SINGLE-MACHINE MULTIPLE-RECIPE PREDICTIVE MAINTENANCE

2013 ◽  
Vol 27 (2) ◽  
pp. 209-235 ◽  
Author(s):  
Yiwei Cai ◽  
John J. Hasenbein ◽  
Erhan Kutanoglu ◽  
Melody Liao
Keyword(s):  
Optimal Policy ◽  
Predictive Maintenance ◽  
Production Costs ◽  
Threshold Policy ◽  
Discrete Time Markov Chain ◽  
System A ◽  
Long Run ◽  
Monotonicity Result ◽  
Maintenance Policies ◽  
Discounted Costs

This paper studies a multiple-recipe predictive maintenance problem with M/G/1 queueing effects. The server degrades according to a discrete-time Markov chain and we assume that the controller knows both the machine status and the current number of jobs in the system. The controller's objective is to minimize total discounted costs or long-run average costs which include preventative and corrective maintenance costs, holdings costs, and possibly production costs. An optimal policy determines both when to perform maintenance and which type of job to process. Since the policy takes into account the machine's degradation status, such control decisions are known as predictive maintenance policies. In the single-recipe case, we prove that the optimal policy is monotone in the machine status, but not in the number of jobs in the system. A similar monotonicity result holds in the two-recipe case. Finally, we provide computational results indicating that significant savings can be realized when implementing a predictive maintenance policies instead of a traditional job-based threshold policy for preventive maintenances.

Availability analysis and maintenance optimization for multiple failure mode systems considering imperfect repair

2021 ◽  
pp. 1748006X2110127
Author(s):  
Qingan Qiu ◽  
Baoliang Liu ◽  
Cong Lin ◽  
Jingjing Wang
Keyword(s):  
Failure Modes ◽  
Maintenance Cost ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Availability Analysis ◽  
Long Run ◽  
Optimal Maintenance ◽  
Maintenance Policies ◽  
Periodic Inspections

This paper studies the availability and optimal maintenance policies for systems subject to competing failure modes under continuous and periodic inspections. The repair time distribution and maintenance cost are both dependent on the failure modes. We investigate the instantaneous availability and the steady state availability of the system maintained through several imperfect repairs before a replacement is allowed. Analytical expressions for system availability under continuous and periodic inspections are derived respectively. The availability models are then utilized to obtain the optimal inspection and imperfect maintenance policy that minimizes the average long-run cost rate. A numerical example for Remote Power Feeding System is presented to demonstrate the application of the developed approach.

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.

scholarly journals OPTIMALITY OF CONTROL LIMIT MAINTENANCE POLICIES UNDER NONSTATIONARY DETERIORATION

1999 ◽  
Vol 13 (1) ◽  
pp. 55-70 ◽  
Author(s):  
Zvi Benyamini ◽  
Uri Yechiali
Keyword(s):  
Optimal Policy ◽  
Transition Probabilities ◽  
Stationary Problem ◽  
Control Limit ◽  
Maintenance Costs ◽  
Operation And Maintenance ◽  
Deterioration Process ◽  
Maintenance Policies ◽  
Deteriorating Systems ◽  
Limit Form

Control limit type policies are widely discussed in the literature, particularly regarding the maintenance of deteriorating systems. Previous studies deal mainly with stationary deterioration processes, where costs and transition probabilities depend only on the state of the system, regardless of its cumulative age. In this paper, we consider a nonstationary deterioration process, in which operation and maintenance costs, as well as transition probabilities “deteriorate” with both the system's state and its cumulative age. We discuss conditions under which control limit policies are optimal for such processes and compare them with those used in the analysis of stationary models.Two maintenance models are examined: in the first (as in the majority of classic studies), the only maintenance action allowed is the replacement of the system by a new one. In this case, we show that the nonstationary results are direct generalizations of their counterparts in stationary models. We propose an efficient algorithm for finding the optimal policy, utilizing its control limit form. In the second model we also allow for repairs to better states (without changing the age). In this case, the optimal policy is shown to have the form of a 3-way control limit rule. However, conditions analogous to those used in the stationary problem do not suffice, so additional, more restrictive ones are suggested and discussed.

Computer Based Expert System for Rotating Machinery: Preventive and Predictive Maintenance

1992 ◽  
Author(s):  
El-Adawi S. El-Mitwally ◽  
M. A. Rayan ◽  
N. H. Mostafa ◽  
Yehia M. Enab
Keyword(s):  
Expert System ◽  
Preventive Maintenance ◽  
Rotating Machinery ◽  
Predictive Maintenance ◽  
Production Costs ◽  
Operating Cycle ◽  
Maintenance System ◽  
Computer Based ◽  
Points Of View ◽  
Parameters Of Interest

Abstract At the present time, the maintenance of the equipment becomes an essential task for any production system. This task is becoming more important from both the quantity and the quality points of view, particularly in developing countries. Initiating a maintenance system controlled by the computer will be valuable and effective. The developed expert system is a combination of an intelligent inference engine matched with a database of information. This system will enable the operator to spot instantaneously the parameters of interest. The expert maintenance system will be designed to perform preventive maintenance tasks and detects faults/failure during the operating cycle. Predictive maintenance enables the operator to minimize the shut down time of faulty equipment and hence increases the productivity. Furthermore, the system will minimize the probable human faults and reduce production costs.

