Optimal Maintenance Frequency Research Articles

Research on an Optimal Maintenance and Inventory Model Based on Carbon Tax Policy

The equipment in a factory will gradually deteriorate during production, leading to the production of defective products. Without appropriate maintenance, the defect rate will increase over time. Consequently, the production cost will rise, the inventory quality will be affected, the profit will decrease, and the risk of carbon emissions will increase, leading to more customer complaints and damaging the corporate image. In addition to focusing on preventive maintenance to ensure the quality of products, companies should also take carbon emissions into consideration. Furthermore, the frequency of maintenance must be carefully considered, as both carbon emissions and maintenance costs will increase if the frequency is too high; conversely, if the maintenance frequency is too low or non-existent, the defect rate may increase cumulatively, or production may be suspended due to equipment failure. Therefore, this research explores preventive maintenance and inventory management issues within an imperfect production system and develops an extended economic production quantity model that incorporates defective products as well as taking carbon tax and preventive maintenance into consideration. The main purpose is to determine the optimal maintenance frequency, production, and replenishment cycle length, so as to maximize the total profit under the carbon tax policy. This study demonstrates a computing process with relatively impractical product data based on the actual business situation of a disposable diaper manufacturer. Furthermore, a sensitivity analysis is implemented to the model parameters in the proposed model. The managemental insights are illustrated based on the results of theoretical analysis to provide a reference to policy makers during decision making, hence, to secure the sustainability and green transitions of corporates. The results of this study not only help to reduce environmental impact but can also improve the competitiveness and sustainable development of enterprises.

Ensuring the Reliability of Gas Supply Systems by Optimizing the Overhaul Planning

The aim of the article is the development of methods for optimal overhaul planning of compressor station equipment. Nowadays, due to uncertainties in the forecast of gas supply flow rates, increasing the reliability and energy efficiency of main gas pipelines is an urgent problem. The dependence of operating costs for major repairs on the maintenance periodicity is extreme. Reducing equipment’s maintenance period leads to an increase in repair costs. It also increases the reliability of equipment operation. Overall, all these facts reduce the probability of emergency failures and related expenses for emergency recovery, gas losses, and undersupply to consumers. Therefore, an optimal maintenance frequency exists, at which the total operating costs will be minimal. A procedure for optimizing the periodicity of repairs and equipment replacement is proposed. It was realized by constructing an objective function as a dependence of exploitation costs on the inter-repair period of major repairs. A probabilistic approach was applied to assess the aging process. The characteristics of the equipment’s state are described by distribution densities (i.e., pre-repair, inter-repair, and full-service life), which vary depending on product initialization time. The main characteristics of major repairs are their duration and intensity, which are evaluated by the quality factor related to repair costs. The extremum of the objective function is sought by the method of competing options. It was determined that the optimal management of the frequency of equipment replacement can be realized by choosing the optimal values of the average service life, average operation time of units until the first planned and preventive repair, and quality factor. As a result, the required technical condition for the technological equipment is ensured under minimum operating costs without reducing the system’s reliability.

Integrated maintenance planning approach to optimize budget allocation for subway operating systems

Millions of citizens worldwide heavily rely on subways as their main public transportation approach. However, public transit infrastructures are generally facing extensive deterioration that requires extensive funds by governments to retain back the desired performance levels. The real case is that most governments are heavily facing a budget scarcity dilemma, and cannot withstand the acquired maintenance costs to maintain a proper operation for subway network. This research aims at introducing a new risk-based multi-objective optimization framework for optimizing performance and budget allocation among subway systems in fulfillment to maintenance planning development in this domain. This would extensively ease the decision-making process for subway asset managers by providing the optimal allocated budget for each subway system in an automated way. The framework targets the vital subway operating systems, namely: railway tracks, overhead catenary, lighting & power supply, centralized control, communication, signaling, rolling stock, and ticketing. The research framework develops four main modules; Reliability Centered Maintenance Database, Deterioration Modelling, Multi-objective Optimization, and Decision-Making. Reliability Centered Maintenance Database where subway operating systems are decomposed to components levels showing their functions, operational failures, failure causes, failure effects, failure consequences, responsive maintenance actions, and the hourly maintenance costs. Deterioration Modeling using deterministic and artificial intelligence models to estimate future conditions of subway components. Multi-objective optimization, and decision-making are developed to decide the optimal maintenance frequencies that derive lowest maintenance costs and lowest risk of failure for each functional failure. An actual case-study is worked out to verify the proposed framework. The results reveal the greatest share of the maintenance budget was allocated to lighting & power supply rectifier station with a 54% of the total maintenance budget, followed by rolling stock system with 32%, railway tracks system with 7%, signaling system with 3%, and approximately 1% for each of the remaining systems.

