Optimal Maintenance Level Research Articles

A Maintenance and Energy Saving Joint Control Scheme for Sustainable Manufacturing Systems

Energy saving has always been a major concern in the design and operation of sustainable manufacturing systems. Optimal maintenance strategies have also been explored intensively to achieve manufacturing sustainability. However, in most of the related studies, the two aspects are considered separately. As a manufacturing system is characterized by its complex and stochastic dynamics, there has been a lack of a general methodology to integrate the two important sectors for a sustainable manufacturing system. In this paper, utilizing the data acquired by the distributed sensors, a data-driven model of multi-stage manufacturing system is established. Based on the proposed model, the losses or benefits of conducting maintenance and energy saving are properly evaluated. Based on the proposed real-time maintenance cost rate, the maintenance control can determine the optimal maintenance level, i.e. perfect, imperfect, or minimal, upon random failures. The energy saving is achieved by switching on or off the machines according to system states. The knowledge-guided genetic algorithm is applied to find the optimal energy saving decisions. The proposed joint control scheme is implemented in a real-time manner to achieve resource-effective and energy-efficient production.

A Real-Time Maintenance Policy for Multi-Stage Manufacturing Systems Considering Imperfect Maintenance Effects

Machines are subject to deterioration due to usage and aging. Once one machine fails, maintenance action has to be imposed in order to resume its operation. In practice, maintenance actions are not always able to restore the machine as new. Multi-level maintenance is a more realistic scenario. It is important to select a proper maintenance level upon failure since it directly relates to the duration of a maintenance action and the deterioration status after maintenance and therefore determines the overall system performance. In this paper, a real-time maintenance policy is proposed to select an optimal maintenance level aiming at reducing maintenance-related costs. The maintenance cost includes resource cost and production loss due to machine stoppage. The maintenance cost rate, which is the cost per unit time after the maintenance, is used to select the optimal maintenance level. The maintenance effect is modeled with a virtual-age approach. With the available data collected by distributed sensors, a data-driven modeling of serial production lines is established for analyzing production dynamics. The opportunity window of machine stoppage in the stochastic scenario is derived, which is further used to estimate the production loss caused by the machine stoppage due to maintenance. A numerical experiment is conducted to validate the proposed maintenance policy.

Optimal maintenance level of equipment with multiple components

Purpose – The purpose of the paper is to provide a method for selection of an optimum level of repair by replacement of an equipment based on its cost. In a ship where the engineer has a vast variety of equipment and systems to operate and maintain within limited time frames and availability of human resources, it is often difficult to disassemble a whole equipment to replace a faulty component. It is instead a lot easier to just replace the faulty equipment with whole new equipment. However, such a decision comes at an enormous capital cost. Therefore, the key question is, can we have a model to help us arrive at a decision on the correct level of carrying out repairs? Design/methodology/approach – The paper uses a model based on cost and convolution of failure distributions of critical sub-components of an equipment. Necessary assumptions based on real life experience have been incorporated in the model. Findings – The paper used an example of a particular type of motor driven sea water centrifugal pump which was commonly used in main engine sea water system, firefighting system, air conditioning system, etc. The pump had one of the highest failure rates in the ship (approximately one failure per 150 days) and the engineers found it cost and time effective to replace the entire pump on failure rather than carrying out replacement of the failed components. The model analyzed that the engineer’s hunch was not off the mark. Research limitations/implications – The implication of the work presented in the paper will be savings in maintenance cost and downtime due to optimal level of repairs on a multi-component equipment. The limitations of the work are assumption of independence of failures of components. This may not be true in all the cases. Further, opportunity based maintenance has also not been considered. Originality/value – The originality of the paper lies in the presentation of a method for selection of an optimum level of maintenance for a multi-component equipment

An Optimization Model for Condition-Based Maintenance Decision Considering Total Risk of Grid Operation

In the background of condition-based maintenance (CBM), the equipment maintenance levels in a certain state have different choices, which has different impacts on the improvement of the equipment state and maintenance costs, which in turn affects the time schedule of equipment maintenance. Therefore, in this paper the equipment maintenance time and maintenance level are viewed as decision variables to make maintenance schedules. This paper presents a risk-based optimization model for system maintenance scheduling problem, considering the state of equipment, correlations of the equipment and the operation of grid. An optimization model minimizing total risk of grid operation by balancing system maintenance risk and failure risk is established, so that both optimal maintenance level and optimal maintenance time could be determined simultaneously. An example is taken to verify the validity of the model.

A value-based preventive maintenance policy for multi-component system with continuously degrading components

A dynamic preventive maintenance policy for system with continuously degrading components is investigated in this paper. Different from traditional cost-centric preventive maintenance policy, our maintenance strategy is formulated from the value perspective. Component value is modelled as a function of component reliability distribution. Maintenance action is triggered whenever the system reliability drops below a certain threshold. Our policy mainly consists of two steps: (i) determine which component to maintain; (ii) determine to what degree the component should be maintained. In Step 1, we introduce the yield-cost importance to select the most important component. In Step 2, the optimal maintenance level is obtained by maximizing the net value of the maintenance action. Finally, numerical examples are given to illustrate the proposed policy.

