Types Of Maintenance Policies Research Articles

Residual life modeling and maintenance planning for repairable systems

Abstract Accepted by: Phil Scarf This paper formulates a state-dependent mean residual lifetime model for a repairable system operating in a dynamic environment. The problem is addressed by means of a two-state damage process reflecting the effect of operating environment on the system and a repair process associated with the damage process. As the damage process shifts to a higher state, to maintain a minimum level of performance, the decision maker repairs the system at times that arise according to a point process with a constant intensity. We demonstrate the generality of the proposed model and show how existing models emerge as specific cases. Our approach stimulates further research on the determination of two types of maintenance policies: maintenance policy based on the number of imperfect repairs (Model I) and time-based maintenance policy (Model II). In both cases, using the renewal reward theorem argument, we aim at minimizing the long-run average maintenance cost per unit time by determining optimal replacement policies and the optimal level of imperfect repairs. We illustrate the proposed models and carry out a comparative analysis of maintenance policies through numerical examples. The main conclusions drawn are that repair and maintenance policies depend on the failure mechanism, repair frequency and the level of costs involved. Also, numerical comparison shows that the maintenance modelling based on the number of imperfect repairs (model I) outperforms the time-based replacement model (model II) and two baseline models ignoring the effect of operating environment or whose attention is restricted to perfect repair.

Discussion of signature‐based models of preventive maintenance

Discussion of signature‐based models of preventive maintenance

A Study on PF–IFF-Based Diagnosis Model of Plant Equipment Failure

There are two types of maintenance policies for equipment: breakdown maintenance and preventive maintenance. In the case of applying preventive maintenance, the maintenance is carried out based on time or the condition of the equipment. However, with the development of Information and Communications Technologies (ICT) and the Internet of Things (IoT) technology, the data collected from equipment has rapidly increased and the use of Condition-Based Maintenance (CBM) to perform appropriate maintenance based on the condition of the equipment is increasing. In this study, based on gathered sensor data, we introduce an approach to diagnosing the condition of the equipment by extracting specific data features related to the types of failures that occur with equipment. To this end, we used the K-means clustering method, support vector machine (SVM) classifier, and Pattern Frequency–Inverse Failure mode Frequency (PF–IFF) method with the Term Frequency–Inverse Document Frequency (TF–IDF) method. As a case study, we applied the proposed approach to a centrifugal pump and carried out computational experiments for assessing the performance and validity of the proposed approach.

Optimal planning of unpunctual preventive maintenance

ABSTRACTIn traditional maintenance decision-making, maintenance planners assume that their prescribed Preventive Maintenance (PM) policies will be implemented without error. In practice, however, the individuals responsible for implementing such plans often deviate from the intended PM policy, resulting in unpunctual PM actions. We formulate cost-rate minimizing models to investigate the impact of such deviations, assuming that the actual PM time differs from the scheduled PM time in a probabilistic manner. We establish both analytical and numerical results for two specific types of maintenance policies, namely, age replacement with and without minimal repair.

Development of framework for predictive maintenance in Indian manufacturing sector

Every machine degrades with time and requires maintenance. Among all types of maintenance policies, predictive maintenance is established as the best form of maintenance policy as numerous benefits are associated with it. Despite all the benefits, it finds restrictive usage in manufacturing companies. A literature survey reveals that limited funds is the major reason for restrictive usage of predictive maintenance, as predictive maintenance is capital intensive. In this paper, a predictive maintenance framework using predictive maintenance models with no investment on technology component is proposed for Indian manufacturing sector.

Integrated design of preventive maintenance and quality control policy parameters with CUSUM chart

Performance of a production system depends on breakdown-free operation of equipment and processes. Maintenance and quality control play an important role in achieving this goal. This paper presents an integrated model for joint optimization of preventive maintenance and quality control policy with cumulative sum (CUSUM) control chart parameters. Two types of maintenance policies are considered, namely minimal corrective maintenance and imperfect preventive maintenance. The proposed model enables the determination of the optimal value of each of the five decision variables, i.e. sample size (n), sample interval (h), the reference value (K), the decision interval (h 1) and preventive maintenance interval (t PM), that minimize the expected total system cost per unit time. A numerical example is presented to demonstrate the effect of the cost parameters on the integrated design of preventive maintenance and quality control policy. It also compares the system performance employing the proposed integrated approach with that obtained by considering maintenance and CUSUM chart independently. Substantial economic benefit of 19 % is seen in the joint optimization.

Optimization of a network of compressors in parallel: Operational and maintenance planning – The air separation plant case

A general mathematical framework for the optimization of compressors operations in air separation plants that considers operating constraints for compressors, several types of maintenance policies and managerial aspects is presented. The proposed approach can be used in a rolling horizon scheme. The operating status, the power consumption, the startup and the shutdown costs for compressors, the compressor-to-header assignments as well as the outlet mass flow rates for compressed air and distillation products are optimized under full demand satisfaction. The power consumption in the compressors is expressed by regression functions that have been derived using technical and historical data. Several case studies of an industrial air separation plant are solved. The results demonstrate that the simultaneous optimization of maintenance and operational tasks of the compressors favor the generation of better solutions in terms of total costs.

