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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.

This study aimed to develop and evaluate the performance of a service system platform based on the Internet of Things (IoT) for monitoring nutritional deficiencies in plants and providing fertilizer recommendations. There are two distinct differences between this work and previous ones; namely, this service system platform has been developed based on IoT using a system engineering approach and its performance has been evaluated using dependability. We have successfully developed and integrated a service system platform and chlorophyll meter that is based on IoT. We have also successfully tested the performance of the service system platform using the JMeter software. The dependability value measured from the five tested variables (reliability, availability, integrity, maintainability, and safety) showed a value of 0.97 which represents a very good level of system confidence in not failing to deliver services to users under normal operational conditions. From a future perspective, this platform can be used as an alternative service to monitor nutrient deficiencies in plants and provide fertilization recommendations to increase yields, reduce fertilizer costs, and prevent the use of excessive fertilizers, which can cause environmental pollution.

Fault tree analysis (FTA) is a well-established technique to analyze the safety risks of a system. Two specific prominent FTA methods, largely applied in the aerospace field, are the so-called minimal cut sets (MCS), which uses an approximate evaluation of the problem, and the direct evaluation (DE) of the fault tree, which uses a top-down recursive algorithm. The first approach is only valid for small values of basic event probabilities and has historically yielded faster results than exact solutions for complex fault trees. The second one means exact solutions at a higher computational cost. This article presents several improvements applied to both approaches in order to upgrade the computing performance. First, improvements to the MCS approach have been performed, where the main idea has been to optimize the number of required permutations and to take advantage of the available information from previous solved subsets. Second, improvements to the DE approach have been applied, which deal with a reduction of the number of recursive calls through a deep search for independent events in the fault tree. This could dramatically reduce the computation time for industrial fault trees with a high number of repeated events. Additional implementation improvements have been also applied regarding hash tables, and memory access and usage, but also implementing the so-called “virtual gates”, which enable limitless children on each gate. The results presented hereafter are promising, not only because they show that both approaches have been highly optimized compared to the literature, but also because a DE solution has been achieved, which can compete in time resources (and obviously in precision) with the MCS approach. These improvements are relevant when considering the industrial, and more specifically the aeronautical, implementation and application of both techniques. The author Jordi Pons‐Prats acknowledges the support from Serra Hunter programme, Generalitat de Catalunya, as well as the support through the Severo Ochoa Centre of Excellence (2019‐2023) under the grant CEX2018‐000797‐S funded by MCIN/AEI/10.13039/501100011033.

The Agriculture 4.0, also called Smart Agriculture or Smart Farming, is at the origin of the production of a huge amount of data that must be collected, stored, and processed in a very short time. Processing this massive quantity of data needs to use specific infrastructure that use adapted IoT architectures. Our review offers a comparative panorama of Central Cloud, Distributed Cloud Architectures, Collaborative Computing Strategies, and new trends used in the context of Agriculture 4.0. In this review, we try to answer 4 research questions: (1) Which storage and processing architectures are best suited to Agriculture 4.0 applications and respond to its peculiarities? (2) Can generic architectures meet the needs of Agriculture 4.0 application cases? (3) What are the horizontal development possibilities that allow the transition from research to industrialization? (4) What are the vertical valuations possibilities to move from algorithms trained in the cloud to embedded or stand-alone products? For this, we compare architectures with 8 criteria (User Proximity, Latency & Jitter, Network stability, high throughput, Reliability, Scalability, Cost Effectiveness, Maintainability), and analyze the advantages and disadvantages of each of them.

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.

Remaining useful life (RUL) prediction is a key solution to improve the reliability, availability and maintainability of engineering systems. Long short-term memory (LSTM) and convolution neural networks (CNN) are the current hotspots in the field of RUL prediction. However, the LSTM-based prognostic approach has a slow loop step to process large-scale time-series data since the dependence of the data processing process at each time on the output of the previous time limits parallelism, and the CNN-based prognostic approach is not fit for time-series data although it can process the data in parallel. In this paper, a new auto-encoder quasi-recurrent neural networks (AEQRNN) based prognostic approach is proposed for RUL prediction of the engineering systems. The AEQRNN contains convolution components that can process input data in parallel, and pooling components which has two LSTM-like gate structures to process time-series data. In addition, the AEQRNN can automatically extract hidden features from monitoring signals without manual feature design. The effectiveness of the proposed prognostic approach is validated by three prognostic benchmarking datasets, including a turbofan engine dataset, a rolling bearing dataset, and a machining tool dataset. Experimental results demonstrate that this approach has both superior prognostic performance and training speed in comparison with other kinds of recurrent neural network-based approaches and various state-of-the-art approaches in the recent literature.

High-performance and safe operation of a serially connected lithium-ion battery pack in the electric vehicle necessitates effective cell equalization to maintain the state-of-charge of each cell at the same level. In this work, an improved module-based cell-to-pack-to-cell (CPC) equalization system is developed, where the module-level (ML)/cell-to-module-to-cell (CMC) equalizers are utilized for equalization of the battery modules/cells in each module. Compared with the conventional CPC balancing system, it has the advantages of simple modular structure and convenient maintainability. Then, a two-layer model predictive control (MPC) strategy is proposed, in which the ML equalizers are controlled by the top-layer MPC and the controlled CMC equalizing currents in each module are designed by the bottom-layer MPC algorithms in parallel. Its computational complexity is much less than the centralized MPC, which makes it more feasible for real-time cell equalization implementation in practical applications. A rigorous mathematical convergence proof of the proposed equalization control strategy is provided based on the Lyapunov stability theorem. At last, extensive results are provided to verify the proposed improved module-based CPC equalization system and the two-layer MPC-based equalization control approach with excellent equalization performance being demonstrated.

