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The presented studies made it possible to clarify the calculation model of the diesel engine clutch with packages of sleeve springs. The stressed state of the spring packets is considered, while it is proposed to place the point of application of the radial force, which bends the spring package, in the zone of its greatest flexibility. Calculations performed according to the obtained expressions showed a coincidence with the results of experimental studies by other authors within 4% and with simulations conducted using automated design systems.

Software maintenance is a time-consuming and costly endeavor. As a part of maintenance, refactoring is aimed at enhancing quality. Due to project deadlines and limited resources, developers need to prioritize refactoring activities. In this paper, we present a livestock management-inspired approach for identifying and prioritizing classes to refactor within an object-oriented program. This approach empowers developers to enhance the time/quality ratio. The novelty of our approach lies in utilizing established metrics for detecting code defects to prioritize each class. To validate its effectiveness, the approach was tested on four distinct Pharo-based open source programs. The results demonstrate the approach's efficacy in improving software quality, reducing development time, and enhancing team productivity

This paper presents a method of equipment demonstration AoA method considering RMS factors. It puts forward the equipment demonstration AoA framework, and elaborates equipment demonstration AoA measure system. It analyses the RMS and cost factors, and establishes their quantitative models. An AoA model based on Data Envelopment Analysis (DEA) and an application example are given to illustrate the feasibility and effectiveness of the method.

This research project aims to improve a power plant maintenance program by using the theory of RAM (Reliability Availability and Maintainability). A North Bangkok Combined Cycle Power Plant, especially a steam turbines power plant, is selected to conduct research from 2021 to 2022. The steps of this research can be separated into 2 phases as follows; the first phase involves root cause analysis from failure notifications stored in the CMMS-KKS code database and risk prioritization. Unit C10 and the compressed air unit system in steam turbines operation are the critical systems subsequently, the RAM approach is applied to improve a preventive maintenance program of unit C10 by estimating an operation time before failure, system availability, and the ability to repair. RAM information is brought to reschedule a PM program, for example, MTTF, MTTR, failure rate, and repair rate, etc. It is found that the percentage of unit C10 system reliability, R(t), and availability, A(t), are higher than 90%. Furthermore, the trade-off between the cost of maintenance and failure for unit C10 is decided by running unit C10 at a percentage of reliability of 88% which can schedule a maintenance interval every 300 hours

Purpose – This study aims to introduce the achievements and benefits of applying wheel/rail-force–based maintenance interval extension of the C80 series wagon in China. Design/methodology/approach – Chinese wagons' existing maintenance strategy had left a certain safety margin for the characteristics of widely running range, unstable service environment and submission to transportation organization requirements. To reduce maintenance costs, China railway (CR) has attempted to extend the maintenance interval since 2020. The maintenance cycle of C80 series heavy haul wagons is extended by three months (no stable routing) or 50,000 km (regular routing). However, in the meantime, the alarming rate of the running state, a key index to reflect the severe degree of hunting stability, by the train performance detection system (TPDS) for the C80 series heavy haul wagons has increased significantly. Findings – The present paper addresses a big data statistical way to evaluate the risk of allowing the C80 series heavy haul wagons to remain in operation longer than stipulated by the maintenance interval initial set. Through the maintenance and wayside-detector data, which is divided into three stages, the extension period (three months), the current maintenance period and the previous maintenance period, this method reveals the alarming rate of hunting was correlated with maintenance interval. The maintainability of wagons will be achieved by utilizing wagon performance degradation modeling with the state of the wheelset and the often-contact side bearing. This paper also proposes a statistical model to return to the average safety level of the previous maintenance period's baseline through correct alarming thresholds for unplanned corrective maintenance. Originality/value – The paper proposes an approach to reduce safety risk due to maintenance interval extension by effective maintenance program. The results are expected to help the railway company make the optimal solution to balance safety and the economy.

The focus on maintenance actions in the early design phases has been a trend in recent years. The main sources of information during the design of the maintainability process include operator reports, maintainer experience, failure history, and manufacturer recommendations. During this process, an important aspect is related to the configuration of maintenance tasks and interventions, such as their main phases, activities, and durations. The allocation or estimation of maintainability involves identifying and/or estimating the mean time to repair (MTTR) for each component or system. The time of the maintenance tasks or the repair time are fundamental for companies, as the availability of equipment directly depends on this parameter. In this study, a new method for evaluating maintainability during the design phases is proposed. The method is based on the integration of the maintenance task analysis (MTA) principles and the UNE 151001 maintainability evaluation standard. A data structure is proposed that serves the application of the UNE151001 procedures, obtaining a data-based maintainability evaluation. As a validation procedure, an application of the proposed approach is presented using two overhead cranes. Comparisons and recommendations are made regarding the maintainability of both pieces of equipment. Finally, some managerial and engineering insights are presented.

Maintenance concerns most of the artifacts, referring simultaneously to the socio-cultural, technical and managerial spheres. Contemporary scenarios impose an overall rethinking, where key-topics such as tradition, consumerism, sustainability and digitization become pivotal in the search for suitable production models, between post-industrial and neo-craftsmanship, in order to have fresher references for the maintenance activities. In the construction field, maintenance is not limited to the objective of prolonging the duration of quality levels that only affect direct users, but also has important implications of a social and collective nature, in the case of both public and private buildings and spaces. Despite this and other specific features, the parallelism between building maintenance and manufacturing maintenance was fundamental in the last quarter of the 20th century, when the subject made its way into the technological culture of architecture, in search of references that could replace pre-industrial habits. In support of the theoretical rethinking of maintenance (an activity which, like the Sisyphean task, does never foresee a definitive completion), the article suggests some considerations referring in particular to the reinforced concrete: a structural material almost omnipresent in the built environment since the second half of the last century, which poses significant problems in terms of duration and not only. In conclusion, some possible developments are presented, distinguishing between newly constructed and existing reinforced concrete constructions.