AFMT: Maintaining the safety-security of industrial control systems

Modern day industrial control systems are overwhelmingly complex. These systems feature intricate interactions between the cyber and the physical components. At the same time, they need to be trustworthy and deliver their services continuously. Underpinning, a crucial industrial activity to ensure the dependability of such critical systems is through timely maintenance, inspections and repairs. Several strategies exist here: “fix it when it breaks” (reactive maintenance), monitor and maintain a system in pre-established time intervals (preventive maintenance), preventive action based upon detected symptoms of failures condition-based maintenance (CBM), etc. In literature, the question of optimal maintenance frequency have been a subject of intense study. However, most papers, do not take information security aspects into account. This paper provides an automated tool-supported quantitative risk analysis framework, Attack-Fault-Maintenance Trees, AFMTs, that will enable practitioners to make informed choice on: (a) identifying the critical component(s) necessary for uninterrupted systems; (b) a decision support system that will provide informed choices on policy measures, countermeasures and safeguards that will reduce the disruptions; (c) run the “what-if” scenarios to find the optimal trade-offs between system attributes (safety, security, usability and maintenance). The front-end of the tool is a domain-specific language geared to represent the system architecture using graphical-constructs. The back-end of the framework remains hidden to the practitioner. It consists of a mathematical engine based on statistical model-checking techniques. A case study of oil-pipeline is used to demonstrate the efficacy of our framework.

Improvement of maintenance and repair system of internal combustion engines of automotive equipment

The paper analyzes the operating conditions of road transport affecting its reliability. It is concluded that it is necessary to develop scientifically based strategies flexible of AE maintenance based on predicting the failure moment by extrapolating the process of time drift of the informative parameters of the AE at the interval of its intended use. To solve this problem, we propose an approach based on the use of quasi-deterministic models of the time drift of the AE parameters, which allow to obtain analytical expressions for the main reliability indicators -density of the distribution time to failure and the probability of failure -free operation at a given time interval. On the basis of these indicators of reliability in operation, performance indicators have been formed allowing determining of the optimal maintenance frequency. In the final part of the article, the author proposes an algorithm and a methodology that allows organizing flexible strategies for AE maintenance, considering special conditions of its operation.

Unrelated Parallel-Machine Scheduling with Maintenance Activities and Rejection Penalties for Minimizing Total Cost

During the production process, regular maintenance is necessary and important to maintain high efficiency, because machines inevitably fail with increasing use. However, certain tasks are often neglected due to time and budget constraints, and other factors. In this regard, we propose the unrelated parallel-machine scheduling problem with maintenance and rejection penalties, wherein the ultimate objective is to minimize total cost while identifying the optimal maintenance frequencies, optimal maintenance positions, set of rejected jobs, and optimal scheduled job sequence. Considering resource constraints, the maintenance cost is controlled by the upper bound of the total maintenance frequency. Based on these factors, the optimal polynomial-time solution and its computational complexity with a fixed number of machines are presented. As an illustrative example, it was determined that the scheduling method proposed in this report is effective and practical.

Improving decision-making in maintenance policies and contract specifications for infrastructure projects

In large infrastructure projects, the government frequently delegates the execution and management to a private through Public–Private Partnerships (PPP) type contract. However, both parties often have conflicting interests; i.e. while the private wants to maximise the profit, the government aims at maintaining a high-performance level. This paper presents a model to define a set of contract parameters that maximise the utility of both entities in the long term, and at the same time optimise the system performance. Moreover, it proposes a strategy for the private to decide the optimal maintenance frequencies and achieve its target revenue. It also describes the complex interactions between the public, the private and nature (i.e. all environmental aspects that influence the system’s performance). The model combines the advantages game theory, simulation, optimisation and agent-based modeling. A set of 72 types of Build-Operate-Transfer (BOT) contracts are simulated, with a sensitivity analysis on the main contract variables (i.e. minimum level of performance required, mean frequency of government inspections, and penalty fee in case of noncompliance). The results show the importance of flexibility in decisions when facing different sources of uncertainty, and in reducing information asymmetry between the parties to improve maintenance decisions.

