Imperfect Maintenance Strategy Research Articles

A novel TD3 for solving multi-level imperfect maintenance optimization problem

Abstract As we all know, multi-level imperfect maintenance strategy is usually more effective than single-level maintenance strategy for the actual production machines. At the same time, in the previous multi-level maintenance strategies, the majority of maintenance models only consider the constant maintenance thresholds, while variable maintenance thresholds are usually ignored. Under these contexts, a novel multi-level imperfect maintenance model with variable preventive maintenance (PM) thresholds, variable overhaul maintenance (OM) thresholds and variable number of PMs in each OM cycle is established. In order to deal with the concerned problem, a novel twin delayed deep deterministic policy gradient (TD3) algorithm that is a kind of reinforcement learning is designed, renamed as NTD3. Finally, through numerical simulation, we can find that (1) the average improvements between the proposed maintenance strategy and other three traditional strategies in the average cost rate (ACR) are 11.50%, 595.91% and 5.16%, respectively; and (2) the average improvement between the proposed NTD3 and other random search method is 5.53%. Thus, the effectiveness of the proposed maintenance strategy and the superiority of proposed NTD3 are all demonstrated.

An Imperfect Grouping Maintenance Strategy for Multi-Component Systems Using the Survival Signature

This paper presents an imperfect maintenance strategy for the multi-component systems. The proposed maintenance strategy takes into account two types of maintenance actions, namely preventive maintenance (PM) and corrective maintenance (CM). The imperfect effect of PM is modeled on the basis of the hybrid hazard rate model. Meanwhile, a new structure importance measure based on the survival signature is presented. Using this new importance measure method, an adjustment function is designed to update the PM maintenance threshold. For CM actions, a decision rule relying on the criticality level of components is introduced. In order to judge the criticality level of components, a novel structure updating method based on the survival signature is proposed. Moreover, a maintenance model considering economic dependence among components is developed. A 10-component system is finally introduced to illustrate the use and advantages of the proposed maintenance strategy.

An improved imperfect maintenance strategy for multiperiod randomly failing equipment with stochastic repair times

PurposeIn this paper, a maintenance strategy based on improved imperfect maintenance actions with stochastic repair times for multiperiod randomly failing equipment is developed. The main objective is to minimize the total maintenance cost by jointly finding the optimal preventive maintenance (PM) cycle and planning horizon.Design/methodology/approachA model based on the mathematical theory of reliability is developed to minimize the total maintenance cost by jointly finding the optimal couple: PM cycle T* and planning horizon H*. The proposed model aims to characterize the evolutionary impact of imperfect PM actions on the equipment failure rate and the resulting mean number of failures. The conventional threshold accepting (TA) algorithm is implemented to solve the proposed model. A numerical example for a given set of input parameters is presented in order to show the usefulness of the proposed model. A sensitivity analysis of some of the key parameters is performed to demonstrate the coherence of the developed maintenance policy.FindingsThe obtained results showed a sensitive trade-off between PM frequency and the total maintenance cost. Performing PM actions more frequently helps significantly to reduce the expected number of corrective maintenance actions and the corresponding total cost. It has also been found that improving the efficiency of the PM actions allows for maintaining the equipment less frequently by increasing the time between successive PM actions.Research limitations/implicationsGiven the complexity of the objective function to be minimized and the stochastic nature of the model's parameters, the authors limited this study to equally cyclic production periods over the planning horizon.Practical implicationsThe present model aims to provide an integrated maintenance/production comprehensive framework to assist planners in establishing maintenance schedules considering multiperiod randomly failing production systems and the evolutionary impact of imperfect PM actions on the equipment failure rate.Originality/valueContrary to the majority of existing works in the literature dealing with maintenance strategies, the authors consider that repair times are stochastic to provide a more realistic framework. In addition, the developed model considers the impact of imperfect maintenance on the equipment's mean time to failure. Thus, the evolutionary impact of imperfect PM actions on the equipment failure rate and the resulting mean number of failures is characterized. Simultaneously, the production planning horizon along with the length of each PM cycle is optimized in order to minimize the total maintenance cost over the planning horizon.