Abstract In software engineering, a software development process, also known as software development life cycle (SDLC), involves several distinct activities for developing, testing, maintaining, and evolving a software system. Within the stages of SDLC, software maintenance occupies most of the total cost of the software life. However, after extended maintenance activities, software quality always degrades due to increasing size and complexity. To solve this problem, software modularisation using clustering is an intuitive way to modularise and classify code into small pieces. , A multi‐pattern clustering (MPC) algorithm for software modularisation is proposed in this study. The proposed MPC algorithm can be divided into five different steps: (1) preprocessing, (2) file labelling, (3) collection of chain dependencies, (4) hierarchical agglomerative clustering, (5) modification of the clustering result. The performance of the proposed MPC algorithm to selected clustering techniques is compared by using three open‐source and one closed‐source software programs. Experimental results show that the modularisation quality of the proposed MPC algorithm is nearly 1.6 times better than that of the expert decomposition. Additionally, compared to other software clustering algorithms, the proposed MPC algorithm, on average, has a 13% enhancement in producing results similar to human thinking. Consequently, it can be seen that the proposed MPC algorithm is suitable for human comprehension while producing better module quality compared to other clustering algorithms.

The demand for Wireless Sensor Networks is increasing day by day because of their diverse nature. Due to the limited energy, it is a complex task to retract the sensor node after deployment. So, there is a requirement for network maintainability before the deployment phase for its smooth working. It is achieved in three phases: hardware of the sensor node, communication and external environmental phase. This paper focuses on network maintainability in the communication phase. A novel framework MD-MARS is presented to enhance the network maintainability. This framework is classified into three phases namely analysis of performance parameters, data flow optimization and maintainability evaluation. In the initial phase, the performance parameter is analyzed using NS2 simulator. The next phase deals with data flow optimization using a machine learning algorithm. It reduces congestion and enhances network performance. The proposed algorithm is finely tuned to different degrees using the Grid Search approach to achieve the highest accuracy. The best model is selected based on accuracy and minimizes the prediction error. This algorithm predicts with the highest accuracy of 99.83%, lowest being 21.17%. Maintainability is achieved in the last phase using the total time taken to optimize the data flow. Several observations of repair time are determined for the best-tune model during the prediction of optimized data flow. These observations are used to calculate the mean time to repair, standard deviation, probability density function, maintainability and repair rate. The maximum maintainability achieved in this paper is 97.67% at a repair time of 26.07 milliseconds.

Improving wind turbine performance, operation, and efficiency requires evolving Operation and Maintenance (O&M) methods. Different models are required for O&M choices. These models offer a broad variety of scenarios and variables to reduce energy costs and enhance wind farm profitability. In this regard, this paper proposes a detailed approach for maintenance decisions to pick an optimum maintenance strategy (MST) for different subassemblies of wind turbines based on failure analysis. This approach is predicated mostly on a vast field database of failures and repairs of several subassemblies of wind turbines. The maintenance model is comprised of many stages, including the data preparation stage, the availability optimization stage, and the optimum MST selection step. Consequently, this model aids in determining the appropriate MST for all subassemblies of wind turbines to achieve the necessary degree of availability.

The mechatronic industry is currently subject to huge changes challenging it to offer products matching individual customer requirements at competitive prices. The design of such products calls for sophisticated and complex components integration following different technologies. Since we are on the cusp of the Fourth Industrial Revolution, in which the world of mechatronic production, network connectivity, the Internet of Things, and cyber-physical systems are correlated, the complexity of these systems increases exponentially, and we are talking about advanced mechatronic systems. To assist these changes, various methods, sweeping all project phases, are used by business houses. Predictive dependability assessment in the earlier design stage is considered a powerful metric used to evaluate the performances of different kinds of mechatronic products before the production phase. Altogether, dependability analysis ties the design directly to the desired functionality, operability, and integrity of the system. This paper explores an approach to assessing the dependability attributes, reliability, availability, and maintainability (RAM), of repairable mechatronic systems based on timed colored Petri nets and a Monte Carlo simulation, integrating simultaneously diverse components technologies: mechanical, electronic, and software. The proposed approach is tested taking the case of a regenerative braking system. The methodology appears to be efficient for evaluating predictive RAM indicators (MTTFF, MTTR, MTBF…) for the whole system and for each individual component separately.

The operation of liquefied natural gas (LNG) marine loading arms plays a pivotal role in the efficient transfer of LNG from maritime vessels to downstream facilities, underpinning the global LNG supply chain. Despite their criticality, these systems frequently encounter operational challenges, notably slow coupling speeds and increased downtimes driven by maintenance demands. Addressing these challenges, Physical Asset Management principles advocate for maximizing process availability by minimizing both planned and unplanned outages. Recognizing maintainability as a key equipment attribute, this document proposes a procedure that extends the use of the UNE 151001 standard to evaluate the maintainability of physical assets. This proposal incorporates into traditional RCM a step for the selection of maintenance levels proposed in the standard, as well as the use of the AHP technique for selecting the weights used during the analysis process. Finally, an aggregated maintainability indicator is presented, which will allow for better evaluation, comparison, and monitoring of this characteristic in one or more industrial assets. To demonstrate its feasibility and utility, the proposed procedure is applied to a set of LNG marine unloading arms. This study identifies pivotal areas for improvement and devises strategic action plans aimed at enhancing asset’s maintainability. The outcomes of this analysis not only provide a roadmap for augmenting operational efficiency but also furnish empirical justification for the requisite investments in maintainability enhancements, thereby contributing to the resilience and sustainability of LNG logistics infrastructure.

When studying Markov chain models and semi-Markov chain models, it is useful to know which state vectors n, where each component ni represents the number of entities in the state Si, can be maintained or attained. This question leads to the definitions of maintainability and attainability for (time-homogeneous) Markov chain models. Recently, the definition of maintainability was extended to the concept of state reunion maintainability (SR-maintainability) for semi-Markov chains. Within the framework of semi-Markov chains, the states are subdivided further into seniority-based states. State reunion maintainability assesses the maintainability of the distribution across states. Following this idea, we introduce the concept of state reunion attainability, which encompasses the potential of a system to attain a specific distribution across the states after uniting the seniority-based states into the underlying states. In this paper, we start by extending the concept of attainability for constant-sized Markov chain models to systems that are subject to growth or contraction. Afterwards, we introduce the concepts of attainability and state reunion attainability for semi-Markov chain models, using SR-maintainability as a starting point. The attainable region, as well as the state reunion attainable region, are described as the convex hull of their respective vertices, and properties of these regions are investigated.