Unrelated Parallel Machines Scheduling with the Effect of Aging and Learning under Multi Maintenance Activities

Maintenance is important to manufacturing process with a view to sustaining production efficiency. In this study scheduling of unrelated parallel machines with effects of learning and aging and multi maintenance activities is considered. The objective is to find the optimal maintenance periods, optimal maintenance frequencies and optimal job sequences such that the makespan of all jobs are minimized. Polynomial algorithm is provided and two hueristic algorithms are presented. Computational experiments are conducted to evaluate their performances.

JIT-scheduling in unrelated parallel-machine environment with aging effect and multi-maintenance activities

In this paper, at first we present a new integer linear programming (ILP) model for the parallel-machine scheduling problem with aging effects and multi-maintenance activities simultaneously. A machine returns to its initial condition after each maintenance and the aging effects start a new one. The objective is to find jointly the optimal maintenance frequencies, the optimal positions of the maintenance activities and the optimal job sequences on the machines, such that the total early/tardy and maintenance cost be minimised. Since, this case problem is NP-hard so we provide a Genetic algorithm (GA)for it and the effectiveness of these approaches is evaluated by solving a large number of problem instances.

Single-Machine Scheduling with Job Rejection, Deteriorating Effects, and Deteriorating Maintenance Activities

This paper addresses the single-machine scheduling problems with simultaneous considerations of job rejection, deterioration effects, and deteriorating multimaintenance activities. A job is either rejected, in which case a rejection penalty has to be paid, or accepted and processed on the single machine. Three deterioration effect models are investigated, and it is assumed that each machine may be subject to several maintenance activities over the scheduling horizon, and the duration of the maintenance depends on its running time. Moreover, due to the restriction of the budget of maintenance, the upper bound of the total maintenance frequencies on the machine is assumed to be known in advance. The objective is to find jointly the optimal accepted job set, the optimal maintenance frequencies, the optimal maintenance positions, and the optimal accepted job sequence such that the cost function based on the total completion time and rejection penalty is minimized. It is shown that all the versions of the problem under study are polynomial time solutions.

Single-Machine Scheduling with Upper Bounded Maintenance Time under the Deteriorating Effect

We consider a single-machine scheduling problem with upper bounded actual processing time and upper bounded maintenance time under deteriorating effect. The actual processing time of a job is a position-dependent power function. If the actual processing time of a job exceeds the upper bound, tardiness penalty of the job should be paid. And if the maintenance time exceeds the corresponding upper bound, tardiness penalty of the maintenance should also be paid. The maintenance duration studied in the paper is a position-dependent exponential function. The objective is to find jointly the optimal maintenance frequency and the optimal job sequence to minimize the total cost, which is a linear function of the makespan and the total tardiness. We show that the studied scheduling problem can be transformed as a classic assignment problem to solve. There is also shown that a special case of the scheduling problem can be optimally solved by a lower order algorithm.

Unrelated parallel-machine scheduling with deterioration effects and deteriorating multi-maintenance activities for minimizing the total completion time

This paper investigates scheduling problems with simultaneous considerations of deterioration effects and deteriorating multi-maintenance activities on unrelated parallel machines. We examine two models of scheduling with the deterioration effect, namely the job-dependent and position-dependent deterioration model and the time-dependent deterioration model. We assume that each machine may be subject to several maintenance activities over the scheduling horizon, and the duration of maintenance on a machine depends on its running time. Moreover, due to the restriction of the budget of maintenance, the upper bound of the total maintenance frequencies on all the machines is assumed to be known in advance. The objective is to find jointly the optimal maintenance frequencies, the optimal maintenance positions, and the optimal job sequences such that the total completion time is minimized. If the number of machines is fixed, we introduce polynomial time solutions for all the versions of the problem under study.

Single-machine scheduling problems simultaneously with deterioration and learning effects under deteriorating multi-maintenance activities consideration

Maintenance is important to manufacturing process as it helps improve the efficiency of production. Although different models of joint deterioration and learning effects have been studied extensively in various areas, it has rarely been studied in the context of scheduling with maintenance activities. This paper considers scheduling with jointly the deterioration and learning effects and multi-maintenance activities on a single-machine setting. We assume that the machine may have several maintenance activities to improve its production efficiency during the scheduling horizon, and the duration of each maintenance activity depends on the running time of the machine. The objectives are to determine the optimal maintenance frequencies, the optimal maintenance locations, and the optimal job schedule such that the makespan and the total completion time are minimized, respectively, when the upper bound of the maintenance frequencies on the machine is known in advance. We show that all the problems studied can be solved by polynomial time algorithms.