Investigating Imperfect Inspection of Avionics System and its Relationship with Availability Percentage

System maintenance is necessary to prolong the operational life of a system. There are four types of maintenance policies which are corrective, preventive, scheduled and predictive (conditioning based maintenance). However, this paper focuses on preventive maintenance and corrective maintenance policies. In general, the goal of preventive maintenance is to retain the system at its good operating conditions before the occurrence of any failure while corrective maintenance is done as a result of the system’s operating failure. This paper investigates the effects of maintenance activities for Engine Indication and Flight Instruments subsystems of the avionics system of a general aircraft. The simulation of the maintenance process is done using Monte Carlo and Discrete Event simulation methods for different preventive maintenance interval (PMI).

A methodology for simultaneous optimisation of design parameters for the preventive maintenance and quality policy incorporating Taguchi loss function

The performance of a production system depends on the breakdown-free operation of equipment and processes. Maintenance and quality control play an important role in achieving this goal. In addition to deteriorating with time, equipment may experience a quality shift (i.e. process moves to out-of-control state), which is characterised by a higher rejection rate and a higher tendency to fail. This paper develops an integrated model for joint optimisation of preventive maintenance interval and control parameters incorporating the Taguchi loss function. We consider two types of maintenance policies: minimal corrective maintenance that maintains the state of the equipment without affecting the age and imperfect preventive maintenance that upgrades the equipment in between ‘as good as new’ and ‘as bad as old’ condition. The proposed model enables the determination of the optimal value of each of the four decision variables, i.e. sample size (n), sample frequency (h), control limit coefficient (k), and preventive maintenance interval (t PM) that minimises the expected total cost of the integration per unit time. A numerical example is presented to demonstrate the effect of the cost parameters on the joint economic design of preventive maintenance and process quality control policy. The sensitivity of the various parameters is also examined.

Stochastic analysis of shock process and modeling of condition-based maintenance

The paper presents an analytical formulation for evaluating the maintenance cost of engineering systems that are damaged by shocks arriving randomly in time. The damage process is nonlinear in a sense that damage increments form an increasing sequence (i.e., accelerated damage) or a decreasing sequence (saturated damage) of random increments. Such processes are motivated from damage data collected from nuclear reactor components. To model the nonlinear nature of damage process, the paper proposes the use of non-homogeneous Poisson process for damage increments, which is in contrast with the common use of a renewal process for modeling the damage. The paper presents a conceptually clear and comprehensive derivation of formulas for computing the expected cost rate associated with a periodic inspection and preventive maintenance policy. Distinctions between the analysis of self-announced and latent failures are highlighted. The analytical model presented in this paper is quite generic and versatile, and it can be applied to optimize other types of maintenance policies.

A hybrid maintenance model with imperfect inspection for a system with deterioration and Poisson failure

A new maintenance model for a system with both deterioration and Poisson failures is proposed. In this model, at any time-instant GS and when the system is operating, one of the following decisions may be taken: (1) stop the system to perform a scheduled minimal maintenance; (2) stop the system to perform an inspection; and (3) no action and allow the system to go on with its operation. Following an inspection, based on the deterioration condition of the system, one of the following decisions may be taken: (a) if the system is in a ‘good’ condition, no maintenance action is taken and a number of periodic minimal maintenance activities are scheduled, starting T1 later; (b) if the system is in an ‘intermediate’ condition, a minimal maintenance is performed and an inspection is scheduled for T2 later (T2 < T1); and (c) if the system is in a ‘bad’ condition, a major maintenance is performed and a number of periodic minimal maintenances are scheduled, starting T1 later. In addition, a deterioration failure is restored by a major repair and a Poisson failure is restored by a minimal repair. Generalised stochastic Petri nets are used to represent and analyse the model, which represents a ‘composite’ maintenance strategy. Based on maximisation of the throughput of the system the benefit of this model compared to (1) an equivalent periodic inspection model and (2) an equivalent planned scheduled maintenance model, is demonstrated. This study presents a new hybrid model with a general framework for incorporating various types of maintenance policies. Also by incorporation of a number of features, this model will be more applicable to real world technical systems (complex systems), although it can be applied to individual components that are part of a complex system.

Evaluation of Maintenance Policies using Markov Chains and Fault Tree Analysis

Reliability analyses of multi-component systems can often be refined by combining Markov-chain models for detailed component characterizations with fault-tree evaluation techniques for describing over-all system behavior. A difficulty encountered in the application of this combined approach is that component maintenance policies can induce statistical dependence among component failures. Thereby, straightforward evaluation of overall system characteristics based upon the assumption of statistically independent component failures can lead to erroneous conclusions. This paper examines the effect of dependent component failures, as induced by the component maintenance policies, on system performance; and it demonstrates that for certain types of maintenance policies (when component maintenance is independent of the condition of the other system components), meaningful results can be obtained by assuming the independence of component failures. The feasibility of the proposed approach is illustrated through a maintenance scheduling problem in nuclear engineering practice.