Introduction. The issue of revising the existing regulatory documents at the stage of operation of residential buildings becomes relevant due to the need to take into account scientific and technological achievements in the field of standardization. The emergence of new building materials, technological methods of manufacturing structures, methods of performing repair and construction work leads to the need for an ongoing update of the regulatory framework of construction. The object of the study is a set of regulatory documents focused on the stage of operation of construction facilities. The purpose of the work is to prepare proposals for updating, correcting and supplementing the regulatory framework governing the stage of operation of construction facilities. Materials and methods. The task of this work is to analyze the domestic regulatory framework affecting the concept of ope­ration of construction facilities, to make a classification of requirements for capital construction facilities at this stage and to structure regulatory technical documents. Results. Proposals were developed to adjust, supplement and update the regulatory framework of the operation stage. Conclusions. Within the framework of this study, regulatory technical and methodological documents affecting the concept of the stage of operation of buildings and structures are systematized and analyzed; a list of regulatory documents requiring adjustments and additions is made.

Introduction. The issue of revising the existing regulatory documents at the stage of operation of residential buildings becomes relevant due to the need to take into account scientific and technological achievements in the field of standardization. The emergence of new building materials, technological methods of manufacturing structures, methods of performing repair and construction work leads to the need for an ongoing update of the regulatory framework of construction. The object of the study is a set of regulatory documents focused on the stage of operation of construction facilities. The purpose of the work is to prepare proposals for updating, correcting and supplementing the regulatory framework governing the stage of operation of construction facilities.Materials and methods. The task of this work is to analyze the domestic regulatory framework affecting the concept of ope­ration of construction facilities, to make a classification of requirements for capital construction facilities at this stage and to structure regulatory technical documents.Results. Proposals were developed to adjust, supplement and update the regulatory framework of the operation stage.Conclusions. Within the framework of this study, regulatory technical and methodological documents affecting the concept of the stage of operation of buildings and structures are systematized and analyzed; a list of regulatory documents requiring adjustments and additions is made.

Code smell causes side effects in the source code and impact the code quality. It is beneficial to recognize code smells to improve software quality. Despite 22 classical code smells as characterized by Martin Fowler, all classical code smells have not been considered for the identification and refactoring. Temporary field code smell is one such code smell that has not been given an appropriate level of attention so far regarding its detection as well as refactoring. In this paper, we have proposed a novel metric-based method and developed a tool to detect temporary field code smell. The proposed method works on three novel metrics in addition to existing metric TCC (tight class cohesion) and three new rules (R1, R2, and R3) to detect temporary field code smell. Detection rules were tested on ten open-source GitHub Java projects used in the literature. Results demonstrate that projects under the study that had non-cohesive classes have shown the presence of temporary field code smell ranging from 54% to 100%. Findings have additionally demonstrated that for the undertaken projects, there exists a strong positive correlation between the number of classes exhibiting temporary field smell and number of non-cohesive classes present in a project.

The structure of steering gear’s HATLAPA mechanism is analyzed. It is shown that presence of redundant constraints in it increases laboriousness of gear montage and respectively worsen maintainability. On the basis of provided analysis developed mechanism with reduced more than twice redundant constrainsts number.

Setiap tahunnya, jumlah pengguna aplikasi seluler terus bertambah. Hal ini menyebabkan pengembang aplikasi seluler dituntut untuk mengembangkan produknya dengan cepat. Framework antarmuka pengguna lintas platform Flutter dan React Native menjadi sangat populer karena kemampuannya untuk dikompilasi ke berbagai jenis sistem operasi perangkat seluler. Namun, di antara kedua framework tersebut, belum diketahui manakah yang memiliki maintainability yang lebih baik. Tahap perawatan perangkat lunak merupakan tahap yang memakan paling banyak waktu, tenaga, dan usaha. Sehingga, penting untuk mengetahui framework mana yang basis kodenya lebih mudah dirawat. Pada penelitian ini, aplikasi media komunikasi untuk taman kanak-kanak dengan kompleksitas use-case yang beragam digunakan sebagai bahan untuk membandingkan maintainability Flutter dan React Native. Basis kode yang dikembangkan masing-masing diukur menggunakan A Code Quality Metrics Model for React-Based Web Applications. Hasil penelitian menunjukkan bahwa basis kode yang ditulis menggunakan Flutter memiliki maintainability lebih tinggi dibandingkan React Native. Faktor yang mempengaruhinya adalah bahasa pemrograman yang digunakannya, yaitu Dart untuk Flutter dan JavaScript untuk React Native, serta cara penulisan komponen yang berbeda antara Flutter dan React Native Mobile phone users are increasing every year. This demands mobile application developers to speed up their development time. Flutter and React Native, which are cross-platform user interface framework, become more popular due to their ability to compile to any mobile operating system. But, it is not yet known which of the two frameworks have the better maintainability. Maintenance is a step in software development process that consumes most of the development effort. So, it is important to know which framework produces the more maintainable code base. In this research, a communication media application for kindergarten with diverse use case complexity is used for comparing maintainability between Flutter and React Native. Each code base are measured using A Code Quality Metrics Model for React-Based Web Applications. The result is code base that are developed using Flutter has more maintainability than React Native. The influencing factors are programming languages used, which are Dart for Flutter and JavaScript for React, as well as how components in each frameworks are written.