Network serveability (NS), which considers both channel availability (CA) and service retainability (SR), is a key indicator to concisely express the performance of cognitive radio networks (CRNs). However, CA cannot guarantee connection setup if receiver’s accessibility (RxA) is neglected. Likewise, SR yields imperfect results if RxA is ignored. As such, the two rather incomplete performance indicators misrepresent NS and lead to an overestimated satisfaction level of users. Aiming at reliable and concise analysis of CRNs’ performance, this letter introduces the concept of connection availability (CoA), which encompasses both CA and RxA for a user. Besides, it introduces service maintainability (SM), which incorporates the impact of RxA into SR. Consequently, the performance is represented more concisely through network serviceability (NeS), a concept we introduce to consider both CA and SM. We show that CoA, SM, and NeS diverge with various proportions from CA, SR, and NS, respectively, under variable traffic loads and channel failure rates. This indicates the degree of performance difference RxA introduces, and provides network designers the basis for dependable CRN budgeting.

The shovel – dumper system is used for the transportation of ore within the mine to improve the productivity of the Indian surface mines. To meet the production target and effective usage, the shovels and dumpers should be maximum reliability and availability. Keeping this in mind, reliability, availability, and maintainability (RAM) of shovel and dumper system were analyzed at surface limestone mine. In this article, the failure and repair data of a set of shovel and dumper i.e., one shovel (ME1) and one dumpers (ME2) were analyzed graphically and statistically to evaluate RAM. The graphical methods involving trend tests and serial correlation tests were used to validate the IID of their MTBF and MTTR. Statistically, the Weibull distribution is selected because the best-fit distribution by using the K-S tests. It is found that ME1 and ME2 had the reliability of 0.348 and 0.292 respectively for particular MTBF. Based on the preventive maintenance, the reliability can be achieved for 70% and 80% for different time intervals.

Sustainability is becoming an increasingly important topic. Information Technology (IT) is an important factor for sustainability; it consumes a substantial, and growing, part of the world supply of energy, but it can also enable significant insights and improvements related to sustainability. These factors need to be taken into account in the design of IT systems, meaning that we need to architect for sustainability. This paper provides insights into the experience and beliefs of IT practitioners and researchers into current and desired practices of architecting for sustainability. It reports on the results of three workshop sessions with practitioners and researchers, providing insight into the state of research and practice.

Eine Software braucht immer neue Funktionalitäten sowie Fehlerbehebungen. Die Wartbarkeit von einer Software ist für Unternehmen in diesem Bereich nicht wegzudenken. Jedoch kommt es immer wieder vor, dass aufgrund gewisser Gründe, wie zum Beispiel Zeitmangel, komplexe IT-Systeme so (weiter)entwickelt werden, dass sie nicht mehr verständlich und somit nicht mehr wartbar sind. Wenn ein System jedoch über eine hohe Wartbarkeit verfügt, ist es einfacher, Verbesserungen in anderen Qualitätsbereichen vorzunehmen, zum Beispiel das Beheben eines kritischen Sicherheitsfehlers. Unter Wartbarkeit versteht man die Leichtigkeit, mit der ein Softwaresystem über seinen Lebenszyklus hinweg geändert, erweitert und repariert werden kann. Es umfasst verschiedene Faktoren wie die Lesbarkeit des Codes, den modularen Aufbau, die Dokumentation sowie die Verfügbarkeit von Ressourcen und Tools für die Wartung. Ein hochgradig wartbares Softwaresystem weist Eigenschaften auf, die es Entwickler*innen ermöglichen, effizient Änderungen vorzunehmen, Fehler zu beheben und sich an sich ändernde Anforderungen anzupassen. Die umfangreiche Literaturrecherche sowie die Implementierung einer Web-Applikation haben gezeigt, dass die Konzentration auf Design-Prinzipien einen erheblichen Einfluss dazu hat, eine wartbare Software zu entwickeln. Das Ziel dieser Arbeit ist es, diese Methodiken sowie Strategien ausführlich zu beschreiben, die in Software-Projekten angewendet werden können, um eine optimale Wartbarkeit zu erzielen. Software always needs new functionalities and bug fixes. The maintainability of software is indispensable for companies in this area. In many cases, certain factors, such as time constraints, can lead to the development of complex IT systems that become increasingly unintelligible and challenging to maintain. However, when a system has high maintainability, it is easier to claim improvements in other quality areas, such as fixing a critical security bug. Maintainability is the ease with which a software system can be changed, extended, and repaired throughout its life cycle. It includes various factors such as code readability, modularity, documentation, and availability of resources and tools for maintenance. A highly maintainable software system exhibits characteristics that enable developers to efficiently make changes, troubleshoot, and adapt to changing requirements. An extensive literature research and the implementation of a web application have shown that concentrating on design principles has a significant impact on developing maintainable software. The aim of this work is to describe in detail these methodologies and strategies that can be applied in software projects to achieve optimal maintainability. Abweichender Titel laut Übersetzung der Verfasserin/des Verfassers Masterarbeit Wien, FH Campus Wien 2023

In previous research the importance of both Markov and semi-Markov models in manpower planning is highlighted. Maintainability and attainability of personnel structures for different types of personnel strategies (i.e. under control by promotion and control by recruitment) is extensively investigated for various types of Markov models (homogeneous as well as non-homogeneous). Semi-Markov models are extensions of Markov models that account for length of stay in the states. Less attention is paid to the study of maintainability and attainability for semi-Markov models. Although, some interesting maintainability results were obtained for non-homogeneous semi-Markov models. The current paper focuses on discrete-time homogeneous semi-Markov models, and explores concepts of maintainable and attainable personnel structures in this setting. Various types of personnel strategies are presented for which the set of maintainable and attainable structures is examined. The obtained insights can easily be converted to various application domains.

