مطالعه ای در محوریت دسترسی تعمیر و نگهداری پیشگیرانه برای سیستم های چند مؤلفه ای

This paper studies preventive maintenance (PM) in simultaneously considering three actions, mechanical service, repair and replacement for a multi-components system based on availability. Mechanical service denotes the activities including lubricating, cleaning, checking and adjusting, etc. which is set to alleviate strength degradation. Repair is defined on that not only slow down the degraded velocity but also restore the degraded strength partly. Replacement is settled to recover a component to its original condition. According to the definitions, the degradation of components is analyzed from its failure mechanisms and the improvements of various actions to it in reliability were measured by using two improved factors. Following the proposed model of reliability, the mean-up and mean-down times of each component are also investigated and the replacement intervals of components are determined based on availability maximization. Here, the minimum one among the intervals is chosen as the PM interval of system for programming the periodical PM policy. The selection of action for the components on every PM stage is decided by maximizing system benefit in maintenance. Repeatedly, the scheduling is progressed step by step and is terminated until the system extended life reaching to its expected life. The complete schedule provides the information, the actions adopted for the components, the availability and the total cost of system on each stage. Validly, a multi-components system is used as an example to describe the proposed algorithm.

To keep a system in normal condition, taking proper maintenance becomes even more important during its serviced life. According to the studies reported in past, maintenance was classified into two categories, corrective maintenance (CM) and preventive maintenance (PM) [1]. Normally, PM is more effective than CM because it is always to keep a system in an available condition so that the large loss caused by unpredictable fails can be avoided. Aiming to PM policy, preventive replacement is a topic frequently discussed. For example, Jayabalan and Chaudhuri [2] developed a branching algorithm with effective dominance rules to determine the number of maintenance interventions before each replacement. Aven and Dekker [3] presented a general framework including various age and block replacement models for the optimization of replacement times. Zheng [4] proposed an opportunity-triggered replacement model to allow joint replacements for multiple-unit systems. Legat et al. [5] determined the optimal interval for PM/replacement using either an age-based or diagnostic-based renewal strategy. Wang et al. [6] proposed a scheduled method of preventive replacement for the key components of mechanical systems. Moreover, Vaurio [7] investigated the time-dependent unavailability of periodically tested aging components under different testing and repair policies, and then decided the time intervals in periodic testing and scheduled maintenance. In particular, combining the expert judgments with available operating feedback (Bayesian approach) have been reported by Procaccia et al. [8] for taking into account the combination of failure risk and economic consequence (statistical decision theory) to achieve a true optimization of maintenance policy choices. Reviewing the above papers, most of them always concentrated on the development of mathematical models in achieving the optimization of PM policy based on some specific supporting, such as uniform improvement, maintenance activity and cost, etc. For a system which is consisted of many subsystems and/or components (SCs), the effectiveness of maintenance mainly depends on both the improved levels and the maintenance-costs of the SCs. It is similar to imperfect maintenance. Aiming to imperfect maintenance, Whitaker and Samaniego [9] proposed a method of reliability evaluation. Refs. [10] and [11] below cover different approaches proposed to model imperfect maintenance based on an improvement factor. Considering multi-activities in maintenance, Martorell et al. [12] assumed that the PM activities would affect component age as a function of the maintenance effectiveness, and suggested some age-dependent models to determine the risk and associated economic cost problems. Further, a new reliability model was presented by Martorel et al. [13] in which includes parameters related to surveillance and maintenance effectiveness and working conditions of the equipment, both environmental and operational. For suitably modeling the effects of maintenance to a multi-component system, this paper combines three typical PM actions as follows. (1a)-maintenance (mechanical service). This type-action emphasizes on maintaining a system on normal operating condition. It usually involves less techniques and tools, i.e. the improvement is limitary. It just only improves the extrinsic state (the deteriorated environment) so that it can tune the SCs to a more good condition. Several typical activities for this type are, for example, (a) lubricating, (b) adjusting/calibrating the position or load carried to the mating parts, (c) tightening the loose parts, (d) cleaning the dust, jam and rust, etc. to maintain the inherent function of parts, and (e) consuming materials supplement such as oil, waters, etc. (1b)-maintenance (repair). This type-action is mainly adopted for some SCs which are expensive and/or uneasily to be acquired. It generally includes the activities of (1a) and repairing/replacing for some simple parts such as springs, seals, belts and bearings, etc. It can rightly recover the intrinsic damage except the extrinsic condition improved. Examples for this type are engine overhaul, engineering structure reinforcement and surface treatments to the moving parts, etc. Normally, it usually contains the following activities: (a) disassembly, (b) reassemble of the repaired SCs and/or (c) the whole function calibration. (2P)-maintenance (replacement). This type-action is to replace the subsystem/component (SC) with a new one. It is frequently adopted for the key SCs to avoid serious damage occurred. In addition, the SCs which undergone several times (1a) and (1b) and were not worthy to go on using, may also take this type-action. While planning the PM schedule according to the defined activities, the maintenance time and the optimization goal of system would affect the contents of actions adopted. Considering the time of PM taken, PM policies can be classified into two kinds, periodical PM and non-periodical PM. The former is more regular so that it is often executed in a general system. The latter usually is more complex and is mostly adopted for some specific parts, e.g. key components, because its maintenance interval is not constant. Moreover, the commonly used goals on maintenance optimization are based on either costs minimization or profits maximization [14]. A frequent adopted index in representing system performance is the availability, which describes the ratio of up and down times of systems. It is so important as well as costs/profits in many real situations. Therefore, there were many authors to have considered the both criteria in developing approaches for searching the optimized maintenance [15], [16] and [17]. Typically, Borgonovo et al. [18] presented an approach for the evaluation of plant maintenance strategies and operating procedures under economic constraints. For a complex system, the shut-down loss could be obviously reduced as well as its effectiveness can be promoted if its availability can be set or maintained at someone level. In this paper, availability maximization is adopted as a criterion for scheduling periodical PM. It is used to determine the PM intervals of SCs for a multi-component system. Three kinds of action mentioned above are concurrently taken on each PM stage. The purpose of PM strategy is not only on maintaining the system life to its expected life but also in obtaining the maximum system benefit by availability optimization. By the example analysis, the results demonstrate that the PM policy which considers more than one action is more advantage than that only single action (replacement) adopted.