Purpose: Reliability and maintainability are the key system effectiveness measures in process and manufacturing industries, and treatment plants, especially in E-waste management plants. The present work is proposed with a motto to develop a stochastic framework for the e-waste management plant to optimize its availability integrated with reliability, availability, maintainability, and dependability (RAMD) measures and Markovian analysis to estimate the steady-state availability of the E-waste management plant. In the analysis an effort is also made to identify the best performing algorithm for availability optimization of the e-waste plant. Methodology: A stochastic model for a particular plant is developed and its availability is optimized using various metaheuristic approaches like a genetic algorithm (GA), particle swarm optimization (PSO), and differential evolutions (DE). The most sensitive component is identified using RAMD methodology while the effect of deviation in various failure and repair rates are observed by the proposed model. The failure and repair rates follow an exponential distribution. All time-dependent random variables are statistically independent. Originality/Novelties: A novel stochastic model is presented for an e-waste management plant and optimum availability is obtained using metaheuristic approaches. The proposed methodology is not so far discussed in the reliability analysis of process industries. Findings: The numerical results of the proposed model compared to identify the most efficient algorithm. It is observed that genetic algorithm provides the maximum value (0.92330969) of availability at a population size 2500 after 500 iterations. PSO algorithm attained the maximum value (0.99996744) of availability just after 50 iterations and 100 population size. So, its rate of convergence is faster than GA. The optimum value of availability is 0.99997 using differential evolution after 500 iterations and population size of more than 1000. These findings are very beneficial for system designers. Practical Implications: The proposed methodology can be utilized to find the reliability measures of other process industries.

Software code is present on multiple levels within current Internet of Things (IoT) systems. The quality of this code impacts system reliability, safety, maintainability, and other quality aspects. In this paper, we provide a comprehensive overview of code quality-related metrics, specifically revised for the context of IoT systems. These metrics are divided into main code quality categories: Size, redundancy, complexity, coupling, unit test coverage and effectiveness, cohesion, code readability, security, and code heterogeneity. The metrics are then linked to selected general quality characteristics from the ISO/IEC 25010:2011 standard by their possible impact on the quality and reliability of an IoT system, the principal layer of the system, the code levels and the main phases of the project to which they are relevant. This analysis is followed by a discussion of code smells and their relation to the presented metrics. The overview presented in the paper is the result of a thorough analysis and discussion of the author’s team with the involvement of external subject-matter experts in which a defined decision algorithm was followed. The primary result of the paper is an overview of the metrics accompanied by applicability notes related to the quality characteristics, the system layer, the level of the code, and the phase of the IoT project.

This paper illustrates the impact of wind turbine (WT) subassemblies’ availability on WTs’ performance. Complete and detailed reliability, availability, and maintainability (RAM) analysis of various subassemblies of WTs utilizing the Weibull probability density function (PDF) is also introduced. A modified dynamic important measures-based reliability and availability are presented to show the significant impact of various WT subassemblies on the overall system performance. This method is mainly utilized to rank the WT subassemblies regarding their impact on the system reliability and availability, identifying the subassemblies that the planned maintenance should focus on. Dynamic ranking of WT subassemblies is obtained to achieve the desired level of reliability and availability. The obtained results demonstrate the effectiveness and efficiency of the proposed approach that achieves the system’s secure operation and improves system reliability and availability.

Obtaining system availability in an engineering design is trickish and challenging, especially when there is a reduction in capacity; however, it supports system maintainability. In this paper, a mathematical model for finding the availability under the reduced capacity has been proposed using the Chapman Kolmogorov approach with the help of transition diagrams associated with various possible combinations of probabilities. The paper observes the most critical subsystem by selecting variable failure and repair rates from different subsystems. It deals with the sensitivity analysis of a complex repairable threshing combined machine comprising subsystems in a series configuration and the threshing machine consisting of 21 subsystems. The device works in total capacity when the threshing drum and feeding Hooper work in the complete state, and the concave subsystem and blower work with reduced power. This study dealt with uncertain data and was analyzed analytically using a complex repairable system. The availability of the entire machine has been investigated analytically, and various availability indices such as subsystems extruder have been computed and reported. The study discovered that subsystem extruder has the most impact on some subsystems’ overall system availability.

The maintainability of sewer infrastructure systems is vital for public health, environmental protection, and the overall well-being of communities. However, maintenance and repair activities for sewer pipelines are often constrained, leading to challenges in effectively managing such infrastructures. To address these challenges, this study assessed the maintainability of sewer pipelines. A total of 15 defects were identified and categorized into structural, hydraulic, and quality defects after a comprehensive literature review was conducted and sewer pipeline experts were interviewed. Each failure caused by these defects was categorized as a pipe collapse associated with structural defects, sewer system overflow (SSO), odor, and groundwater contamination associated with quality defects. Apart from assessing the defects, the study identified potential solutions. After that, the obtained data were analyzed to determine the relative significance of each probability identified and its impact on four parameters, economic, social, environmental, and detection difficulty, using the relative importance index (RII), while the risk value index (RI) was applied to prioritize the defects. Furthermore, a data reliability assessment was utilized to evaluate internal consistency. The findings indicate that the probability of joint defects in the structural category caused by weaknesses in welded joints due to the misalignment of plastic pipes or joints, especially spigot and socket joints for rigid pipes, was the highest (RII = 0.733). Additionally, the ranking showed that the dumping of FOG had the highest priority, with an RI value of 0.535. This study offers a comprehensive maintainability framework that can be utilized by agencies assessing their current sewer infrastructure systems, in particular Arab Gulf countries including Saudi Arabia, which is the subject of this study.

The objective of this research was to investigate the performance of the Finger Joint Fu-King Furnimate machine, especially for the most critical component of this machine. Based on historical data of machine damage, the Finger Joint Fu-King Furnimate is the machine that has the highest-level frequency of damage. Reliability, Availability, Maintainability, and Safety (RAMS) methods are proposed to analyze the machine's historical data. The result shows that the reliability of machine performance at t = 160 hours is only 27.42%, but the availability of machines is quite high, which passed the standard of 95%. Meanwhile, the maintainability of the machine is relatively fast, which the repair time of its critical component is 8 hours. The low-reliability critical machine spare part affected the safety of the spare part which the Safety Integrity Level (SIL) in the lowest standard (level 1). In general, the novelty of this research is to combine the application of the RAM method as the basis for analyzing machine performance with a safety analysis of the selected critical machine subsystems.