Unrelated parallel-machine scheduling with aging effects and multi-maintenance activities

Machine maintenance is often performed in manufacturing to prevent premature machine failures with a view to sustaining production efficiency. In this paper we study the parallel-machine scheduling problem with aging effects and multi-maintenance activities simultaneously. We assume that each machine may be subject to several maintenance activities over the scheduling horizon. A machine reverts to its initial condition after maintenance and the aging effects start anew. The objective is to find jointly the optimal maintenance frequencies, the optimal positions of the maintenance activities, and the optimal job sequences such that the total machine load is minimized. We apply the group balance principle to obtain the optimal positions of the maintenance activities and the number of jobs in each group in the scheduling sequence on each machine. We provide an efficient algorithm to solve the problem when the maintenance frequencies on the machines are given.

Minimizing the total completion time in single-machine scheduling with aging/deteriorating effects and deteriorating maintenance activities

In a real manufacturing system, a machine may need multiple maintenance activities to improve its production efficiency due to the effects of aging or deteriorating. This paper considers scheduling with aging or deteriorating effects and deteriorating maintenance activities simultaneously on a single machine. We assume that the machine may be subject to several maintenance activities during the planning horizon. However, due to the restriction of budget of maintenance, the upper bound of the maintenance frequency on the machine is assumed to be known in advance. Moreover, we assume that the duration of each maintenance activity depends on the running time of the machine. The objective is to find jointly the optimal maintenance frequencies, the optimal maintenance positions, and the optimal job sequence for minimizing the total completion time. We show that all the problems studied are polynomially solvable.

Optimization of Preventive Maintenance Policies for Aging Equipments in Finite Time Horizon

The recursion relationship between the failure rate and the equipment age before and after preventive maintenance (PM) was built up concerning with the concept of improvement factor. The optimal imperfect PM policy model in finite time horizon of the aging equipments following Weibull distribution was proposed, which can minimize the total relative cost of the equipment PM. The optimal maintenance frequency and optimal maintenance interval under imperfect maintenance were determined by the model, and the reliability after each PM of equipments was considered. The model built in this paper can be used the decision supporting the maintenance plan and providing decision supporting for job shop scheduling.

Minimizing the makespan on single-machine scheduling with aging effect and variable maintenance activities

This paper considers a single-machine scheduling with a position-dependent aging effect described by a power function under maintenance activities and variable maintenance duration considerations simultaneously. We examine two models of the maintenance duration in this study. The objective is to find jointly the optimal maintenance frequency, the optimal maintenance positions, and the optimal job sequences to minimize the makespan of all jobs. We provided polynomial time solution algorithms for all the studied problems.

Coverage Modeling and Optimal Maintenance Frequency of an Automated Restoration Mechanism

In this paper, the coverage modeling of an automated restoration mechanism with two components is studied, and optimal maintenance frequencies are determined. Failures and repairs are exponentially distributed for the two components, while the failures of the automated mechanism follow a Weibull distribution. A corrective maintenance policy is considered for each component whereas, for the automated restoration mechanism, an additional preventive maintenance is taken into account. The system is modeled with a continuous time Markov chain and two performability indicators: one performability indicator modeling the downtime, and a second one modeling the overall operational cost. Consequently, two optimal maintenance frequencies are derived: first by minimizing the downtime, and second by minimizing the overall operational cost. A numerical example is used to evaluate the applicability of the proposed method.

Application of Bayesian statistical decision theory for a maintenance optimization problem

Reliability-centered maintenance (RCM) is a rational approach that can be used to identify the equipment of facilities that may turn out to be critical with respect to safety, to availability, or to maintenance costs. Is is dor these critical pieces of equipment alone that a corrective (one waits for a failure) or preventive (the type and frequency are specified) maintenance policy is established. But this approach has limitations: • •when there is little operating feedback and it concerns rare events affecting a piece of equipment judged critical on a priori grounds (how is it possible, in this case, to decide whether or not it is critical, since there is conflict between the gravity of the potential failure and its frequency?); • •when the aim is propose an optimal maintenance frequency for a critical piece of equipment - changing the maintenance frequency hitherto applied may cause a significant drift in the observed reliability of the equipment, an aspect not generally taken into account in the RCM approach. In these two situations, expert judgments can be combined with the available operating feedback (Bayesian approach) and the combination of risk of failure and economic consequences taken into account (statistical decision theory) to achieve a true optimization of maintenance policy choices. This paper presents an application on the maintenace of diesel generator component.