This paper presented a method of periodical PM policy based on availability consideration for multi-components systems. The possible jobs in maintenance are classified into three activity-types (1a, 1b and 2P) which are concurrently considered on every PM stage. The effects of maintenance to reliability were formulated based on the improvements of the survival and failed parts for constructing the reliability model of system following PM. The improvements are measured by using two factors, which the assessed approach had also been proposed. The PM interval of system is then derived based on availability maximization after the maintenance times decided. While scheduling the PM program, the components whether maintained or not was settled depending on reliability check, and the action option for them were decided by maintenance-benefit analyzing. The PM scheduling was progressed step by step for obtaining the maximum system effectiveness. Once the extended system life is meet to the expected system life, the PM scheduling is terminated. In brief, several remarks are summarized as follows: 1. This PM scheduling was well suitable on a real system because the maintenance contents are considered from its physical characteristics. Properly, this approach can be extended to cost-oriented systems for minimizing life-cycle-cost or maximizing system profit. 2. The maintenance improvement involves both the maintainability of component itself and the maintenance support. A large improvement would easily be obtained if the complexity of components is low and having sufficient tools provided. 3. The studied results show that simultaneously considering 1a, 1b and 2P can efficiently reduce the maintenance cost and increase system availability so that it is more advantage than only replacement considered. 4. The PM interval is affected obviously by the maintenance times. The bigger the ratio of the CM to the PM times, the shorter the PM interval would be. Meanwhile, the more small system effectiveness would be incurred following the ratio increased.