This paper discusses the progress made so far and future challenges in integrating the analysis of multiple Non-Functional Properties (NFP) (such as performance, schedulability, reliability, availability, scalability, security, safety, and maintainability) into the Model-Driven Engineering (MDE) process. The goal is to guide the design choices from an early stage and to ensure that the system under construction will meet its non-functional requirements. The evaluation of the NFPs considered in this paper uses various kinds of NFP analysis models (also known as quality models) based on existent formalisms and tools developed over the years. Examples are queueing networks, stochastic Petri nets, stochastic process algebras, Markov chains, fault trees, probabilistic time automata, etc. In the MDE context, these models are automatically derived by model transformations from the software models built for development. Developing software systems that exhibit a good trade-off between multiple NFPs is difficult because the design of the software under construction and its underlying platforms have a large number of degrees of freedom spanning a very large discontinuous design space, which cannot be exhaustively explored. Another challenge in balancing the NFPs of a system under construction is due to the fact that some NFPs are conflicting—when one gets better the other gets worse—so an appropriate software process is needed to evaluate and balance all the non-functional requirements. The integration approach discussed in this paper is based on an ecosystem of inter-related heterogeneous modeling artifacts intended to support the following features: feedback of analysis results, consistent co-evolution of the software and analysis models, cross-model traceability, incremental propagation of changes across models, (semi)automated software process steps, and metaheuristics for reducing the design space size to be explored.

Системы SAPFOR и DVM были спроектированы и предназначены для упрощения разработки параллельных программ научно-технических расчетов. Главной целью системы SAPFOR является автоматизация процесса отображения последовательных программ на параллельные архитектуры в модели DVMH. В некоторых случаях пользователь системы SAPFOR может рассчитывать на полностью автоматическое распараллеливание, если программа была написана или приведена к потенциально параллельному виду. DVMH модель представляет собой расширение стандартных языков C и Fortran спецификациями параллелизма, которые оформлены в виде директив и не видимы стандартным компиляторам. В статье будет рассмотрено автоматизированное дополнительное распараллеливание существующих MPI-программ с помощью системы SAPFOR, где, в свою очередь, будут использованы новые возможности DVMH модели по распараллеливанию циклов в MPI программе внутри узла. Данный подход позволяет существенно снизить трудоемкость распараллеливания MPI программ на графические ускорители и многоядерные процессоры, сохранив при этом удобство сопровождения уже написанной программы. Данная возможность в системе SAPFOR была реализована для языков Fortran и C. Эффективность данного подхода показана на примере некоторых приложений из пакета NAS Parallel Benchmarks. The SAPFOR and DVM systems are primarily designed to simplify the development of parallel programs of scientific-technical calculations. SAPFOR is a software development suite that aims to produce a parallel version of a sequential program in a semi-automatic way. The fully automatic parallelization is also possible if the program is well-formed and satisfies certain requirements. SAPFOR uses the DVMH directive-based programming model to expose parallelism in the code. The DVMH model introduces CDVMH and Fortran-DVMH (FDVMH) programming languages which extend the standard C and Fortran languages by parallelism specifications. We present MPI-aware extension of the SAPFOR system that exploits opportunities provided by the new features of the DVMH model to extend existing MPI programs with intra-node parallelism. In that way, our approach reduces the cost of parallel program maintainability and allows an MPI program to utilize accelerators and multicore processors. SAPFOR extension has been implemented for both Fortran and C programming languages. In this paper, we use the NAS Parallel Benchmarks to evaluate the performance of generated programs.

With the improvement of people’s cultural level, more and more museums are being built or renovated. The design of lighting products for museums is a specialized field that requires designers to take into account a variety of factors, such as safety, presentation, and maintainability. As museum lighting systems meet the needs of conservation, visitor experience, and maintenance, the traditional design process is limited by the experience of the designer and the actual situation of the museum, and the actual light conservation effect of the exhibits is difficult to quantify. We have designed a digital-twin-based intelligent lighting system for museums, which can facilitate museum managers to quantify and manage the light life of exhibits while providing a more immersive viewing experience and recognition effect for visitors.

Due to their critical influence on manufacturing accuracy, machine tool feed drives and the monitoring of their condition has been a research field of increasing interest for several years already. Accurate and reliable estimates of the current condition of the machine tool feed drive’s components ball screw drive (BSD) and linear guide shoes (LGSs) are expected to significantly enhance the maintainability of machine tools, which finally leads to economic benefits and smoother production. Therefore, many authors performed extensive experiments with different sensor signals, features and components. Most of those experiments were performed on simplified test benches in order to gain genuine and distinct insights into the correlations between the recorded sensor signals and the investigated fault modes. However, in order to build the bridge between real use cases and scientific findings, those investigations have to be transferred and performed on a more complex test bench, which is close to machine tools in operation. In this paper, a condition monitoring test cycle is developed for such a test bench. The developed test cycle enables the recording of a re-producible data basis, on which models for the condition monitoring of BSDs and LGSs can be based upon.

