An Age-Based Inspection and Replacement Policy for Heterogeneous Components

Abstract

Abstract-This paper considers a hybrid maintenance policy for a single component from a heterogeneous population. The component is placed in a socket, and the component and socket together comprise the system. The -population of components consists of two sub-populations with different failure characteristics. By supposing that a component may be in a defective but operating state, so that there exists a delay time between defect arrival and component failure, we consider a novel maintenance policy that is a hybrid of inspection and replacement policies. There are similarities in this approach with the concept of "burn-in" maintenance. The policies are investigated in the context of traction motor bearing failures. Under certain circumstances, particularly when the mixture parameter is large, and the distribution of lifetimes for the two component types are well separated, the hybrid policy has significant cost savings over the standard age-based replacement policy, and over the pure inspection policy. In addition to the cost metric, the mean time between operational failures of the system under the hybrid policy can be used to guide decision-making. This maintenance policy metric is calculated using simulation, and using an approximation which assumes that operational failures occur according to a Poisson process with a rate that can be calculated in a straightforward way. The simulation results show good agreement with the approximation.

Random preventive maintenance policy based on inspection for a multicomponent system using simulation

“…segments of, industry such as considering a high-speed milling tool wear by Yan et al [25], in pipes that undergo corrosion by Sahraoui et al [21], in reparable multicomponent hospital systems by Golmakani and Moakedi [13], and for the equipment that are inspected by the manufacturers in the warranty period with a cost charged to them, and after this period with the cost charged to the customer [8]. Golmakani and Moakedi [13] were among who developed a maintenance cost optimization model based on periodic inspections for a reparable multicomponent system.…”

“…According Scarf et al [21], the search for the optimum value of the policy considering the cost minimization, can be calculated by dividing the expected value for the policy cost by the expected value of the cycle size. Thus, the present paper finds the expected value for the cost E(C) and the expected value to the size of the cycle E(SL) by a simulation process (in a free programming software), through the flowchart shown in Figure 5.…”

Basic Concepts on Risk Analysis, Reliability and Maintenance

“…The first consists of formulating a problem in terms of relating it to the aims of a project by establishing systems and structural, technological or organizational measures to ensure that the standard of reliability required by the production system will meet the requirements set by performance issues. Such questions resonate with many problems that extend right up to the moment prior to using the system (Scarf et al 2009). …”

“…At one extreme, if all maintenance actions are limited to emergency repairs only after the system has suffered a failure, then the operational characteristics of the system are likely to be very low and the system will not operate in an efficient manner (Scarf et al 2009). As a result, the second approach deals with numerous issues, the main concerns of which are related to the system already in operation and its nature and have regard to proposing measures that will obtain the best possible operational characteristics.…”

A study of postponed replacement in a delay time model

“…Further, we allow the possibility that inspections may be imperfect, so that false negatives (whereby inspection indicates that the system is no-defective when it is in fact defective) and false positives are possible (as in Berrade et al [6], [7], [8]). The consequences of imperfect maintenance interventions mentioned in points 4 and 5 whereby strong components may be replaced with weak components have been analyzed in Scarf and Cavalcante [30] and [31]. In this new context, we can consider points 4 and 5 as reasons for postponement, and also related to these, belief of the maintainer that the system is good when inspection indicates otherwise.…”