Optimal maintenance level for second‐hand product with periodic inspection schedule

This paper formulates a periodic inspection/upgrade model under free non‐renewable warranty policy with a fixed length of warranty period for the second‐hand product and derives an optimal number of inspections required and an optimal improvement level to minimize the expected total warranty cost from the perspective of the dealer during the warranty period. At each inspection, the product is taken an upgrade action in order to reduce its failure rate, which is characterized by an improvement level. It is true in general that the higher improvement level and more frequent inspections increase the warranty cost but lower the chance of product failures. In this paper, we propose an optimal strategy with respect to the inspection/upgrade action for the dealer to lower the total warranty cost. Firstly, we define an inspection/upgrade action, which reduces the product's failure rate proportionally to the improvement level at each inspection and then evaluate the expected total warranty cost. Secondly, the optimal solutions for the decision variables and its uniqueness are discussed in general. Numerical results are presented when the failure distribution follows a Weibull distribution under the proposed model. Copyright © 2014 John Wiley & Sons, Ltd.

Maintenance of multi-state production systems deteriorated by random shocks and production

We consider the preventive maintenance of a production system that is deteriorated by random shocks and the production process itself. The degree of deterioration is modeled by discrete and finite states. Shocks arrive according to a Poisson process and deteriorate the system by random amounts. The system may deteriorate whenever it produces an item. The system is continuously monitored and repaired if the system state is at or above a predetermined level for maintenance. We analyze the lifetime, product quantity, average cost, and average profit considering revenue from the product and cost due to setup, operation, and repair. Assuming a structure of system parameters and costs, using numerical examples, we investigate the impact of production and shock arrivals on the average profit and the optimal maintenance level that maximizes the average profit. The proposed model is applicable to manufacturing tasks in which machines wear due to production, for example, press processes, milling, turning, punching, and drilling.

Optimal Predictive Maintenance Policies for a Deteriorating System: The Total Discounted Cost and the Long-Run Average Cost Cases

A predictive maintenance policy for a system subject to degradation is considered. Over time, the system is subject to degradation. The degradation level is observed only at successive inspection times. The system has a nominal life Y, and it fails once the degradation exceeds the nominal life. Failure is detected only by inspection, and is then maintained (corrective maintenance). The system is also maintained when the degradation level exceeds a predetermine level M(preventive maintenance). Each preventive maintenance costs c 1, while the cost of a corrective maintenance is equal to c 1 + d, d ≥ 0. At any inspection, before failure, the cost of inspection is state dependent: if the degradation level at inspection is x, then an inspection cost of c(x) occurs. We determine the optimal maintenance level M using the total discounted cost as well as the long-run average cost criteria. Our results extend those of Grall et al. [Grall, A., Dieulle, L., Berenguer, C., Roussignol, M. (2002). Continuous-time predictive-maintenance scheduling for a deteriorating system. IEEE Trans. Reliability 51:141–149].

Integrated production maintenance and quality model for imperfect processes

In this paper, we develop an integrated model for the joint optimization of the economic production quantity, the economic design of X¯-control chart, and the optimal maintenance level. This is done for a deteriorating process where the in-control period follows a general probability distribution with increasing hazard rate. In the proposed model, Preventive Maintenance (PM) activities reduce the shift rate to the out-of-control state proportional to the PM level. Compared to the case with no PM, the extra cost of maintenance results in lower quality control cost which may lead to lower overall expected cost. These issues are illustrated using an example of a Weibull shock model with an increasing hazard rate.

Integrated production maintenance and quality model for imperfect processes

In this paper, we develop an integrated model for the joint optimization of the economic production quantity, the economic design of x¯-control chart, and the optimal maintenance level. This is done for a deteriorating process where the in-control period follows a general probability distribution with increasing hazard rate. In the proposed model, Preventive Maintenance (PM) activities reduce the shift rate to the out-of-control state proportional to the PM level. Compared to the case with no PM, the extra cost of maintenance results in lower quality control cost which may lead to lower overall expected cost. These issues are illustrated using an example of a Weibull shock model with an increasing hazard rate.

NETWORK BASIS OPTIMAL MAINTENANCE STARATEGY OF FLEXIBLE PAVEMENTS BASED ON THE CONCEPT OF REPAIRED RATIO

In this paper, applications of Markovian transition probability model to decision of optimal maintenance strategy of flexible pavements on network basis are discussed.The optimal maintenance strategy at the project level is formulated based on both dynamic progrmming and the equivalent annual maintenance cost. These two methods give the exactly same optimal maintenance level for the minimum long-run expected average cost.Introducing the concept of repaired ratio, the optimal strategy at the network level is formulated as budget allocation problem by expansion of the equivalent annual maintenance cost model at the project level.