scholarly journals Opportunistic Maintenance Policy for a Multi-Component System Subject to Random Failures

2017 ◽  
Vol 4 (2) ◽  
pp. 80-91
Author(s):  
H. Eldhadaf ◽  
R. Benmansour ◽  
H. Allaoui ◽  
M. Tkiouat ◽  
A. Artiba
Keyword(s):  
Optimization Procedure ◽  
Spare Part ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Opportunistic Maintenance ◽  
Component System ◽  
Two Parameters ◽  
Scheduled Time ◽  
Random Failures ◽  
Multi Component System

In this paper, an opportunistic maintenance policy (OMP) for a multi-component system is studied. The objective is to minimize the maintenance cost while guaranteeing a minimum level of reliability for the system and for each of its components. Each component is subject to random failures and at most one spare part of it should be kept in stock or ordering at any time. The lifetime of this system will be divided into several periods. At the beginning of each period, the set of actions (among many others) must be determined in order to achieve the objective mentioned above. The policy OMP is characterized by two parameters; the first one is the scheduled time for spare ordering and the second one is the period of realization of the maintenance action (if any). These parameters will be derived from the joint optimization of maintenance cost and the inventory cost for each component. Finally, a numerical example to explain the proposed maintenance policy and the optimization procedure is provided.

scholarly journals Opportunistic Maintenance Policy for A Multi-Component System Subject To Random Failures

2021 ◽  
Vol 4 (1) ◽  
pp. 15-27
Author(s):  
H. Elhadaf ◽  
R. Benmansour ◽  
H. Allaoui ◽  
M. Tkiouat ◽  
A. Artiba
Keyword(s):  
Optimization Procedure ◽  
Spare Part ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Opportunistic Maintenance ◽  
Component System ◽  
Two Parameters ◽  
Scheduled Time ◽  
Random Failures ◽  
Multi Component System

In this paper we study an opportunistic maintenance policy (OMP) for a multi-component system. The objective is to minimize the maintenance cost while guaranteeing a minimum level of reliability for the system and for each of its components. We suppose that each component is subject to random failures and at most one spare part of it should be kept in stock or ordering at any time. The lifetime of this system will be divided into several periods. At the beginning of each period we must determine the set of actions (among many others) that will achieve the objective mentioned above. The policy OMP is characterized by two parameters; the first one is the scheduled time for spare ordering and the second one is the period of realization of the maintenance action (if any). These parameters will be derived from the joint optimization of maintenance cost and the inventory cost for each component. Finally, we will give a numerical example to explain the proposed maintenance policy and the optimization procedure.

A condition-based opportunistic maintenance strategy for multi-component system

2018 ◽  
Vol 18 (1) ◽  
pp. 270-283 ◽  
Author(s):  
Hongshan Zhao ◽  
Fanhao Xu ◽  
Botong Liang ◽  
Jianping Zhang ◽  
Peng Song
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Condition Based Maintenance ◽  
Threshold Function ◽  
Maintenance Cost ◽  
Maintenance Strategy ◽  
Opportunistic Maintenance ◽  
Component System ◽  
Condition Indicator ◽  
Multi Component System

As a new dynamic maintenance strategy, the condition-based opportunistic maintenance strategy for multi-component system is presented in this work. In the strategy, the degeneration of each component is described by Weibull proportional hazards model or Weibull proportional intensity model, and the condition indicator is defined to characterize the operating state of each component. Then, when and how to maintain a component can be confirmed by comparing the value of the condition indicator with that of the maintenance threshold function. Condition-based maintenance will be implemented on a component if the value of its condition indicator exceeds that of its condition-based maintenance threshold function. Meanwhile, opportunistic maintenance will also be implemented on a component if the value of its condition indicator exceeds that of its opportunistic maintenance threshold function. The two maintenance threshold functions can be determined by minimizing maintenance cost. Finally, taking the wind turbine as an example of a multi-component system, simulation analyses are described to validate the feasibility and effectiveness of the condition-based opportunistic maintenance strategy.

Bi-Criteria Optimization for Finding the Optimal Replacement Interval for Maintaining the Performance of the Process Industries

2016 ◽  
pp. 643-675 ◽  
Author(s):  
Harish Garg
Keyword(s):  
Maintenance Cost ◽  
Time Interval ◽  
Process Industries ◽  
Component System ◽  
Optimal Replacement ◽  
Maintenance Program ◽  
Optimal Maintenance ◽  
Maintenance Decision ◽  
System Life ◽  
Multi Component System

The optimization of the maintenance decision making can be defined as an attempt to resolve the conflicts of decision situation in such a way that variable under the control of the decision maker take their best possible value. One of the most important controllable parameters is the time interval between maintenance. Most of the researchers have kept the fact that whenever the suitable maintenance interval is reached, the system is replaced with the original one. However the improvement of a system life not only depends on the replacement of deteriorated components, but also on the effectiveness of the maintenance. Taking care about this fact, the effects of maintenance of a multi-component system by combining the three main different PM actions, namely (1a), (1b) and (2p)-maintenance actions. Thus, the main purpose of an effective maintenance program is to present a technique for finding the optimal maintenance interval for the system by considering the multiple goals of the organization viz. maximum availability, minimum maintenance cost.

