Maintenance Decision Model for a Two-Machine Production Line With Multistage Degradation Machines

2018 ◽  
Author(s):  
Yunyi Kang ◽  
Feng Ju
Keyword(s):  
Decision Model ◽  
Production Systems ◽  
Maintenance Policy ◽  
Multi Stage ◽  
Markov Decision ◽  
Optimal Maintenance ◽  
Markov Decision Model ◽  
Maintenance Decision ◽  
Maintenance Policies ◽  
Optimal Maintenance Policy

In this work, we develop preventative maintenance policies on two-machine-and-one-buffer production systems with machines subject to multi-stage degradation. Condition-based maintenance policies are generated for both machines, with consideration on both the machine degradation stages and the buffer level. Moreover, the policies are flexible, allowing a machine to be recovered to any better operating state, while merely recovering to the best operating state is possible in many previous work. A Markov decision model is formulated to find the optimal maintenance policy and computational experiments show that the policies improve the performance of a system in finite production runs.

Real-Time Maintenance Policy in Manufacturing Systems With Intermediate Buffers

2015 ◽  
Author(s):  
Xi Gu ◽  
Xiaoning Jin ◽  
Jun Ni
Keyword(s):  
Real Time ◽  
Manufacturing Systems ◽  
Maintenance Policy ◽  
Discrete Time Markov Chain ◽  
Markov Decision ◽  
Maintenance Decision ◽  
Maintenance Policies ◽  
Time Buffer ◽  
Buffer Capacities ◽  
One Machine

Real-time maintenance decision making in large manufacturing system is complex because it requires the integration of different information, including the degradation states of machines, as well as inventories in the intermediate buffers. In this paper, by using a discrete time Markov chain (DTMC) model, we consider the real-time maintenance policies in manufacturing systems consisting of multiple machines and intermediate buffers. The optimal policy is investigated by using a Markov Decision Process (MDP) approach. This policy is compared with a baseline policy, where the maintenance decision on one machine only depends on its degradation state. The result shows how the structures of the policies are affected by the buffer capacities and real-time buffer levels.

Imperfect maintenance model for estimating aircraft fleet availability

2017 ◽  
Vol 89 (2) ◽  
pp. 338-346 ◽  
Author(s):  
Aleksandar Knezevic ◽  
Ljubisa Vasov ◽  
Slavisa Vlacic ◽  
Cedomir Kostic
Keyword(s):  
Intermediate Level ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Content Type ◽  
Reliability Parameters ◽  
Optimal Maintenance ◽  
Maintenance Policies ◽  
Optimal Maintenance Policy ◽  
Maintenance Model

Purpose The purpose of this paper is to define conditions under which improved availability of fleet of G-4 jet trainers is obtained, and optimization of intermediate-level maintenance through imperfect maintenance model application. This research has been conducted based on available knowledge, and experience gained by performing intermediate-level maintenance of Serbian Air Force aircrafts. Design/methodology/approach Analysis of the data collected from daily maintenance reports, and the analysis of maintenance technology and organization, was performed. Based on research results, a reliability study was performed. Implementation of imperfect maintenance with its models of maintenance policies (especially a quasi-renewal process and its treating of reliability and optimal maintenance) was proposed to define new maintenance parameters so that the greater level of availability could be achieved. Findings The proposed methodology can potentially be applied as a simple tool to estimate the present maintenance parameters and to quickly point out some deficiencies in the analyzed maintenance organization. Validation of this process was done by conducting a reliability case study of G-4 jet trainer fleet, and numerical computations of optimal maintenance policy. Research limitations/implications The methodology of the availability estimation when reliability parameters were not tracked by the maintenance organization, and optimization of intermediate-level maintenance, has so far been applied on G-4 jet trainers. Moreover, it can be potentially applied to other aircraft types. Originality/value Availability estimation and proposed optimization of intermediate maintenance is based on a survey of data for three years of aircraft fleet maintenance. It enables greater operational readiness (due to a military rationale) with possible cost reduction as a consequence but not as a goal.

