Search

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.

In the industrial systems there is a requirement that systems should work efficiently for long time. System performance is an important aspect for failure free operation but in real practice complete failure free operation of any production system is seldom possible. Detailed critical literature review for the past thirty three years of Reliability, Maintainability and Availability (RAM) approaches has been carried out which can help to improve performance of Complex systems. Review of some papers provided the detailed information about past and current scenario of RAM practices in research field and industries. Different RAM tools and techniques extracted from the review may be helpful in qualitative and quantitative analysis of the complex systems. In this paper, author tried to focuss on some major aspects of RAM approaches. [ABSTRACT FROM AUTHOR]

Knowledge of the quality characteristics (reliability and maintainability) of a product or equipment is essential, whether it is a simple or complex system. Reliability influences maintenance, the lifespan of products and equipment, as well as an acceptable level of their security. Wear and tear on equipment and renewal are cost generators that must be managed efficiently. This is why emphasis is placed on a new field of investigation aimed at reducing these costs. This approach is primarily based on modeling the occurrence of defects over time and the corresponding remediation times. The paper aims to establish the reliability and maintainability of technological equipment, particularly those that experience a high number of failures, using data from a coal preparation plant in the Jiu Valley over a period of three years. [ABSTRACT FROM AUTHOR]

Given the rapid evolution that has taken place in recent years in the software industry, and along with it the emergence of quantum software, there is a need to design an environment for measuring quality metrics for hybrid, classic-quantum software. In order to measure and evaluate the quality of classic software, there are models and standards, among which ISO/IEC 25000 stands out, which proposes a set of quality characteristics such as maintainability. However, there is currently no consensus for the measurement and evaluation of quantum software quality. In this paper we propose a series of adaptations to "classic" metrics, as well as a set of new measurements for hybrid maintainability. Finally, a first prototype of a measurement tool developed as a SonarQube plugin, capable of measuring these metrics in quantum developments, is also presented. [ABSTRACT FROM AUTHOR]

This quantitative study aims to determine the significant relationship of the respondents’ profile and the indicators such as functionality, reliability, efficiency, usability, maintainability and portability of the Internal Revenue Integrated System (IRIS) of the Bureau of Internal Revenue. The research instrument includes the demographical profile question for the respondents includes their age and years in service at the Bureau of Internal Revenue. It includes 57 questions and a 5-point Likert scale and the research instrument is based on the ISO 9126 Software Engineering Standard was administered to the 41 frontliners of Revenue District No. 55 – San Pablo City. Findings of the study conclude and shows that there is no significant relationship in the profile of the respondents which is the age and years in service compare to the indicators of the Internal Revenue Integrated System (IRIS) such as functionality, reliability, usability, efficiency, maintainability and portability. Using the mean the result shows that the system has an average of moderately to very acceptable verbal interpretation. Spearman rho was used to test the significant relationship between respondents’ profile and the indicators of the Internal Revenue Integrated System (IRIS). This information can be used to help the Bureau of Internal Revenue on how to enhance the system without affecting business registration processes and services. [ABSTRACT FROM AUTHOR]

The purpose of the article was to analyse the reliability, maintainability, and availability estimates of firefighting and rescue engines. Analysing the reliability parameters of heavy firefighting and rescue vehicles over time requires knowledge of their failures. In this article, failure data from the six years of maintenance of ten heavy firefighting and rescue vehicles from ten were analysed in relation to two main subsystems. Reliability analysis was performed and the best-fit distribution was found, with the parameters calculated. For both subsystems, the chassis combined with the cabin and the superstructure, the 2P-Weibull distribution was identified as the most suitable fit. The availability and maintenance indicators for each vehicle and the individual subsystems were calculated. It was clearly defined that there exists a significant difference between the two subsystems analysed in terms of failure characteristics, as well as maintainability and availability parameters. [ABSTRACT FROM AUTHOR]

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.

Software development can be a time-consuming and costly process that requires a significant amount of effort. Developers are often tasked with completing programming tasks or making modifications to existing code without increasing overall complexity. It is essential for them to understand the dependencies between the program components before implementing any changes. However, as code evolves, it becomes increasingly challenging for project managers to detect indirect coupling links between components. These hidden links can complicate the system, cause inaccurate effort estimates, and compromise the quality of the code. To address these challenges, this study aims to provide a set of measures that leverage measurement theory and hidden links between software components to expand the scope, effectiveness, and utility of accepted software metrics. The research focuses on two primary topics: (1) how indirect coupling measurements can aid developers with maintenance tasks and (2) how indirect coupling metrics can quantify software complexity and size, leveraging weighted differences across techniques. The study presents a comprehensive set of measures designed to assist developers and project managers with project management and maintenance activities. Using the power of indirect coupling measurements, these measures can enhance the quality and efficiency of software development and maintenance processes. [ABSTRACT FROM AUTHOR]