In recent years, using of the resilience concept has been increased in order to evaluate the response of systems against the failures. Resilience depicts the system ability to return to its normal operational status after failure accruing. According to the literature survey, there are various studies, which have been done in the field of engineering and non-engineering systems, and there is no study about applying resilience concept in the field of mining industry. In this paper, at first, resilience concept has been introduced and then the resilience of the mining fleet of Sungun copper mine has been estimated. Systems performance indicators include reliability; maintainability and supportability have been used in order to resilience estimation. The results showed that the resilience of the entire system for one hour of its function is equal to 83.1% and this value decreases to 37.1% after 10 hours. This means if there is a failure in the system; it will have 83.1% and 37.1% probabilities to be resilience against the failure event after 1 hour and 10 hours of system function.

Maintainability is one of the design parameters (reliability, availability, maintainability, and safety (RAMS)) and maintenance is needed to keep the respective design in sustainable use. At the same time, the human is involved in the form of interface and interaction in an engineered product/system designed. Ergonomics is a multi-disciplinary science that considers human capabilities and limitations in a broader sense. The objective of this paper is to integrate ergonomics into the maintainability design process in order to facilitate maintenance operation in lesser; time, cost, easier operation as well as the well-being of human who is involved. In other words, good ergonomics lead to good economics and in a broader sense, sustainability. This investigation shows that designing comfortable workplaces and lesser workload for maintenance operators will be beneficial for the maintainability design process and also improve the meantime to repair MTTR. In order to evaluate the effect of designed work-place and workload on maintainers 3 D Static Strength Prediction Program (3D SSPP) that is commonly used as an ergonomics evaluation tool in scientific studies was applied.

Introduction/purpose: At the end of 2019, the Government of the Republic of Serbia adopted the Strategy for the Development of Artificial Intelligence in the Republic of Serbia for the 2020-2025 period. This was a motivation for the author of this paper to try to give an overview of the current artificial intelligence (AI) applications in the field of reliability and maintenance, as well as its future applications. Methods: The overview is done mainly using available literature, mostly from the Science Direct database, using abstracts generally, and in some cases whole papers. Results: The result of this research is an overview of the artificial intelligence applications in the field of reliability and maintenance in the past thirty years. It also showed that AI systems can also be unreliable and need maintenance. Conclusion: Artificial intelligence is and can be applied in reliability and maintenance. The research of available literature showed that AI is more applied in maintenance than in reliability. The progress in AI is inevitable, so it is important to understand its potentials for application in reliability and maintenance as well as its possible drawbacks.

For any industrial entity put into operation, it is of interest to its ability to fulfil its mission under certain conditions, at a given time or during a given period of time, assuming that the means of maintenance are provided. This represents availability and is a complex form of system / product quality, as it includes both reliability and maintainability. Availability can be increased by: maximum reliability, maintenance, respectively by maximum maintainability, correct use of equipment / machines, renewal, optimization of reliability and maintainability characteristics, but provided that such balancing does not lead to contradictory solutions. The availability of a product will be higher the more reliable it is and requires less maintenance. It should be borne in mind that in order to ensure a certain level of reliability, maintenance costs must not exceed 10...20% of the purchase price of the product each year [1]. Restoration of reliability to a normal level is achieved through corrective or preventive maintenance. In practice, a compromise is sought between the purchase price, the service imposed and the accepted risk, as in order to achieve availability through reliability, very reliable parts must be used, which cost 5-10 times more than usual [2]. Maintenance-based availability results from the consideration that reliability is a probability of trouble-free operation over a period of time. Reliability is technically and financially limited. Defects in the initial period of operation of the product, as well as those in the final period derive from inevitable physical phenomena, and defects in the maturity period have a normal accidental character. In addition, the reliability can deteriorate over time even during storage, thus causing additional damage. Reliability is restored to its normal level through corrective or preventive maintenance, as failures are foreseeable or unpredictable. Product availability is the result of a combination of reliability and maintainability and they support each other. Increasing the maintainability of products leads to increased availability. In this case, the real maintainability of a burning oven of a cement factory was studied, with the aim of finding practical solutions to increase the service life. Achieving the proposed objective required monitoring the operation / failure of such equipment for nine months and statistical processing of the information obtained.

Indonesia has the potential for large solar power plants. It has relatively constant solar radiation because it is close to the equator. Besides, solar energy includes renewable energy that is more environmentally friendly and easier to apply in office areas, especially Wonogiri. However, it turns out that the solar power plant projects that have been built are not yet fully functional, and some have even failed. A lack of responsibility and maintenance causes this carried out after the project is complete. For this reason, it is necessary to estimate the reliability of these components and determine the maintenance schedule before the project is carried out. So that later they have a picture and be better prepared when this project is already underway. The fault tree method's failure factors are expected to create a picture to maintain reliability and determine the prioritized components for maintainability. For the results obtained to be more appropriate, apart from seeing the quantitative analysis output, the fault tree also needs to be adjusted to the component manual or datasheet to determine the replacement of spare parts and their maintenance. So that the resulting schedule for maintenance and replacement of spare parts. Thus, the solar power plant project that has been built will be more reliable and can be appropriately utilized.

Software architecture is known to be an effective tool with regards to improving software quality attributes. Many quality attributes such as maintainability are architecture dependent, and as such, using an appropriate architecture is essential in providing a sound foundation for the development of highly maintainable software systems. An effective way to produce a well-built architecture is to utilize standard architectural patterns. Although the use of a particular architectural pattern cannot have a preserving effect on software maintainability, the mere conformance of a system to any architecture cannot guarantee the system’s high maintainability. The use of an inappropriate architecture can seriously undermine software maintainability at lower levels. In this article, the effect of standard architectural patterns on software maintainability quality attributes is investigated. We develop a quality model for maintainability quality attributes, which is later used to compare various standard architectural patterns. We finish by investigating two real-world experiences regarding the application of a particular pattern to two different existing architectures, exploring the effect of the change in architecture on maintainability quality attributes.

The maintainability of the software is one of the most substantial aspects when assessing software product quality. It is known as the easiness with which the current software can be changed. In the literature, a great number of models have been suggested to predict and measure maintainability during various stages of the Software Development Life Cycle, to conduct a comparative study of the existing suggested models of the prediction, only few attempts have been done. This study hints at the basics about the manner of how to measure maintainability in the object-oriented (OO) design knowing that the maintainability will be measured differently at every level. Also, we will concentrate on the artificial intelligence technologies of these studies.