There has been a growing interest in integrating vegetation into the built environment in order to ameliorate the negative effects of increasing urbanisation. In Singapore, government policies encourage the inclusion of skyrise greenery into new and existing buildings. To further streamline workflows, statutory BIM (Building Information Modelling) submissions in architecture, engineering and construction (AEC) industries have been mandated. However, landscape plans are still excluded from these BIM submissions due to the lack of a centralised vegetation database and the absence of a standardised BIM format for landscape architectural submissions. This paper presents a streamlined methodology for creating and using a centralised vegetation library for landscape architects. The workflow leverages off the Industry Foundation Classes (IFC) standard for data exchange regardless of the BIM authoring software used and provides a framework of four operational modules: an expandable and low-maintenance species-level vegetation library, a BIM authoring workflow that allows inclusion of vegetation objects, an IFC interface, and a lightweight 3D vegetation model generator. This paper also showcases a use-case of embedding information-enriched 3D vegetation objects into a simulated landscape plan. The proposed workflow, when adopted in AEC industries, will enable governing agencies to track diverse greening efforts by the industry and to potentially include other measurements such as cooling performance or maintainability.

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.

11th International Conference on Through-life Engineering Services - TESConf2022 8-9 November 2022, Cranfield UK Due to the rising environmental awareness and fluctuating fuel prices over the past decade, several countries started collaborating on a national program to achieve the climate agreement goals of the Paris agreement. At the moment, one of the most crucial challenges of the electrification process is the replacement of conventional engines. As there is a substantial gap in energy density between fuel and batteries per unit volume, the consequence is increasing aircraft weight after electrification. The overall stability and configuration of the aircraft are affected by the altered weight, hence requiring further analysis. This paper focuses on discussing and proposing future solutions for the battery storage system in terms of maintainability and position in the aircraft. Methodology-wise, to validate the research solutions the paper uses a conventional aircraft planned to be retrofitted with a hybrid propulsion system as a case study. The results show that the battery system has to be separated into two main categories, namely the energy and structural storage system where the former concerns the selection of battery type and defining the battery size/ weight based on the required energy output and whereas the latter regards the positioning and structural design of the battery storage system. DMG Mori

Effective software maintenance is a crucial factor to measure that can be achieved with the help of software metrics. In this paper, authors derived a new approach for measuring the maintainability of software based on hybrid metrics that takes advantages of both i.e. static metrics and dynamic metrics in an object-oriented environment whereas, dynamic metrics capture the run time features of object-oriented languages i.e. run time polymorphism, dynamic binding etc. which is not covered by static metrics. To achieve this, the authors proposed a model based on static and hybrid metrics to measure maintainability factor by using soft computing techniques and it is found that the proposed neuro-fuzzy model was trained well and predict adequate results with MAE 0.003 and RMSE 0.009 based on hybrid metrics. Additionally, the proposed model was validated on two test datasets and it is concluded that the proposed model performed well, based on hybrid metrics.

El modelo de gestión de mantenimiento tiene como objetivo mejorar los índices de disponibilidad operativa aplicando estrategias de monitoreo, control y evaluación con retroalimentación directa en la unidad que proporciona el mantenimiento a los Volquetes Sinotruk del Gobierno Autónomo Descentralizado del Cantón El Carmen (GADMEC), tomando como fuente, el histórico de fallos del sistema y adoptando las particularidades del proceso de mejora continua. La metodología utilizada permite el tratamiento de las variables mediante la ejecución de 5 etapas: definición estrategias del mantenimiento en función del modelo de gestión de mantenimiento basado en el ciclo de Deming que implica 4 pasos: planear, hacer, verificar y actuar (PHVA) propuesto en la norma ISO 9001:2015; la implementación de las estrategias de mantenimiento como herramientas de gestión, el análisis de criticidad de los activos sujetos de estudio, la ejecución de metodología de análisis confiabilidad, mantenibilidad y disponibilidad (CMD) y finalmente, la selección de estrategias de mejoramiento para el manejo recursos. El análisis CMD logró determinar el comportamiento de los indicadores técnicos de gestión de mantenimiento en un periodo determinado de tiempo; los datos obtenidos fueron procesos de forma sistemática y la información resultante permitió medir la incidencia de las estrategias aplicadas, evaluando su comportamiento en función de sus indicadores, estableciendo el crecimiento real de la productividad con la implementación del modelo teórico de gestión de mantenimiento, cuyo enfoque logístico logró la integración entre las unidad de mantenimiento y los activos del Gobierno Autónomo Descentralizado del Cantón El Carmen. Palabras clave: Disponibilidad operativa, estratégicas, gestión de mantenimiento, confiabilidad, mantenibilidad, disponibilidad.

