Maintenance costs are one of the major costs in plants and companies. The observation in many cases illustrates the lack of plans or mistakes in Maintenance activities that incurred great costs. In this study, the number of equipment failures have been determined. Then the failure rate and reliability of each equipment are calculated. The third step calculates total system reliability so the initial plan is presented. After that, by using the obtained information, the sustainability aspects of the program will generate and the Maintenance costs and sustainability functions will assess. At the end, this multi-objective Optimization problem is solved by MOPSO algorithm and the results are compared with a simulation method. As a result, with this reliability centered Maintenance program, the reliability of each equipment, as well as the whole system are improved; economic aspect of sustainability and customer satisfaction are increased; environmental pollutions and Maintenance costs are decreased by offering more reliability based program; a scheduling plan for each Maintenance procedures is provided and also more stable internet connection is established by reducing the system failures.

In this paper, recommended spiral passive micromixer was designed and simulated. spiral design has the potential to create and strengthen the centrifugal force and the secondary flow. A series of simulations were carried out to evaluate the effects of channel width, channel depth, the gap between loops, and flowrate on the micromixer performance. These features impact the contact area of the two fluids and ultimately lead to an increment in the quality of the mixture. In this study, for the flow rate of 25 μl/min and molecular diffusion coefficient of 1×10-10 m2/s, mixing efficiency of more than 90% is achieved after 30 (approximately one-third of the total channel length). Finally, the optimized design fabricated using proposed 3D printing method.

Application of the network equivalent concept for external system representation for power system transient analysis is well known. However, the challenge to utilize an equivalent network, approximated by a rational function, is to guarantee the passivity of the corresponding model. In this regard, special techniques are required to enforce the passivity of the equivalent model through a post processing approach that minimizes its impact on the original model characteristics. In this paper, the passivity is enforced by expressing the problem in terms of a convex Optimization problem that guarantees the global optimal solution. The convex Optimization problem is efficiently solved by recently developed numerical interior–point methods. This passivity enforcement is also global which indicates that the passivity enforcement in one region does not lead to passivity violation in other regions.

The reliability of designing systems such as electrical and electronic circuits, power generation/ distribution networks and mechanical systems, in which the failure of a component may cause the whole system failure, and even the reliability of cellular manufacturing systems that their machines are connected to as series are critically important. So far approaches for improving the reliability of these systems have been mainly based on the enhancement of inherent reliability of any system component or increasing system reliability based on Maintenance strategies. Also in some of the resources, only the influence of the location of systems' components on reliability is studied. Therefore, it seems other approaches have been rarely applied. In this paper, a multi criteria model has been proposed to perform a balance among a system's reliability, location costs, and its system Maintenance. Finally, a numerical example has been presented and solved by the Lingo software.

Risk management and technical integrity of air systems are critical in the aviation industry. Maintenance grouping, as one of the main risk management tools in the aviation industry, refers to activities aimed at maintaining and improving the technical integrity or reducing the risk of maintaining aviation systems. Since there may be a set of equipment and parts in an air system that need Maintenance or repair, Optimization of Maintenance grouping can improve performance and increase the safety and technical accuracy of the air system. This article will analyze and review the Optimization methods of Maintenance grouping in air systems. First, the importance of risk management and the technical accuracy of air systems will be examined, and then a detailed description of the Maintenance grouping steps will be discussed. In the following, various Optimization methods and algorithms used to improve Maintenance grouping performance will be reviewed. Then, the advantages and limitations of each method will be discussed. In the end, the results of this research and its critical implications will be evaluated, and suggestions will be made to optimize Maintenance grouping in air systems. The study results show that the genetic algorithm can improve resource utilization, scheduling efficiency, and cost reduction in Maintenance grouping. This can significantly benefit the aviation industry, as it can help reduce costs, improve aircraft availability, and enhance safety.

All bridges designed by kind of structure and built by any type of materials، get burnt out sooner or later. These exhaustions are spread due to several factors such as atmospheric conditions، flood or earthquakes، increased over load more than expected in design phase، design and execution quality، and the type of materials affecting that causes to decrease bridge's useful life if these factors will be ignored. Therefore، bridge Maintenance makes to increase its useful life if it happens on time. In this paper، Mazandaran province bridges are studied based on failure situation، faults of each bridges، their condition against traffic load and other effective variables. in order to solve the problem، first، required data have been collected by field study after bridges inspection and then bridges are prioritized based on fault evaluation criteria by Analytic Hierarchy Process (AHP) multi attribute decision making method. Finally، corrective actions are determined based on budget level for bridges. To achieve this goal، a linear mathematical programming model firstly presented and then to solve the large scale problem a genetic algorithm has been developed to find the optimal corrective actions. The proposed algorithm is implemented in MATLAB software and results show that the proposed genetic algorithm have suitable performance to solve the problem. Several budget levels have been considered to assess proposed genetic algorithm validation and changing trend of corrective actions number has been studied. It is seen that amount of effectiveness and total number of repairs are increased by soaring budget level

Maintenance plan efficacy traditionally prioritizes long-term predicted Maintenance cost rates, emphasizing performance-centric approaches. However, such criteria often neglect the fluctuation in Maintenance costs over renewal cycles, posing challenges from a risk management perspective. This study challenges conventional solutions by integrating both performance and robustness considerations to offer more suitable Maintenance options. The study evaluates two representative Maintenance approaches: a block replacement strategy and a periodic inspection and replacement strategy. It introduces novel metrics to assess these approaches, including long-term expected Maintenance cost rate as a performance metric and variance of Maintenance cost per renewal cycle as a robustness metric. Mathematical models based on the homogeneous Gamma degradation process and probability theory are employed to quantify these strategies. Comparative analysis reveals that while higher-performing strategies may demonstrate cost efficiency over the long term, they also entail greater risk due to potential cost variability across renewal cycles. The study underscores the necessity for a comprehensive evaluation that balances performance and resilience in Maintenance decision-making. By leveraging the Monte Carlo Method, this research offers a critical appraisal of Maintenance strategies, aiming to enhance decision-making frameworks with insights that integrate performance and robustness considerations.

In this paper, we have developed a novel approach to reliability Maintenance of one-shot systems such as military missiles and rockets. The reliability estimation and Maintenance of these stretegic products are crucial and challenging, and the area has not yet been fully developed. In our new approach, we take a sample of the finished products and deconstruct it into their parts. These parts are then further divided, according to their intrinsic nature, into the class of testable parts with destruction, the class of testable parts without destruction and the class of non-testable parts. We have considered that the first two classes of parts have increasing rate of failure, while the third class of parts has a constant rate of failure. We apply destructive and non-destructive tests according to the state-of-the-art testing technology and the cost associated with it. We then have integrated concepts and techniques from Maintenance planning, condition monitoring, Genetic Algorithm, Bayesian method, and variance propagation to optimize the relibility of standing products. From maintenace planning, we find the optimal inspection period. From condition monitoring, we learn how to perform non-destructive tests. By using genetic algorithm, we estimate nea-optimal number of samples for each part. Also, Bayesian method is used to estimate the system reliability when the sample size is small which is the case for one-shot systems. In fact, through Baysian process, the reliability information obtained by the new tests is integrated into the prior estimations in order to minimize the sample size. Finally, by variance propogation technique, we communicate the mean and variance data estimated at the lower part level up to higher level of sub systems and the total system. This new approach enables us to estimate the reliability of the total system using the reliability information of the constituent parts. Our aim is to maintain the reliability of stand-pile products while the life cycle cost is also minimized. We have tested the proposed approach on the sounding rocket separation system of the explorer missile system built in Iran.