The rapid increase of rates of change, disruptive events, risk and uncertainty increasingly threaten the long-term utilisation of hospital buildings. This challenge calls for an evolution in the lifecycle thinking that has always been integral to the hospital building design processes; or an approach that is termed 'future proofing'. Yet the implementation of future proofing as an emerging design requirement is impeded by lack of holistic understanding of the concept, and clarity about its objectives. As such, this research aims to provide a conceptualisation of future proofing via a taxonomic hierarchy. We interviewed sixteen experienced hospital architects from leading consultant firms across Australia to explore their general perceptions, and implementation in practice, of future proofing. The semi-structured interviews were informed by and indeed tested a theoretical model of future proofing previously constructed via literature review and were analysed and validated via thematic analysis and member checking. Our findings align theoretical understanding with hospital architects' practice-based perceptions and experiences of future proofing; elucidating future proofing as a dynamic meta-capability involving a multi-purpose hierarchy. Accordingly, a hierarchical integrated model of future proofing in practice was developed based on three axes (Survive, Evolve and Thrive), respectively defining three sets of spectrums with two extremes ranging from passivity to activity (Resilience-Mitigation, Maintainability-Improvement, and Changeability-Transition). While in previous research future proofing has been oversimplified and perceived largely in terms of adaptability, our findings support a more expansive definition of future proofing that includes various lifecycle design considerations. [ABSTRACT FROM AUTHOR]

The paper deals with an overview of RAMS strategies for complex systems in various process industries. This paper has reviewed a wide range of research articles and conference proceedings. These research publications dealt with the effect of failure and repair rates of subsystems on overall system performance. A comprehensive literature review regarding RAMS tactics has been conducted for twentyfive years. RAMS strategies address reliability, availability, maintenance and safety issues concerning industrial systems. These strategies aim to identify the failure-prone subsystems of industrial systems, which finally decide about the criticality of the subsystems and eventually improve the overall availability of the system by adopting the proper RAMS procedures. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the impact of mixed ground conditions and the presence of groundwater, which are critical geotechnical variables during mechanized tunneling, on the tool life, reliability, and maintainability of the EPB-TBM cutterhead. To achieve this goal, field data from the Tabriz urban railway project were gathered and classified into two groups: failures occurring in the tunnel's upper section above the water level and failures in the lower section below the water level. A comprehensive analysis of this data was conducted. The examination of various cutting tool types' consumption in mixed ground conditions revealed that scrapers had the highest replacement rate, while other tool types experienced fewer replacements. In terms of maintainability, the analysis showed that under dry ground conditions, there is an 80% probability of completing cutterhead maintenance within less than four shifts. However, in saturated ground conditions, this figure rises to 18.5 shifts. The reliability analysis demonstrated that the mean time between failures in dry ground and below the water level stands at 49.8 and 107.4 h, respectively. The significant contrast between maintainability and reliability findings underscores the influence of ground conditions on machine downtime and operational efficiency. The outcomes of this study provide valuable operational benchmarks that can be applied in EPB mechanized tunneling, enabling better project scheduling and enhancing the reliability of construction contracts. [ABSTRACT FROM AUTHOR]

In this article, the use of Markov approach has been made to analyze the reliability, availability and maintainability of a repairable system. The system has three non-identical units which work simultaneously and system will completely be failed at the failure of all units. The distribution for failure and repair times is taken as negative exponential as transition rates follow homogenous continuous Markov process. The reliability measures are derived using Chapman-Kolmogorov equations. The use of Laplace transform technique has been made to solve the system equations. For particular values of the parameters, the reliability measures including reliability, MTSF, availability, MTTR and maintainability have been obtained considering all units identical in nature. The effect of failure rate, repair rate and operating time has been observed on these measures through graphs. The application of the research work has been discussed in case of crypto mining process. [ABSTRACT FROM AUTHOR]

Modern software architectures such as microservices provide a high degree of scalability, changeability, and maintainability in application development. Furthermore, enabling controlled failure of microservices can provide abstract‐level solutions to design more resilient applications. In this paper, we introduce modularity vulnerability to analyze the vulnerability of a modular software design model under the failure of m top‐rank modules by the proposed structural metrics. The study analyzes the modularity quality coefficient (MQC) under the failure of the critical modules identified using the proposed parameter‐based greedy strategy. We conduct a comprehensive analysis of the software design generated by well‐known models and online datasets and provide a perspective for reasoning about the correlation between modularity metrics. The results show that the failure of the modules with the highest cluster factor (CF) value leads to a maximum decrease in the software modularity quality. Finally, we show a linear correlation between CF and the variations of the MQC, implying stability in the software modularity analysis (SMA) problem. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

