data set example.


Author(s):  
GWO-LIANG LIAO ◽  
BOR-LING SHAW

This work presents a periodic preventive maintenance (PM) model for a repairable system that undergoes minimal repair or delayed repair at each failure to keep a plant operating. Two PM types are performed, i.e. imperfect PM and perfect PM. The likelihood that PM is perfect depends on the number of imperfect maintenance activities have been performed since the last renewal cycle. Mathematical formulae for expected cost per unit time are developed. The optimal period for periodic PM, which minimizes cost, is identified. Various special cases are considered, including the maintenance learning effect. A numerical example demonstrates the effectiveness of the proposed model.


2009 ◽  
Vol 2009 ◽  
pp. 1-43 ◽  
Author(s):  
Ushio Sumita ◽  
Jia-Ping Huang

The class of counting processes constitutes a significant part of applied probability. The classic counting processes include Poisson processes, nonhomogeneous Poisson processes, and renewal processes. More sophisticated counting processes, including Markov renewal processes, Markov modulated Poisson processes, age-dependent counting processes, and the like, have been developed for accommodating a wider range of applications. These counting processes seem to be quite different on the surface, forcing one to understand each of them separately. The purpose of this paper is to develop a unified multivariate counting process, enabling one to express all of the above examples using its components, and to introduce new counting processes. The dynamic behavior of the unified multivariate counting process is analyzed, and its asymptotic behavior ast→∞is established. As an application, a manufacturing system with certain maintenance policies is considered, where the optimal maintenance policy for minimizing the total cost is obtained numerically.


2009 ◽  
Vol 26 (06) ◽  
pp. 831-847 ◽  
Author(s):  
J. H. PARK ◽  
S. C. LEE ◽  
J. W. HONG ◽  
C. H. LIE

A block preventive maintenance (PM) policy for a multi-unit system composed of identical units is investigated in this paper. The block PM model of this paper considers periodic inspection and periodic imperfect maintenance. The imperfect maintenance effects are formulated using improvement factor and age reduction model. We define variables of maintenance policy as the inspection period and the PM period and obtain an optimal maintenance policy which minimizes the average total cost. A numerical example is presented, and some sensitivity analyses for model parameters are also investigated.


Sign in / Sign up

Export Citation Format

Share Document