PurposeThe purpose of this research is to calculate and enhance the cheese cheddar manufacturing plant efficiency under actual workplace conditions by measuring reliability, availability and maintainability (RAM) indices. The authors highlight how RAM analysis is important in determining periodic maintenance and in scheduling and managing the appropriate maintenance policy.Design/methodology/approachThe current work is conducted using statistical approaches to evaluate failure and repair statistics. The RAM estimation was calculated on the basis of quantitative data obtained over a span of 32 months. Descriptive statistics, Pareto analysis, as well as the presumption of independence were ensured through trend and serial correlation tests. In addition, the reliability and maintainability of the cheddar cheese processing plant and its machines were calculated at various mission periods.FindingsThe primary goal of the implementation approach is to understand the fault patterns and the accurate quantitative assessment of the reliability and maintainability of the cheddar production plant. The findings revealed the essential aspects of the line, which need improvement by an appropriate maintenance program.Originality/valueThis study is intended to serve to highlight the RAM assessment and its impact on the performance of the real-time system. The benefit of the technique is the continual control of the manufacturing process by means of acceptable indexes, whose use corresponds to a continuous improvement process.

Programming teachers very often assess their students' submissions solely from their correctness, sometimes with the help of an automated-grading platform. This approach is arguably effective and efficient at the same time. Unfortunately, this single-dimension assessment approach narrows the students' perspective on a high-quality solution to just a working solution. In the real world setting, a solution should be maintainable with minimal cost. Maintainability is closely related to code quality. In this paper, we present a web-based tool that would help the teachers to assess the students' submissions from both correctness and quality in one place. In this tool, we integrate GitHub Classroom and SonarQube.

The Sichuan-Tibet Railway is facing extraordinary challenges in terms of construction, operation, and maintenance because of its extremely complicated natural environment and geological conditions. Consequently, countermeasures are necessary and urgent to ensure its safety and reliability in the whole life cycle. This study proposes a novel reliability framework to guarantee the ideal operation state of the Sichuan-Tibet Railway. Reliability application in many fields are summarized, including military equipment, rail locomotive, and railway engineering. Given the fact that the Sichuan-Tibet Railway is a complex giant system, Nine-Connotation was summarized (i.e., safety, inherent reliability, testability, maintainability, supportability, environmental adaptability, predictability, resilience, and durability) under the goal of optimizing the operational efficiency. On the basis of the concept of the Nine-Connotation and the understanding of reliability transmission mechanism, the framework of reliability for the Sichuan-Tibet Railway was established, which can facilitate a comprehensive and real-time evaluation of all situations with a clear hierarchy. The proposed framework is composed of a resilience management system, an integrated technology system, and a dynamic reliability assessment system. The pathway for its application on railway construction was developed in this study. The proposed framework can assist in well-informed decisions for the construction, as well as the operation of the Sichuan-Tibet Railway. On the basis of a top-down design concept for the first time, this study emphasizes the railway’s availability and validity to complete the assigned tasks as a whole, that is, operational efficiency. It also shows the reliability transmission and control mechanism of the railway’s giant complex system, innovating and establishing the management principle of great safety and great reliability over the life cycle.

Code smell is a software quality problem caused by software design flaws. Refactoring code smells can improve software maintainability. While prior works mostly focused on Java code smells, only a few prior researches detect and refactor code smells of Python. Therefore, we intend to outline a route (i.e. sequential refactoring operation) for refactoring Python code smells, including LC, LM, LMC, LPL, LSC, LBCL, LLF, MNC, CCC and LTCE. The route could instruct developers to save effort by refactoring the smell strongly correlated with other smells in advance. As a result, more smells could be resolved by a single refactoring. First, we reveal the co-occurrence and the inter-causation between smells. Then, we evaluate the smells’ correlation. Results highlight seven groups of smells with high co-occurrence. Meanwhile, 10 groups of smells correlate with each other in a significant level of Spearman’s correlation coefficient at 0.01. Finally, we generate the refactoring route based on the association rules, we exploit an empirical verification with 10 developers involved. The results of Kendall’s Tau show that the proposed refactoring route has a high inter-agreement with the developer’s perception. In conclusion, we propose four refactoring routes to provide guidance for practitioners, i.e. {LPL [Formula: see text] LLF}, {LPL [Formula: see text] LBCL}, {LPL [Formula: see text] LMC} and {LPL [Formula: see text] LM [Formula: see text] LC [Formula: see text] CCC [Formula: see text] MNC}.

Purpose.The aim of the study is to determine and analyse causes of faults in the operation of TR-7A scraper conveyor and to estimate the required time for their remediation and select the methods of their prevention and elimination. Methods. The characteristic of a system, such as the scraper conveyor, intended to fulfil its specified function in time and operation conditions, can be studied, theoretically, by determining its operational reliability. This implies the existence of a framework that incorporates several interconnected components of technical, operational, commercial and management nature. The quantitative expression of reliability was based on elements of mathematical probability theory and statistics (exponential distribution law), failure and repair mechanism not being subject to certain laws. Findings. The following TR-7A subassemblies, if defective, could have been the cause of a failure: chains, hydraulic couplings, chain lifters, drive, return drums, some electrical equipment. After 28 months of monitoring the TR-7A operation, we have established the number of failures (defects) ni, the operating time between failures ti, frequency of failures fc, time to repair tri, weight repair time pr, mean time between failures (MTBF), mean time to repair (MTR). Originality.Data collection and processing involves the adoption of specific procedures to allow the correct highlighting of the causes and frequency of failures. The accomplishment of this approach allowed finding the solutions for increasing reliability of some subassemblies of TR-7A conveyor (i.e., those subjected to abrasive wear). Practical implications.One solution was to use materials with compositional and functional gradient in the case of worn surfaces of some subassemblies. It was successfully applied for the chain lifters where a significant increase in the mean time between failures was obtained. The field of application of these materials can be extended to the metal subassemblies of machines and equipment with abrasion wear that occurs both in underground mines and in quarries.