A Generalized Age-Replacement Model

1992 ◽  
Vol 6 (4) ◽  
pp. 525-541 ◽  
Author(s):  
Stephan G. Vanneste
Keyword(s):  
Optimization Procedure ◽  
Control Limit ◽  
Maintenance Policy ◽  
Unimodal Function ◽  
Replacement Model ◽  
Markov Decision ◽  
Optimal Maintenance ◽  
Age Replacement ◽  
Replacement Problem ◽  
Optimal Maintenance Policy

Four practically important extensions of the classical age-replacement problem are analyzed using Markov decision theory: (1) opportunity maintenance, (2) imperfect repair, (3) non-zero repair times, and (4) Markov degradation of the working unit. For this general model, we show that the optimal maintenance policy is of the control limit type and that the average costs are a unimodal function of the control limit. An efficient optimization procedure is provided to find the optimal policy and its average costs. The analysis extends and unifies existing results.

MAINTENANCE OPTIMIZATION OF EQUIPMENT BY LINEAR PROGRAMMING

2005 ◽  
Vol 20 (1) ◽  
pp. 183-193 ◽  
Author(s):  
Archana Jayakumar ◽  
Sohrab Asgarpoor
Keyword(s):  
Linear Programming ◽  
Preventive Maintenance ◽  
Mathematical Optimization ◽  
Optimal Solution ◽  
Cost Effective ◽  
Maintenance Policy ◽  
Markov Decision ◽  
Random Failure ◽  
Optimal Maintenance ◽  
Optimal Maintenance Policy

Optimal levels of preventive maintenance performed on any system ensures cost-effective and reliable operation of the system. In this paper a component with deterioration and random failure is modeled using Markov processes while incorporating the concept of minor and major preventive maintenance. The optimal mean times to preventive maintenance (both minor and major) of the component is determined by maximizing its availability with respect to mean time to preventive maintenance. Mathematical optimization programs Maple 7 and Lingo 7 are used to find the optimal solution, which is illustrated using a numerical example. Further, an optimal maintenance policy is obtained using Markov Decision Processes (MDPs). Linear Programming (LP) is utilized to implement the MDP problem.

An Optimal Maintenance Policy for a Queueing System Server Under Periodic Observation

1997 ◽  
Vol 04 (04) ◽  
pp. 357-367 ◽  
Author(s):  
Junji Koyanagi ◽  
Hajime Kawai
Keyword(s):  
Preventive Maintenance ◽  
Queueing System ◽  
Observation Time ◽  
Maintenance Policy ◽  
Corrective Maintenance ◽  
Markov Decision ◽  
Poisson Stream ◽  
Optimal Maintenance ◽  
Optimal Maintenance Policy ◽  
Time Of Failure

This paper describes an optimal maintenance policy for an M/M/1 queueing system server. Customers arrive at the system in a Poisson stream and are served by the exponential server. After a random time, the server is interrupted by a failure and this failure is detected through regularly timed observations. We begin corrective maintenance when we detect the failure. Through the failure of the server, we lose the customers in the system at the time of failure, as well as the customers that arrive between the failure and the completion of corrective maintenance. However, it is possible to avoid the failure and subsequent corrective maintenance by performing preventive maintenance at observation time. It is true that customers in the system at the start of preventive maintenance and those that arrive prior to its completion are lost. Since the queueing system should serve as many customers as possible, our objective is to minimize the number of lost customers. We then formulate this problem as a semi-Markov decision process and prove the switch curve structure of the optimal policy.

scholarly journals Dynamic Analysis of a Unified Multivariate Counting Process and Its Asymptotic Behavior