A multi-stage imperfect maintenance strategy for multi-state systems with variable user demands

The main purpose of this paper is to schedule an imperfect maintenance policy for a single unit multi-state system (MSS) exhibiting more than two output states in the duration of its multiple operation stages. Firstly, a nonhomogeneous continuous time Markov chain (NHCTMC) is introduced to describe the state evolution process when the number of external shocks is modeled by a nonhomogeneous Poisson process (NHPP), and state residence probabilities of the Markov process are derived via a proposed recursive algorithm (RA) in solving the Chapman-Kolmogorov (CK) differential equations. Based on those modeling approaches, reliability measures such as the survival function and mean time to first failure (MTTFF) are evaluated where the randomly varied user demands reflecting real industrial applications are taken into consideration. We subsequently put forward a multi-stage imperfect maintenance policy by dividing system output states into three subsets concerning different degrees of degradation, incorporating a condition-based maintenance (CBM) action and a corrective maintenance (CM) activity in each operation stage. It is assumed that the CBM is a minimal repair and the effectiveness of CM is imperfect. The system will not be completely replaced by a brand new one until the number of failures reaches N in light of the investigated maintenance policy, where the expected profit in per renewal cycle is maximized to seek the optimal N analytically. An illustrative example of a bulk power electric system is presented to verify the proposed idea numerically, in which three common types of demand distributions are introduced.

Fleet-Level Selective Dispatch and Imperfect Maintenance Strategy Optimization Based on Evolutionary Co-Petition Game Theory

Fleet-level selective dispatch under imperfect maintenance oriented to mission reliability is a practical, multi-level maintenance strategy decision problem that becomes highly difficult since the number of potential maintenance strategies dramatically increases. In this paper, the fleet-level selective imperfect maintenance model is established, and an evolutionary co-petition game theory based approach is proposed for optimizing the fleet maintenance strategy. During the route of the proposed method, each piece of equipment is considered as a game player, and an evolutionary co-petition game strategy is adopted for the dispatch and standby groups in each game round: a cooperative game strategy with strategy space generation way for the dispatch group to decrease the maintenance cost; and a competition game strategy between the dispatch and standby groups to select the optimal dispatch equipment. And a termination condition is given upon which the optimized maintenance strategy is achieved. A case study is further conducted on a fleet of 15 pieces of equipment under 5-level imperfect maintenance actions, and is compared with numerical simulation method. And the results validate that the proposed method possesses high efficiency and effectiveness in optimizing the fleet-level selective imperfect maintenance planning problem.

A stochastic simulation-optimization model for base-warranty and extended-warranty decision-making of under- and out-of-warranty products

In recent years, product warranties (including base-warranty and extended-warranty) have become an integral part of marketing strategy for most manufacturers as well as and a key determinant of purchasing decision for most customers. It is crucial for manufacturers or dealers who offer warranty to their customers to optimize decisions regarding price of products, durations of base-warranty and extended-warranty, price of extended-warranty, etc. On the other side, manufacturers must decide on a cost-effective imperfect maintenance strategy and spare part inventory policy for their under-warranty and out-of-warranty products. In order to solve these decision-making problems, this study proposes a novel stochastic simulation-based optimization (SBO) model with the objective of maximizing the manufacturer's profit. A metaheuristic Monte-Carlo simulation algorithm integrated with a dynamic programming approach is also presented to solve the model. A case study of vacuum cleaners is provided to illustrate the developed model and its solution procedure, and the simulation results are verified with real data. Finally, a sensitivity analysis is performed in order to evaluate the impact of key parameters on the optimal solution. Our analysis shows how different planning horizons can affect warranty-related decisions for both the manufacturers and customers, providing valuable insights to corporate decision-makers.

Selective Maintenance Optimization Modelling for Multi-State Deterioration Systems Considering Imperfect Maintenance

Motivated by the need to reduce the maintenance cost and improve the system reliability, the issue of selective maintenance has attracted much attention in the industrial and military fields. The existing research mainly focused on binary-state systems or the perfect maintenance strategy. In this paper, we presented a novel selective maintenance model for multi-state deteriorating systems with multi-state components considering imperfect maintenance strategy. The proposed model aims to minimize the total maintenance costs and takes the relationship between the maintenance cost, the system service life and the maintenance quality into account. A case study where the proposed model was applied to an aircraft gas turbine engine system was conducted. The sensitivity analyses for the minimum requirement of the health level, the aging factor, and the number of health states were conducted, respectively. Moreover, a comparative analysis between perfect and imperfect maintenance strategies was conducted, and the results demonstrated that the imperfect maintenance strategy was more cost-effective than perfect maintenance strategy. The findings of this study can guide the maintenance decision-making process for actual systems.