The design of a safety-critical system requires an effective prediction of its reliability, availability, maintainability, and safety (RAMS). Anticipating the RAMS analysis at the concept design helps the designer in the tradeoff of the system architecture and technologies, reduces the cost of product development and the time to market. This action is rather difficult, because the RAMS analysis deals with the hazard assessment of system components, whose abstraction at concept level is never simple. Therefore, to integrate the system design and RAMS assessment, a clear path to follow is required. This article investigates how the model-based systems engineering supports this task and drives the system reliability allocation, through the functional and dysfunctional analyses. The implementation of the proposed approach needs to set up the tool chain. In the industrial context, it must be compatible with practices, standards, and tools currently used in product development. Defining a suitable process of integration of tools used for the system design and the safety engineering is a need of the industry. Therefore, this task is also discussed, in this article, dealing with some examples of industrial test cases.

A quality model is a conceptual decomposition of an abstract notion of quality into relevant, possibly conflicting characteristics and further into measurable metrics. For quality assessment and decision making, metrics values are aggregated to characteristics and ultimately to quality scores. Aggregation has often been problematic as quality models do not provide the semantics of aggregation. This makes it hard to formally reason about metrics, characteristics, and quality. We argue that aggregation needs to be interpretable and mathematically well defined in order to assess, to compare, and to improve quality. To address this challenge, we propose a probabilistic approach to aggregation and define quality scores based on joint distributions of absolute metrics values. To evaluate the proposed approach and its implementation under realistic conditions, we conduct empirical studies on bug prediction of ca. 5000 software classes, maintainability of ca. 15000 open-source software systems, and on the information quality of ca. 100000 real-world technical documents. We found that our approach is feasible, accurate, and scalable in performance.

In highly-integrated electronic circuits designs, power reduction must be properly addressed. The standardized ways of power-intent specification are unbearable in modern complex designs, since they extensively prolong the time-to-market of products. In this article, we propose a simplified method of designing energy-efficient systems at the register-transfer level, which is fully compatible with the existing design flow and industrial automation tools. The power-intent specification is abstract enough to be easily integrated into the HDL model, which also simplifies its maintainability. A connection to later design-flow stages (i.e. lower abstraction levels) is achieved by automated synthesis, which translates the simplified specification into the standard means, supported by the existing professional design-automation tools. The benefit of the proposed design method is speed-up of the development process, reduced number of possible power-intent errors, and easier energy-efficient systems design. Such design can be utilized by all designers, even those, which were unable to utilize the standard means due to high complexity. The experiments using 10 000 power-intent specification samples have shown that the proposed specification method is approximately 23-times less complex (in terms of lines of code) than the standard method. Moreover, it is able to achieve the same power-consumption reduction, while requiring much less designer effort.

A sugar manufacturing plant is a complex industrial system having five subsystems arranged in a series configuration and each subsystem followed a different failure rate. Upon ensues of a random failure, the failed subsystem stops working and forces the complete system to stop and results in a downstate of the plant. The impact of downstate directly influences the production of plant and its reliability. Here, a reliability and maintainability analysis of the sugar manufacturing plant has been carried out at the subsystem and plant level. Data collection has been performed for six months from the sugar plant and descriptive statistical analysis has been made for time to repair and time between failures. The best-fitted distribution and parameters were determined along with trend and serial correlation analysis to attain the best performance of the plant. Additionally, graphs for reliability and hazard rate modes for five subsystems and the entire plant were depicted. The suggested models might be a suitable tool towards (a) considering the recent conditions, and (b) forecasting reliability for refining the sugar manufacturing plant by applying proper maintenance policy.

Facade cleaning of high-rise buildings requires automation due to the risk and inefficiency of a fall accident for human workers. Recently, due to the need for automation, various types of facade cleaning robots have been developed. In our previous study, the gondola-mounted type cleaning robot was developed, and it showed several issues. In this article, we propose an improved design feature to solve the issues. First, we modularized the robot design for lightweight and maintainability. Second, we implemented passive obstacle overcoming mechanism with tri-star wheel and compliant manipulator for minimizing uncleaned area near obstacles. Third, we developed the position sensing device for measurement and compensation of lateral disturbance occurred by swinging gondola. To verify the cleaning performance of the robot, experiments were conducted with different scenarios of cleaning general plane surface, obstacle overcoming, and lateral disturbance applied and compensated. Experimental results of both lab test and field-test performed on a real-world building were analyzed and summarized in this article.

With version 9, Java has been given the new module system Jigsaw. Major goals were to simplify maintainability of the JDK and improve its security by encapsulating modules’ internal types. While the module system successfully limits the visibility of internal types, it does not prevent sensitive data from escaping. Since the module system reasons about types only, objects are allowed to escape even if that module declares the type as internal. Finding such unintended escapes is important, as they may violate a module’s integrity and confidentiality, but is a complex task as it requires one to reason about pointers and type hierarchy. We thus present ModGuard , a novel static analysis based on Doop which complements the Java module system with an analysis to automatically identify instances that escape their declaring module. Along with ModGuard we contribute a complete formal definition of a module’s entrypoints, i.e., the method implementations that a module actually allows other modules to directly invoke. We further make available a novel micro-benchmark suite MIC9Bench to show the effectiveness but also current shortcomings of ModGuard , and to enable comparative studies in the future. Finally, we describe a case study that we conducted using Apache Tomcat, which shows that a migration of applications towards Jigsaw modules does not prevent sensitive instances from escaping, yet also shows that ModGuard is an effective aid in identifying integrity and confidentiality violations of sensitive instances.