This paper investigates the maintainability of economizers of three coal-based boilers for making decision of selection of replacement or maintenance practices. A sudden failure in the economizer can result huge production loss hence, a suitable decision model is essential which provides a strong data base for making optimal decision. A practical model for making decision is developed with respect to failure/repair data of three different economizers and trend with serial correlation tests are conducted. An investigation is carried out to determine the idealized statistical probability distribution providing best fit distribution. Further their Reliability and Maintainability are calculated. The tests of trend and serial correlation show very fast increasing failure rate of economizer # 1&2 with respect to economizer # 3. The present paper highlights that the failure data of economizer # 1 and economizer # 2 follow the NHPP model with poor reliability condition which indicates that these economizers should be replaced to restore boiler system as new as. However, failure data of economizer #3 follows the Lognormal distribution with poor reliability condition which suggests to develop the Preventive Maintenance Interval (PMI) to restore the boiler system. The present model serves a strong ground to decide replacement/preventive maintenance policy for not only to economizers but also to any pressure parts of coal based boilers. [ABSTRACT FROM AUTHOR]

This study develops a knowledge-based planned maintenance system (PMS) supported by reliability, availability and maintainability (RAM) analysis. The system enables maintenance plan revisions based on the data analysis which calculates instant RAM values and predicts the future trends. The visualised data is monitored to support decisions at both the operational and management level. The proposed system is demonstrated with the periodical data of the main engine installed onboard a container ship. Particularly, the data visualization is conducted on fuel injection valves. The results illustrate that the enhanced PMS system adds value to the timely and effective planning of routine and non-routine maintenance tasks onboard ships. Considering the existing potential of PMS applications onboard ships, the RAM analysis provides reasonable contributions to ship engine room crew and technical managers. The further study focuses on developing a maintenance planning app to digitalise the process and to strengthen compliance with ISM Code Clause 10 and TMSA 4A.4 requirements. [ABSTRACT FROM AUTHOR]

Software organizations face constant pressure due to stakeholder requirements and the increasing complexity of software systems. This complexity, combined with defects in code quality and failures, can pose risks to software systems. To ensure code is understood before maintenance, developers must spend over 60% of their time modifying and improving code quality, which is costly. This study examines the impact of code refactoring activities on software maintainability and quality by reviewing relevant research and explaining key terms. The research finds that refactoring activities can enhance specific quality characteristics, including maintainability, understandability, and testability. The study also identifies important factors that should be considered when developing refactoring tools. Refactoring enables code improvement without altering program behavior and can be applied multiple times to source code. [ABSTRACT FROM AUTHOR]

Due to the high demand for quality goods and products, most manufacturing industries run their equipment and manufacturing teams more than expected to meet the demands. However, they do not regularly conduct maintenance and reliability checks to ascertain the industry’s well-being. Operating their manufacturing systems and processes to achieve the requisite production rates of high-quality goods is a constant challenge for manufacturing industries in Nigeria due to a need for maintainability. To improve performance, this paper recently reviewed Nigeria's manufacturing industries' maintainability and reliability. The study examined articles that cut across, Maintainability scheduling in the production system with the analysis of Industry 4.0 Technologies, the reliability optimisation in the manufacturing industry in Nigeria, and the effects of sustainable maintainability and reliability implementation on manufacturing systems and the sustainability issues. Furthermore, the research highlighted the manufacturing industries’ challenges regarding maintainability and reliability. Some of these challenges are insecurity, lousy infrastructure, inadequate company growth plans, and irregular taxation, which affect the day-to-day running of the industry. One of the most significant issues facing the manufacturing sector today is inventory management; nonetheless, many small manufacturers still manage their stocks by hand. Furthermore, this study provides possible suggestions for a sustainable way forward for these identified problems. Nigerian manufacturing industries might adopt Industry 4.0 technology, which will assist in successfully adopting total preventive maintenance as a strategy and culture. This article recommends a maintenance culture in the manufacturing industry. It also recommends self-auditing and benchmarking as ideal preconditions for total productive maintenance. [ABSTRACT FROM AUTHOR]

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.

In order to solve the design problems of narrow-space maintainability of ship power cabins at the research and development (R&D) stage, ergonomics simulation and systems engineering evaluation techniques are used to study narrow-space maintainability by taking a ship power cabin as an object. Firstly, the core indexes of comfort, maintenance workspace, accessibility and visibility are identified, and weights are determined after consulting technical experts; then, maintenance tasks are decomposed into basic operation units to guide visualization simulation; finally, operation units are analyzed one by one to identify maintenance weaknesses and make recommendations for improvement. Taking "pipeline oil leakage maintenance" as an example, the feasibility of the method is verified by comparing and analyzing the maintainability before and after improvement. The results show that this method can identify and solve design problems of maintainability in narrow spaces of ship power cabins at the R&D stage and has practical engineering value. [ABSTRACT FROM AUTHOR]

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.

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.