Online Analytics Framework of Sensor-Driven Prognosis and Opportunistic Maintenance for Mass Customization

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Tangbin Xia ◽  
Xiaolei Fang ◽  
Nagi Gebraeel ◽  
Lifeng Xi ◽  
Ershun Pan
Keyword(s):  
Real Time ◽  
Mass Customization ◽  
Maintenance Scheduling ◽  
System Level ◽  
Maintenance Cost ◽  
Time To Failure ◽  
Maintenance Policy ◽  
Opportunistic Maintenance ◽  
Product Demand ◽  
System Breakdown

In mass customization, a manufacturing line is required to be kept in reliable operation to handle product demand volatility and potential machine degradations. Recent advances in data acquisition and processing allow for effective maintenance scheduling. This paper presents a systematic framework that integrates a sensor-driven prognostic method and an opportunistic maintenance policy. The prognostic method uses degradation signals of each individual machine to predict and update its time-to-failure (TTF) distributions in real time. Then, system-level opportunistic maintenance optimizations are dynamically made according to real-time TTF distributions and variable product orders. The online analytics framework is demonstrated through the case study based on the collected reliability information from a production line of engine crankshaft. The results can effectively prove that the real-time degradation updating and the opportunistic maintenance scheduling can efficiently reduce maintenance cost, avoid system breakdown, and ensure product quality. Furthermore, this framework can be applied not only in an automobile line but also for a broader range of manufacturing lines in mass customization.

scholarly journals Maintenance modelling and optimization in the industry 4.0 context: Applications to the maintenance and design of industrial vehicles

2021 ◽  
Vol 3 (2) ◽  
pp. 130-138
Author(s):  
Segolene Clemence Marie Mosser
Keyword(s):  
Industry 4.0 ◽  
Operating Costs ◽  
Maintenance Cost ◽  
Component System ◽  
Total Cost ◽  
The Impact ◽  
Multi Component System ◽  
Modelling And Optimization ◽  
Monitoring Information

This paper focused on the maintenance problems encountered by industrial vehicles within the Volvo Group. The main goal of the research on this subject was to propose to customers’ a personalized maintenance offer which adapts to their constraints while reducing the impact on the operating costs. To achieve this, a policy has been developed. This policy works on the dynamic gathering of information using both the available monitoring information and the knowledge of the multi-component system. Its objective is to guarantee to the customer the autonomy of its system over given periods of operation while minimizing the total cost of maintenance. The paper showed that the policy developed does indeed reduce the total maintenance cost compared to the previous policy used within the Volvo group. Nevertheless, this policy still has room for improvement.

scholarly journals A MULTI-OBJECTIVE APPROACH TO OPTIMIZE A PERIODIC MAINTENANCE POLICY

2012 ◽  
Vol 19 (06) ◽  
pp. 1240002 ◽  
Author(s):  
ANTONELLA CERTA ◽  
MARIO ENEA ◽  
GIACOMO GALANTE ◽  
TONI LUPO
Keyword(s):  
Programming Model ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Multi Objective ◽  
System A ◽  
Periodic Maintenance ◽  
Finite Time Horizon ◽  
Multi Component System

The present paper proposes a multi-objective approach to find out an optimal periodic maintenance policy for a repairable and stochastically deteriorating multi-component system over a finite time horizon. The tackled problem concerns the determination of the system elements to replace at each scheduled and periodical system inspection by ensuring the simultaneous minimization of both the expected total maintenance cost and the expected global system unavailability time. It is assumed that in the case of system elements failure they are instantaneously detected and repaired by means of minimal repair actions in order to rapidly restore the system. A nonlinear integer mathematical programming model is developed to solve the treated multi-objective problem, whereas the Pareto optimal frontier is described by the Lexicographic Goal Programming and the ε-constraint methods. To explain the whole procedure, a case study is solved and the related considerations are given.

OPPORTUNISTIC MAINTENANCE OPTIMIZATION FOR WIND TURBINE SYSTEMS CONSIDERING IMPERFECT MAINTENANCE ACTIONS

2011 ◽  
Vol 18 (05) ◽  
pp. 463-481 ◽  
Author(s):  
FANGFANG DING ◽  
ZHIGANG TIAN
Keyword(s):  
Wind Power ◽  
Preventive Maintenance ◽  
Wind Farm ◽  
Power Industry ◽  
Maintenance Cost ◽  
Maintenance Optimization ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Opportunistic Maintenance ◽  
Wind Power Industry

Currently corrective maintenance and time-based preventive maintenance strategies are widely used in wind power industry. However, few methods are applied to optimize these strategies. This paper aims to develop opportunistic maintenance approaches for an entire wind farm rather than individual components that most of the existing studies deal with. Furthermore, we consider imperfect actions in the preventive maintenance tasks, which address the issue that preventive maintenance do not always return components to the as-good-as-new status in practice. In this paper we propose three opportunistic maintenance optimization models, where the preventive maintenance is considered as perfect, imperfect and two-level action, respectively. Simulation methods are developed to evaluate the costs of the proposed opportunistic maintenance policies. Numerical examples are provided to demonstrate the advantage of the proposed opportunistic maintenance methods in reducing the maintenance cost. The two-level action method demonstrates to be the most cost-effective in different cost situations, while the imperfect maintenance policy, which is a simpler method, is a close second. The developed methods are expected to bring immediate benefits to wind power industry.

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