Many resilience definitions and metrics have been presented across various disciplines in recent times. However, from a design and operations perspective, a limited effort is focused on quantifying the resilience of oil and gas support structures. This study proposes a methodology for structural resilience quantification of an offshore hydrocarbon pipeline. Resilience is modelled as a function of the structure’s time-dependent reliability, adaptability, and maintainability. The proposed model is demonstrated on an internally corroded offshore natural gas pipeline segment with multiple initial defects; and considers disruptive events arising from the leak, burst, and rupture failure modes. The resilience index and sensitivity analysis are evaluated for the offshore pipeline. The pipeline sensitivity analysis indicates the apparent effect of pipe wall thickness and defect depth growth rate on resilience over its design life. The outcome of this study provides an insight into the resilience quantification of structural systems considering multiple disruptive events. The proposed model is expected to serve as an essential tool for resilience evaluation during the design and operations of oil and gas structures.

The equipment in underground mines provides a continuous production flow, depending on the way their quality is preserved during their operation. The TR-7A scraper conveyer subassemblies, which function in the Jiu Valley coal basin and are subjected to abrasion wear, showed a high failure frequency (chains, chain elevators, and driving and turning drums), as well as the hydraulic couplings and certain electric equipment of the same machinery. The data collected following the TR-7A scraper conveyer at work allowed the parameters to be determined that characterise the reliability and maintainability of the above-mentioned components, the failure modes, and their effects. Using calculation methods, the interpretation of the results has been facilitated, with a view to reducing maintenance costs and obtaining an 80% reliability for the components with the most failures, in the case of the TR-7A scraper conveyer.

Abstract Database code fragments exist in software systems by using Structured Query Language (SQL) as the standard language for relational databases. Traditionally, developers bind databases as backends to software systems for supporting user applications. However, these bindings are low‐level code and implemented to persist user data, so Object Relational Mapping (ORM) frameworks take place to abstract database access details. Both approaches are prone to problematic database code fragments that negatively impact the quality of software systems. We survey problematic database code fragments in the literature and examine antipatterns that occur in low‐level database access code using SQL and high‐level counterparts ORM frameworks. We also study problematic database code fragments in different and popular software architectures such as Service‐Oriented Architecture, Microservice Architecture, and Model View Controller. We create a novel categorization of both SQL schema and query antipatterns in terms of performance, maintainability, portability, and data integrity.

The process of aircraft operation involves constant effects of various factors on its components leading to accidental or systematic changes in their technical condition. Markov processes are a particular case of stochastic processes, which take place during aeronautical equipment operation. The relationship of the reliability characteristics with the cost recovery of the objects allows us to apply the analytic apparatus of Markov processes for the analysis and optimization of maintainability factors. The article describes two methods of the analysis and control of object maintainability based on stationary and non-stationary Markov chains. The model of a stationary Markov chain is used for the equipment with constant in time intensity of the events. For the objects with time-varying events intensity, a non-stationary Markov chain is used. In order to reduce the number of the mathematical operations for the analysis of aeronautical engineering maintainability by using non-stationary Markov processes an algorithm for their optimization is presented. The suggested methods of the analysis by means of Markov chains allow to execute comparative assessments of expected maintenance and repair costs for one or several one-type objects taking into account their original conditions and operation time. The process of maintainability control using Markov chains includes search of the optimal strategy of maintenance and repair considering each state of an object under which maintenance costs will be minimal. The given approbation of the analysis methods and maintainability control using Markov processes for an object under control allowed to build a predictive-controlled model in which the expected costs for its maintenance and repair are calculated as well as the required number of spare parts for each specified operating time interval. The possibility of using the mathematical apparatus of Markov processes for a large number of objects with different reliability factors distribution is shown. The software implementation of the described methods as well as the usage of tabular adapted software will contribute to reducing the complexity of the calculations and improving data visualization.

With the increasing ability to generate actionable insight from data, the field of data science has seen significant growth. As more teams develop data science solutions, the analytical code they develop will need to be enhanced in the future, by an existing or a new team member. Thus, the importance of being able to easily maintain and enhance the code required for an analysis will increase. However, to date, there has been minimal research on the maintainability of an analysis done by a data science team. To help address this gap, data science maintainability was explored by (1) creating a data science maintainability model, (2) creating a new tool, called MIDST (Modular Interactive Data Science Tool), that aims to improve data science maintainability, and then (3) conducting a mixed method experiment to evaluate MIDST. The new tool aims to improve the ability of a team member to update and rerun an existing data science analysis by providing a visual data flow view of the analysis within an integrated code and computational environment. Via an analysis of the quantitative and qualitative survey results, the experiment found that MIDST does help improve the maintainability of an analysis. Thus, this research demonstrates the importance of enhanced tools to help improve the maintainability of data science projects.

The problem of reliability and availability of the Internet of Things (IoT) from the point of view of the classical approach of reliability assessment using MIL-HDBK 217 is discussed in this paper. With the classical approach of reliability assessment using MIL-HDBK 217, only hardware reliability can be assessed, and the situation with the IoT is more complicated: billions of different things (devices), software programs, and human users are involved (networked). The reliability and availability of the IoT is not only a matter of a failure rate of elements (things), but also protocols, standardization, logistics support and other influences. The relation for the reliability calcuation of an IoT system is proposed. / В данной статье обсуждается проблема надежности и доступности Интернета вещей (IoT) с точки зрения классического метода оценки надежности с помощью MIL-HDBK 217. Однако при применении классического метода оценки надежности с помощью MIL-HDBK 217 можно оценить только надежность аппаратного обеспечения, в то время как ситуация с IoT намного сложнее, так как задействованы (объединены в сеть) миллиарды различных факторов: вещей (устройств), программных обеспечений, включая и людей. Надежность и доступность интернета вещей зависит не только от частоты отказов элементов (вещей), но также и от протоколов, стандартизации, логистической поддержки и других факторов. Предложено соотношение для расчета надежности системы IoT. / U radu se razmatra problem pouzdanosti i raspoloživosti dostupnosti interneta stvari (IoT) sa stanovišta klasičnog pristupa procene pouzdanosti pomoću MIL-HDBK 217. Korišćenjem klasičnog pristupa procene pouzdanosti pomoću MIL-HDBK 217 može se proceniti samo pouzdanost hardvera, a situacija sa IoT-om je složenija: milijarde različitih stvari (uređaja), softvera, uključujući ljude, uključeno je (umreženo). Pouzdanost i dostupnost interneta stvari nije samo pitanje stepena otkaza elemenata (stvari) već i protokola, standardizacije, logističke podrške i drugih uticaja. Predložena je relacija za izračunavanje pouzdanosti IoT sistema.