The study designed and developed RECORDS (Research and Extension Completed and On-going Registered programs Database System which will serve as the central storage of data of SLSU Research and Extension offices. The development of the system used VB.Net as a programming language and MySQL as database of the system application to function properly. This research followed the process of developmental research. It was conducted during the school year 2019-2020 at SLSU Campus Lucena The developed software and data base system were evaluated by IT experts, selected members of Research and Extension Council and researchers and extensionists of SLSU. The parameters used in evaluating the developed system were functionality, reliability, usability, efficiency, maintainability, portability and security. The evaluation result showed that the 30 respondents highly accepted the system. Overall rating of the RECORDS evaluation got the average weighted mean of 3.79 with equivalent interpretation of highly acceptable. This implied that, the developed RECORDS (Research and Extension Completed and On-going Registered programs Database System) can be utilized by the SLSU Research and Extension Offices.

PurposeAirport construction is extremely different than the construction of any other transport infrastructure. It is a vital area affecting both the environment and the economy. Therefore, sustainable selection of building materials represents a very important step. The main objective of this paper was to develop a set of sustainable assessment criteria (SAC) to assist design team members in the selection between two different material alternatives when constructing a new runway in Kuwait international airport. The proposed materials were asphalt or concrete.Design/methodology/approachA set of 24 sub-criteria were developed, those were emerged from three main criteria: technical, environmental and socio-economic. Fuzzy analytical hierarchy process (FAHP) was employed to assign weights and to measure the relative importance of these criteria for the material alternatives selection. The prioritizing process for criteria was based on a survey of 100 responses.FindingsIt had been concluded from the use of FAHP that asphalt material was a better alternative in maintainability, ease of construction, health and safety, initial cost and energy saving. Concrete was better in fire resistance, durability, decay resistance, energy saving and thermal insulation, maintenance cost, aesthetics, minimizing pollution, impact on air quality, low toxicity, environmentally disposal sound system, amount of likely wastage and raw material extraction method.Originality/valueDevelop a set of SAC to assist design team members in deciding between two material alternatives to construct a runway.

PurposeThe maintenance of green building technologies such as building-integrated photovoltaic (BIPV) is a challenge due to the non-existence of maintainability considerations during the design stage. This led to building defects which accounts to high expenditures throughout the building's lifecycle. The use of BIPV in buildings is an emergent trend, and further research is requisite for their maintainability. This paper assesses the performance and maintainability of BIPV façade applications based on the green maintainability design considerations.Design/methodology/approachQualitative method is undertaken in this study, which includes field surveys, instrumental case studies and stakeholder interviews to probe the issues linked with the BIPV's maintainability.FindingsFindings have shown some technical defects discovered in BIPV applications in tropical areas, as well as issues on cost, aesthetics and implementation are the main causes for the low adoption of BIPV in Singapore.Originality/valueUnderstanding the research outcomes will embolden designers and allied professionals to team up in ensuring the long-term maintainability and sustainability of green building technologies. This research gives recent and important information in the design, installation and maintainability of BIPV, as well as good practices that would add value to facilities management and to the design of green building technologies.

PurposeThe paper aims to convert into useable guidelines, the knowledge related to human factors and tasks' organisation, which are embedded in one of the most exciting maintenance actions that are carried out, the pitstop in Formula 1 races.Design/methodology/approachThe paper opted for a fault tree analysis (FTA) to de-construct all the sub-tasks and their possible deviations from desirable situations and to evaluate the most relevant information needed for carrying out the pitstop operation. Besides, the SHELL model was applied in a second stage to evaluate the interaction between human being and human interfaces with other components of the system. Once this set of information was crystallised, the research translated it into useable guidelines for organising industrial maintenance actions using the same approach and possible reaching the same results.FindingsThe results of this study is a structured set of guidelines that encompasses the most paramount aspects that should be considered for setting correct maintenance actions. They represent a “guide” for including the different angles that are included during these operations.Research limitations/implicationsThe guidelines are potentially applicable to every maintenance operation. The guidelines should be tested on different working domains to check their applicability besides the racing world.Practical implicationsThis study is a reverse engineering work for creating a scheme to include into maintenance operations aspects such as crew athlete-like fitness, training, technology, organisational issues, safety, ergonomics and psychology.Originality/valueThe value of the paper is deconstructing the results of one of the most successful and prepared maintenance action. The paper takes a different approach in proposing how to structure and create maintenance solutions. The difference in approaches between the maintenance during the pitstop of Formula 1 car and industrial applications enhances the gap that needs still to be filled for further improving maintenance actions out of the racing world.