The Study of Imperfect Maintenance Strategy based on Improved Age Reduction Factor

This paper is going to study the maintenance strategy optimization of repairable equipment in the imperfect maintenance mode. By introducing age reduction factor, repairable equipment can effectively describe the effects of imperfect maintenance. For the current age reduction factor is usually given by industry experts without a clear quantitative calculation formula, this paper offers an improved formula on the basis of its definition. The new formula takes not only traditional factors like repair times,costs, etc. but also subjective factors like equipment importance into account. Based on this and NSGA II(the second generation of non-dominated sorting genetic algorithm), the traditional scheduling maintenance strategy tries to solve its model whose objective function includes the maximum reliability, maximum availability, minimum total costs. Finally, by taking the radio relay equipment of mobile communication vehicle as an example to calculate and demonstrate, its validity was proved.

Optimal imperfect maintenance strategy for leased equipment

This paper presents a preventive maintenance (PM) policy for leased equipment over a finite lease period L. Maintenance is entrusted to the lessor. The purpose is to determine the PM period T minimizing the expected total cost over the lease period in a context where repairs and PM actions are imperfect and have non-negligible durations. The leased equipment is periodically subjected to imperfect PM restoring it to the state ‘as good as new’ with probability p and keeping it at state ‘as bad as old’ with probability q. In case of failures between successive PM actions, imperfect repairs are performed with a given efficiency following a decreasing quasi-renewal process. Besides the maintenance costs, the lessor may incur a penalty cost if the total expected equipment downtime due to repair and PM during the lease period exceeds a pre-specified threshold. A mathematical model and a numerical algorithm are developed to find the optimal maintenance strategy T* over the lease period for any given set of input parameters (equipment reliability, the lease period length, the repair and PM efficiency levels, and the maintenance and penalty costs). A numerical example is presented and the obtained results are discussed.

A decision-making framework to integrate maintenance contract conditions with critical spares management

Maintenance outsourcing is a strategic driver for asset intensive industries pursuing to enhance supply chain performance. Spare parts management plays a relevant role in this premise since its significant impact on equipment availability, and hence on business success. Designing critical spares policies might therefore seriously affect maintenance contracts profitability, yet service receivers and external providers traditionally attempt to benefit separately. To coordinate both chain parties, we investigated whether the spare components pool should be managed in-house or contracted out. This paper provides a decision-making framework to efficiently integrate contractual conditions with critical spares stockholding. Using an imperfect maintenance strategy over a finite horizon, the scheme maximizes chain returns whilst evaluating the impact of an additional part to stock. As result, an original joint value – preventive interval and stock level – sets the optimal agreement to profitably allocate the components pool within the service contract. Subsidization bonuses on preventive interventions and pooling costs are also estimated to induce the service provider to adjust its policy when needed. The proposed contractual conditions motivate stakeholders to continuously improve maintenance performance and supply practices, thus obtaining higher joint benefits.

A Joint Redundancy and Imperfect Maintenance Strategy Optimization for Multi-State Systems

The redundancy allocation problem has been extensively studied with the aim of determining optimal redundancy levels of components at various stages to achieve the required system reliability or availability. In most existing studies, failed elements are assumed to be as good as new after repair, from a failure perspective. Due to deterioration, the repaired element cannot always be restored to a virtually new condition unless replaced with a new element. In this paper, we present an approach of joint redundancy and imperfect maintenance strategy optimization for multi-state systems. Along with determining the optimal redundancy levels, the element replacement strategy under imperfect repair is also optimized simultaneously, so as to reach the desired availability with minimal average expenditure. A generalized imperfect repair model is proposed to characterize the stochastic behavior of multi-state elements (MSEs) after repair, and a replacement policy under which a MSE is replaced once it reaches the pre-determined number of failures is introduced. The cost-repair efficiency relation, which regards the imperfect repair efficiency as a function of assigned repair cost, is put forth to provide a flexibility of assigning repair efforts strategically among MSEs. The benefits of the proposed method compared to the existing ones are demonstrated and verified via an illustrative case study of a three-stage coal transportation system.

Optimal burn-in time and imperfect maintenance strategy for a warranted product with bathtub shaped failure rate

'Burn-in/preventive maintenance' programme is an efficient approach used to minimise the warranty servicing cost of a product with bathtub shaped failure rate. Burn-in is a widely used method to improve the quality of product during its 'infant mortality' period and preventive maintenance is a scheduled necessary activity carried out during its 'wear-out' period. In this paper, an optimisation model is developed to determine the optimal burn-in time and optimal imperfect preventive maintenance strategy that minimises the total mean servicing cost of a warranted product with an age-dependent repair cost. We provide a numerical study to illustrate our results.