A way of SQL-injection vulnerability detection based on static code analysis is discussed. A web-application internal quality model based on the results of automated detection of SQL-injection vulnerabilities is given. Practical results of applying the quality model to real-world web-applications are presented.

Reachability, as a vital parameter in product maintainability design, exerts a tremendous influence in practical maintenance, especially in the usage stage. To decrease subjectivity in maintenance reachability analysis, this study proposes an automatic and quantitative approach based on the spatial data of the human arm to implement maintenance reachability analysis. The approach focused on two aspects, namely, accuracy and efficiency. In terms of accuracy, the presented methodology starts from the maintenance spot where the human hand is attached. An original global data sequence set was generated, including the wrist, elbow, and shoulder joints, under the constraints of kinematics, in which a data sequence represents an arm motion. Moreover, the surrounding objects are represented by their geometric data, in which each data sequence is analyzed to judge whether collision occurs between arm segments and surrounding objects. In this filtering process, the data sequence is retained if the aforementioned collision does not occur. In terms of efficiency, owing to the large number of global data sequences, the efficiency of the interval selection in collision calculation is also taken into consideration in this methodology. Unlike the traditional methods in the virtual environment, the starting point is the maintenance spot, rather than the human body. Hence, nearly all possibilities of arm postures are considered in a global perspective with little subjective involvement, which enhances the automation and objectivity in maintenance reachability analysis to a certain extent. The case study shows the usability and feasibility by a practical maintenance scene.

Tunnelling is a vital geotechnical engineering feature of underground transportation systems that is potentially hazardous if not properly investigated, studied, planned, and executed. A reliability, availability, and maintainability (RAM) analysis is one of the main practical techniques in machinery-based projects to recognize the failure and repair rates of machines during or after their operations. RAM analysis of mechanized tunneling can help to manage the project safety and cost, and improve the availability and performance of the machine. There are several methods to obtain and predict the RAM of a system, including the Markov chain simulation and other statistical methods; however, the result of the analysis can be affected by the selected method. This paper presents the results of a critical investigation on the RAM of the Earth pressure balance machines (EPBMs) used in developing an urban metro project in Isfahan, Iran. The five kilometer length of the first line of the Isfahan metro project was excavated using EPBMs over four years. After overhauling the EPBMs and making some minor changes, excavation of the second line started, and to date, about 1.2 km has been excavated by the refurbished machines. In the present study, a RAM analysis has been applied to electrical, mechanical, and cutter head subsystems of the EPBMs in Lines 1 and 2 of the Isfahan metro project over an 18- and 7-month period of machine operation, respectively. The results show that the estimated availability, A(t), determined by the Markov method, is closer to reality but cannot be propagated to reliability R(t) and maintainability M(t) analysis. It was also revealed that by predicting the required maintenance and proper planning, the overall availability of the EPBM was improved from 45% in Line 1 to 61% in Line 2. The outcomes of this study can be used in the future planning of urban tunneling projects to estimate machine, staff, and logistic performance with the least possible error, and appropriately arrange the factors involved in the system.

With the increasing ability to generate actionable insight from data, the field of data science has seen significant growth. As more teams develop data science solutions, the analytical code they develop will need to be enhanced in the future, by an existing or a new team member. Thus, the importance of being able to easily maintain and enhance the code required for an analysis will increase. However, to date, there has been minimal research on the maintainability of an analysis done by a data science team. To help address this gap, data science maintainability was explored by (1) creating a data science maintainability model, (2) creating a new tool, called MIDST (Modular Interactive Data Science Tool), that aims to improve data science maintainability, and then (3) conducting a mixed method experiment to evaluate MIDST. The new tool aims to improve the ability of a team member to update and rerun an existing data science analysis by providing a visual data flow view of the analysis within an integrated code and computational environment. Via an analysis of the quantitative and qualitative survey results, the experiment found that MIDST does help improve the maintainability of an analysis. Thus, this research demonstrates the importance of enhanced tools to help improve the maintainability of data science projects.

Introduction: Successive code changes during the maintenance phase may cause the emergence of bad smells and anti-patterns in code and gradually results in deterioration of the code and difficulties in its maintainability. Continuous Quality Control (QC) is essential in this phase to refactor the anti-patterns and bad smells. Objectives: The objective of this research has been to present a novel component called Code Deterioration Watch (CDW) to be integrated with existing Issue Tracking Systems (ITS) in order to assist the QC team in locating the software modules most vulnerable to deterioration swiftly. The important point regarding the CDW is the fact that its function has to be independent of the code level metrics rather it is totally based on issue level metrics measured from ITS repositories. Methods: An issue level metric that properly alerts us of bad-smell emergence was identified by mining software repositories. To measure that metric, a Stream Clustering algorithm called ReportChainer was proposed to spot Relatively Long Chains (RLC) of incoming issue reports as they tell the QC team that a concentrated point of successive changes has emerged in the software. Results: The contribution of this paper is partly creating a huge integrated code and issue repository of twelve medium and large size open-source software products from Apache and Eclipse. By mining this repository it was observed that there is a strong direct correlation (0.73 on average) between the number of issues of type “New Feature” reported on a software package and the number of bad-smells of types “design” and “error prone” emerged in that package. Besides a strong direct correlation (0.97 on average) was observed between the length of a chain and the magnitude of times it caused changes to a software package. Conclusion: The existence of direct correlation between the number of issues of type “New Feature” reported on a software package and (1) the number of bad-smells of types “design” and “error prone” and (2) the value of “CyclomaticComplexity” metric of the package, justifies the idea of Quality Control merely based on issue-level metrics. A stream clustering algorithm can be effectively applied to alert the emergence of a deteriorated module.