Big Data Analytics for Predictive Maintenance Strategies

2017 ◽  
pp. 50-74 ◽  
Author(s):  
C. K. M. Lee ◽  
Yi Cao ◽  
Kam Hung Ng
Keyword(s):  
Big Data ◽  
Big Data Analytics ◽  
Cost Effective ◽  
Health Condition ◽  
Predictive Maintenance ◽  
Maintenance Policy ◽  
Failure Patterns ◽  
Maintenance Decision ◽  
Maintenance Policies ◽  
Faulty Component

Maintenance aims to reduce and eliminate the number of failures occurred during production as any breakdown of machine or equipment may lead to disruption for the supply chain. Maintenance policy is set to provide the guidance for selecting the most cost-effective maintenance approach and system to achieve operational safety. For example, predictive maintenance is most recommended for crucial components whose failure will cause severe function loss and safety risk. Recent utilization of big data and related techniques in predictive maintenance greatly improves the transparency for system health condition and boosts the speed and accuracy in the maintenance decision making. In this chapter, a Maintenance Policies Management framework under Big Data Platform is designed and the process of maintenance decision support system is simulated for a sensor-monitored semiconductor manufacturing plant. Artificial Intelligence is applied to classify the likely failure patterns and estimate the machine condition for the faulty component.

Selection of Maintenance Strategies in an Operating Theatre

2021 ◽  
pp. 1-35
Author(s):  
María Carmen Carnero ◽  
Andrés Gómez
Keyword(s):  
Preventive Maintenance ◽  
Predictive Maintenance ◽  
Operating Theatre ◽  
Sterile Water ◽  
Repairable Systems ◽  
Corrective Maintenance ◽  
Water Power ◽  
Suitable Combination ◽  
Multicriteria Model ◽  
Maintenance Policies

The aim of this chapter is to select the most suitable combination of maintenance policies in the different systems that make up an operating theatre: air conditioning, sterile water, power supply, medicinal gases, and operating theatre lighting. To do so, a multicriteria model will be developed using the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) approach considering multiple decision centres. The model uses functional, safety, and technical-economic criteria, amongst which is availability. Mean availability for repairable systems has been measured to assess this criterion, using Markov chains from the data obtained over three years from the subsystems of a hospital operating theatre. The alternatives considered are corrective maintenance; preventive maintenance together with corrective maintenance by means of daily, weekly, monthly, and yearly programmes; periodical predictive maintenance together with corrective maintenance; and corrective together with preventive and predictive maintenance.

A NOTE ON OPTIMAL DEBT REDUCTION POLICIES

2019 ◽  
Vol 24 (7) ◽  
pp. 1850-1860 ◽  
Author(s):  
Davide la Torre ◽  
Simone Marsiglio
Keyword(s):  
Economic Policy ◽  
Real World ◽  
Optimal Policy ◽  
Social Costs ◽  
Social Planner ◽  
Long Run ◽  
The Social ◽  
Reduction Problem ◽  
Short Run ◽  
Over Time

We analyze the optimal debt reduction problem in an uncertainty context. The social planner has a finite horizon and seeks to minimize the social costs associated with debt repayment by taking into account not only the short-run costs of the policy, but also the long-run costs associated with the outstanding level of debt. We characterize the optimal policy and the dynamics of the debt-to-GDP ratio, showing that it will decrease over time if economic policy is effective enough. We characterize how the evolution of the debt-to-GDP ratio depends on the main parameters and we present a simple calibration based on Greek data to illustrate the implications of our analysis in real-world setups.

Do we care what others Get? A Behaviorist Approach to Targeted Promotions

2002 ◽  
Vol 39 (3) ◽  
pp. 277-291 ◽  
Author(s):  
Fred M. Feinberg ◽  
Aradhna Krishna ◽  
Z. John Zhang
Keyword(s):  
Economic Theory ◽  
Stochastic Model ◽  
Optimal Policy ◽  
Optimal Strategy ◽  
Consumer Preference ◽  
Theoretic Analysis ◽  
Game Theoretic Analysis ◽  
Pricing Policies ◽  
Long Run ◽  
Game Theoretic

Increased access to individual customers and their purchase histories has led to a growth in targeted promotions, including the practice of offering different pricing policies to prospective, as opposed to current, customers. Prior research on targeted promotions has adopted a tenet of the standard economic theory of choice, whereby what a consumer chooses depends exclusively on the prices available to that consumer. In this article, the authors propose that consumer preference for firms is affected not just by prices the consumers themselves are offered but also by prices available to others. This departure from the conventional strong-rationality approach to targeted promotion results in a decidedly different optimal policy. Through a laboratory experiment, calibration of a stochastic model, and game-theoretic analysis, the authors demonstrate that ignoring behaviorist effects exaggerates the importance of targeting switchers as opposed to loyals. This occurs, though with intriguing differences, even when only part of the market is aware of firms’ differing promotional policies. The authors show that both the deal percentage and the proportion of aware consumers affect the optimal strategy of the firm. Furthermore, the authors find that offering lower prices to switchers may not be a sustainable practice in the long run, as information spreads and the proportion of aware consumers grows. The model cautions practitioners against overpromoting and/or promoting to the wrong segment and suggests avenues for improving the effectiveness of targeted promotional policies.

Sign in / Sign up

Export Citation Format

Share Document