Actuation Delay-Time Estimation with Imaging Fuze

Generally,Doppler fuze can only estimate actuation delay-time with a limited precision. As an improvement,imaging fuze can estimate actuation delay-time more precisely with the available two-dimensional image of the target. In this paper,imprecision of actuation delay-time estimation with Doppler fuze is first analyzed theoretically in brief. Secondly,feasibility analysis and theoretical model of imaging fuze are described,in which a criterion is established for the actuation delay-time based on the image,and then an image based gray-value weighted least square（ GWLS） algorithm is presented to calculate actuation delay-time of the imaging fuze. Finally,a simulation model of missiletarget near-field encounter is established. Simulation results indicate that actuation delay-time of the imaging fuze is estimated more precisely than by the Doppler fuze.

Maintenance Scheduling with Delay-time Modelling An Overview

Effective maintenance is a key for infrastructuresr high operational reliability.The integration of corrective repairs and schedule-based failure preventions has been a mainstream of modern maintenance,and an associated policy-making technique,delay-time modelling,is overviewedin this paper for optimising the maintenance cost-efficiency in different practical scenarios,including imperfect,opportunistic and nested maintenance.A few typical examples of its applications in minimising maintenance operating expenses are discussed in this paper and their results are explained to better demonstrate the benefits of the technique.This work aims to prepare for the future applications of the delay-time modelling in railway maintenance policy making.

Joint optimization of inspection, maintenance, and spare ordering policy considering defective products loss

This paper proposes a joint inspection-based maintenance and spare ordering optimization policy that considers the problem of integrated inspection,preventive maintenance,spare ordering,and quality control for a four-state single-unit manufacturing system.When an inspection detects a minor defect,a second phase inspection is initiated and a regular order is placed.Product quality begins to deteriorate when the system undergoes a severe defect.To counter this,an advanced replacement of the minor defective system is carried out at the Jth second phase inspection.If a severe defect is recognized prior to the Jth inspection,or if system failure occurs,preventive or corrective replacement is executed.The timeliness of replacement depends on the availability of spare.We adopt two modes of ordering:a regular order and an emergency order.Meanwhile,a threshold level is introduced to determine whether an emergency order is preferred even when the regular order is already ordered but has not yet arrived.The optimal joint inspection-based maintenance and spare ordering policy is formulated by minimizing the expected cost per unit time.A simulation algorithm is proposed to obtain the optimal two-phase inspection interval,threshold level and advanced replacement interval.Results from several numerical examples demonstrate that,in terms of the expected cost per unit time,our proposed model is superior to some existing models.

Periodical Inspections and Delay Replacement Model Based on Age Preventive Replacement Policy

Periodical inspections and an age-based preventive replacement( APR) model were proposed based on a two-stage failure process for a single component system. Inspection activities were performed at regular intervals. Once the system was identified to be at defective state by inspection,a maintenance decision needed to be made that whether to replace the defective system immediately or wait till the preset APR time. So a threshold was introduced into the model and called as inspection-based preventive replacement( IPR) threshold. If the distance from the defect identification point to the APR time was longer than the threshold, a preventive replacement( PR) action was made; otherwise PR action was to wait till the APR time. Two models were proposed and compared,and a numerical example was conducted to illustrate the applicability of the model.

Reliability modelling based on dependent two-stage virtual age processes

This paper proposes reliability and maintenance models for systems suffering random shocks arriving according to a non-homogeneous Poisson process.The system degradation process include two stages:from the installation of a new system to an initial point of a defect(normal stage),and then from that point to failure(defective stage),following the delay time concept.By employing the virtual age method,the impact of external shocks on the system degradation process is characterized by random virtual age increment in the two stages,resulting in the corresponding two-stage virtual age process.When operating in the defective state,the system becomes more susceptible to fatigue and suffers from a greater aging rate.Replacement is carried out either on failure or on the detection of a defective state at periodic or opportunistic inspections.This paper evaluates system reliability performance and investigates the optimal opportunistic maintenance policy.A case study on a cooling system is given to verify the obtained results.

Optimal Inspection and Replacement Strategy for Systems Subject to Two Types of Failures with Adjustable Inspection Intervals

The inspection activities are often carried out to detect possible indication of failures in plant systems.This paper considers a single unit system subject to two types of failures, where one failure mode is the traditional0-1 logic failure and the other failure mode is described by a two-stage failure process. Adjustable inspections are used to detect the defective stage of the latter. We assume that the inspection duration gets shorter and shorter with a constant ratio. At the same time, preventive replacement is used to avoid the possible failure due to the former failure mode. The renewal process of this system is analyzed and the expected long-run cost per unit time(ELRCUT) is derived. The optimal inspection period and the preventive replacement interval to minimize ELRCUT are studied. At last, a numerical example is presented to illustrate the proposed model.