2009 ◽  
Vol 2009 ◽  
pp. 1-43 ◽  
Author(s):  
Ushio Sumita ◽  
Jia-Ping Huang
Keyword(s):  
Asymptotic Behavior ◽  
Counting Process ◽  
Poisson Processes ◽  
Renewal Processes ◽  
Counting Processes ◽  
Maintenance Policy ◽  
Nonhomogeneous Poisson Processes ◽  
Optimal Maintenance ◽  
Maintenance Policies ◽  
Optimal Maintenance Policy

The class of counting processes constitutes a significant part of applied probability. The classic counting processes include Poisson processes, nonhomogeneous Poisson processes, and renewal processes. More sophisticated counting processes, including Markov renewal processes, Markov modulated Poisson processes, age-dependent counting processes, and the like, have been developed for accommodating a wider range of applications. These counting processes seem to be quite different on the surface, forcing one to understand each of them separately. The purpose of this paper is to develop a unified multivariate counting process, enabling one to express all of the above examples using its components, and to introduce new counting processes. The dynamic behavior of the unified multivariate counting process is analyzed, and its asymptotic behavior ast→∞is established. As an application, a manufacturing system with certain maintenance policies is considered, where the optimal maintenance policy for minimizing the total cost is obtained numerically.

Maintenance Decision-Making Under the Cost Criterion and the Competing Risks Approach

2017 ◽  
Vol 9 (1) ◽  
pp. 32-48 ◽  
Author(s):  
Rima Oudjedi Damerdji ◽  
Myriam Noureddine
Keyword(s):  
Decision Making ◽  
Competing Risks ◽  
Preventive Maintenance ◽  
Optimal Operation ◽  
Maintenance Cost ◽  
Delay Model ◽  
Maintenance Policy ◽  
Optimal Maintenance ◽  
Maintenance Decision ◽  
Optimal Maintenance Policy

The definition of an appropriated maintenance policy appears essential to avoid the system failures and ensure its optimal operation, while taking into account the criteria of availability and costs. This article deals with a maintenance decision-making for a system subject to two competing maintenance actions, corrective and preventive maintenance. To define this situation of dependent competing risks, the Alert Delay model seems well suited because it involves the notion of a delivered alert before system failure in order to perform preventive maintenance. This paper proposes an approach including both an extension of the Alert Delay model where the considered system follows an exponential distribution, and the total maintenance cost assessment of the system. These two concepts provide an aid decision-making to select the optimal maintenance policy based on the minimal cost. The proposed approach is validated in a computer system localized in a real industrial enterprise.

Condition-Based Maintenance Decision-Making for Multiple Machine Systems

2009 ◽  
Vol 131 (3) ◽  
Author(s):  
Saumil Ambani ◽  
Lin Li ◽  
Jun Ni
Keyword(s):  
Decision Making ◽  
Single Machine ◽  
Resource Constraints ◽  
Quantitative Description ◽  
Condition Based Maintenance ◽  
Maintenance Policy ◽  
Machine System ◽  
Maintenance Decision ◽  
Maintenance Policies ◽  
Optimal Maintenance Policy

Maintenance decision-making has emerged as an important area of industrial research. Over the past two decades, maintenance policies have evolved from simple reactive maintenance to complex versions of condition-based maintenance (CBM). A quantitative description of a machine’s health, as found in CBM, is essential to plan maintenance effectively as it helps avoid excessive or insufficient maintenance. In spite of several advancements in the degradation monitoring techniques, most CBM decision-making methods still focus on a single machine system. Maintenance analysis of a single machine provides good insights, but lacks practical applications. In this paper, we develop a continuous time Markov chain degradation model and a cost model to quantify the effects of maintenance on a multiple machine system. An optimal maintenance policy for a multiple machine system in the absence of resource constraints is obtained. In the presence of resource constraints, two prioritization methods are proposed to obtain effective maintenance policies for a multiple machine system. A case study focusing on a section of an automotive assembly line is used to illustrate the effectiveness of the proposed method.

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