Dependency injection (DI) is generally known to improve maintainability by keeping application classes separate from the library. Particularly within the Java environment, there are many applications using the principles of DI with the aim to improve maintainability. There exists some work that provides an inference on the impact of DI on maintainability, but no conclusive evidence is provided. The fact that there are no publicly available tools for quantifying DI makes such evidence more difficult to be produced. In this paper, we propose two novel metrics, dependency injection-weighted afferent couplings (DCE) and dependency injection-weighted coupling between objects (DCBO), to measure the proportion of DI in a project based on weighted couplings. We describe how DCBO can serve as a more meaningful metric in assessing maintainability when DI is also considered. The metric is implemented in the CKJM-Analyzer, an extension of the CKJM tool to perform static analysis on DI detection. We discuss the algorithmic approach behind the static analysis and prove the soundness of the tool using a set of open-source Java projects.

The two main research goals of this study are to develop a relationship diagram between the parameters of reliability and maintainability and to investigate the impact of reliability and maintenance on engineering design costs. In this study, we use the theory of reliability and maintainability parameters to derive the relationship between the parameters using block diagrams. Compared with onshore wind farms, offshore wind farms have higher reliability requirements, but the maintenance degree of offshore wind farms is lower due to environmental factors. This study proposes an important concept of reliability and maintenance for value engineering, which can help system design engineers and project engineers integrate reliability concerns in the design phase and operation and maintenance phase.

Model-Based Systems Engineering (MBSE) methods have developed a strong foothold in the design space in industry. These methods have proven fruitful when the right method is applied to the right problem. Reliability, Availability, and Maintainability (RAM) is an equally important area. Currently, there is a gap in applying a methodology to integrate the two in the design process, particularly when the design is complex. This work attempts to provide a methodology that results in the successful integration of RAM and MBSE that can be used during the early phases of design. The methodology was developed after an extensive literature review, followed by the illustration of the methodology through an example of a steam turbine fuel system. Each step of the method is applied and explained in the illustrative example, to include figures, tables, and calculations demonstrating the effectiveness of the method, concluding with evidence for validation.

The study of the methods revealed their advantages and disadvantages for further synthesis and optimization. The main task was to improve the most suitable method, which will have the maximum number of affecting factors. The experimental method is highly accurate, but it requires high costs to work on analogues for each specific type of fasteners. The calculated method based on a single experiment allows to determine time standards for various fasteners. The given method does not require high costs for experiments, but like the experimental method, does not take into account performance degradation with continuous operation time. This leads to serious errors in obtaining time standards for a large number of fasteners. The article shows the optimized model of calculated method, based on a linear approximation of dependence of the number of fasteners replacements (removals/installations) on time at multiple intervals. The optimized model allows to obtain time standards of typical fasteners replacement with different geometric characteristic taking into account performance degradation over time. Several experiments on the aircraft were conducted for testing the improved calculated method. On the basis of the experimental data the researchers built graphs of the number of fasteners replacements (removal/installation) on time with different geometric characteristics taking into account performance degradation over time. The data obtained is advisable to use for calculation maintainability factors on aircraft design stages. Program realization of these methods and systematization of the received time standards allow to improve maintainability, due optimization number and position of airframe fasteners and systems units and aviation equipment for the aircraft being designed and modernized. Application of the automated systems of design and analysis will contribute to labor input decrease at the aircraft maintainability analysis.

The paper outlines the main problems and perspectives of methods development for regulation and finding compliance of aircraft during the type design maintainability certification. Mentioned requirements and methods relevance are related to the fact that aircraft continuing airworthiness at the operational stage is possible only with a reasonable combination of the maintenance documentation instructions for continuing airworthiness of a type design and the required level of its maintainability, which both meet the minimum requirements of airworthiness standards. Deficiencies in those requirements and means of compliance have notable influence on the safety and effectiveness of air transportation. Main ICAO standards and international practice of regulation and evaluation of aircraft maintainability and instructions for continuing airworthiness are briefly analyzed. On the base of aircraft maintenance requirements analysis recommendations proposed aimed to further develop regulations and means of compliance for a type design maintainability certification. For solving this problem there is a need to implement certain scientific and practical developments in the domain of integrated logistic support as a technology which integrates the reliability, maintainability and other technical operating capabilities activities for a newly-designed aircraft in order to create its effective maintenance system. The kinds of requirements within the aviation regulations and means of compliance for them are recommended, which have to be corrected and developed, as well as directions of works necessary for that, including implementation of computer modelling and prototypes testing for showing compliance of aircraft with the maintainability certification requirements. It is shown a need for implementation of the scientific and practical results of research in integrated logistic support domain which allow for interconnect of the reliability and maintainability activities within a new aircraft design in order to integrate systematically reliability requirements with the necessary maintenance action in support of reliability and with the required for those maintenance works level of type design maintainability.

The solution to the problem connected with increasing the service reliability of the combine harvesters at the expense of cutting time on the delivery of spare parts to the field is offered.

An effective operations of a projection spot welding (PSW) machine is closely related to the effec-tiveness of the maintenance. Timely maintenance can prevent failures and improve reliability and maintainability of the machine. Therefore, establishing the maintenance frequency for the welding machine is one of the most important tasks for plant engineers. In this regard, reliability analysis of the welding machine can be used to establish preventive maintenance intervals (PMI) and to identify the critical parts of the system. In this reliability and maintainability study, analysis of the PSW machine was carried out. The failure and repair data for analysis were obtained from automobile manufacturing company located in Uzbekistan. The machine was divided into three main sub-systems: electrical, pneumatic and hydraulic. Different distributions functions for all sub-systems was tested and their parameters tabulated. Based on estimated parameters of the analyzed distribu-tions, PMI for the PSW machines sub-systems at different reliability levels was calculated. Finally, preventive measures for enhancing the reliability of the PSW machine sub-systems are suggested.