Un sistema de gestión de mantenimiento basado en la confiabilidad operativa se fundamenta en el proceso de mejora de los indicadores de mantenimiento técnico, en el cual, se aplica un modelo de gestión por etapas, desarrollado y ejecutado según las condiciones actuales de la planta, con el fin de optimizar los procesos de planificación, programación y ejecución del mantenimiento a nivel preventivo. El empleo de una metodología que permita evaluar las variables inherentes y las características operacionales del sistema permite aumentar el rendimiento de la unidad de mantenimiento, al realizar un tratamiento integral de la gestión de activos y gestión organizacional para un real tratamiento del plan de mantenimiento. Este proceso de evaluación se lo realizo mediante un análisis con metodología RAM, la cual permite establecer el comportamiento la mantenibilidad, confiabilidad y disponibilidad como indicadores técnicos de gestión en función de los requerimientos de producción volumétrico de agua tratada para los centros hospitalarios como la empresa DIALILIFE S. A. que, mediante el procesamiento de los datos obtenidos de las evaluaciones sistemáticas, logró establecer un modelo teórico enfocada la mejora continua, y así mismo, establecer la incidencia de la aplicación de la gestión, con las mejoras los tiempos promedios entre fallas “TPEF”, los tiempos promedios para reparar “TPPR” y disminuir el número paradas programadas o no programadas de planta, como aporte fundamental al aumento de la confiabilidad de los equipos de la planta de tratamiento de agua. Palabras clave: Confiabilidad operativa, gestión de mantenimiento, mantenibilidad, disponibilidad.

A software system’s design determines many of its properties, such as maintainability and performance. An understanding of design is needed to maintain system properties as changes to the system occur. Unfortunately, many systems do not have up-to-date design documentation and approaches that have been developed to recover design often focus on how a system works by extracting structural and behaviour information rather than information about the desired design properties, such as robustness or performance. In this paper, we explore whether it is possible to automatically locate where design is discussed in on-line developer discussions. We investigate and introduce a classifier that can locate paragraphs in pull request discussions that pertain to design with an average AUC score of 0.87. We show that this classifier, when applied to projects on which it was not trained, agrees with the identification of design points by humans with an average AUC score of 0.79. We describe how this classifier could be used as the basis of tools to improve such tasks as reviewing code and implementing new features.

The problem of modeling the process of functioning of redundant measuring instruments is considered. The determination of the frequency of verification of complex duplicate measuring instruments is validated on the basis of a semi-Markov model of the process of functioning of the instruments. The importance of the use of the theory of semi-Markov processes for modeling the functioning of redundant technical systems, including measurement systems, is demonstrated. A semi-Markov model of the process of functioning of measuring instruments by means of which the influence of such factors as the frequency of verification, support of measuring instruments with spare parts, level of failure-free performance, and degree of maintainability on the reliability of measuring instruments may be taken into account is developed. A method of specifying a semi-Markov process that correctly and adequately approximates the true process is found. The availability factor of the measuring instruments is selected as the indicator of the operating efficiency of the functioning of a measuring instruments and of the corresponding model.

The railway is one of the most prominent models of transportation across the globe and it carries a large number of people, thus requiring high reliability, maintainability and safety. The reliability of railways mostly depends on an effective signalling system, making it one of the critical parts of railway operation. A signalling system is part of a large array of systems with interconnected components and subcomponents. Therefore, there is a need to make the signalling system more reliable and optimised with enhanced fault detection. Proper inspection and maintenance are required to make the signalling system reliable and safe. In this study, different inspection modelling techniques are applied to find the reliability of the signalling system. The signalling system has been divided into subsystems (signal unit, track unit, point-and-point machine) considering their importance and their effects on the failure rate of the entire signalling system. Inspection modelling of each subsystem has been conducted to provide the basis for the entire signalling system. A case study has been investigated to validate the model developed in one of the busiest tracks in eastern India. The obtained data thus are used to analyse the inspection pattern of signalling subsystems. Special attention to maintenance for inspection activities and logistics support has been taken into consideration, which is required to improve the reliability and maintainability of signalling subsystems and systems to make the railway signalling system sustainable in the long run.

In recent years, the international community has become increasingly aware of the scale and severity of the problems posed by landmines and explosive remnants of war, including unexploded ordnance, gradually agreeing that this is a global problem that requires international concerted actions [1]. Significant excess of pace of development and intensity of mines use in comparison with the means of demining determine the urgency of the problem of ensuring the required level of their technical perfection. At the same time, special attention should be paid to ensuring the required level of quality of demining processes, reducing to a minimum level of explosive threats and cost of demining [2]. In modern economic conditions, the high efficiency of UXO detection in a certain area with relatively minimal cost of material and human resources is of great importance. The article analyzes the possibility of detecting explosive ordnance using a thermal imager, hyperspectral camera, magnetometer, metal detector which are installed on an unmanned aerial system (UAS). In addition, there was given consideration to the properties of sensors for detecting explosive ordnance which will ensure their full use during humanitarian demining: performance, transportability, survivability, reliability, failure-free, durability, maintainability, storage ability, cost effectiveness. Explosive ordnance detection sensors mounted on UAS must have their own navigation system or be connected to an on-board navigation system that links information from the sensors to the terrain. It must be possible to determine the coordinates of any object after landing an UAS and process information from the sensors. The calculations were made regarding the effectiveness of actions for searching and detecting explosive ordnance using an unmanned aerial system.

Load Haul Dumpers (LHDs) are prominent equipment employed for transportation operations in many of the underground mines. This equipment often suffers from frequent breakdowns due to a variety of technical and managerial practices resulting in increased maintenance costs and loss of production and productivity. Reliability, Availability and Maintainability (RAM) analysis deal with the optimal functioning of equipment, maintenance scheduling, controlling cost, and improvement of availability and performance. Keeping this in view, the current study focused on the estimation of the performance of the equipment using RAM investigation. The required failure and repair data of LHDs were collected from field investigations. Graphical analyses using Trend and serial correlation tests and analytical analysis using Statistic-U test were conducted to validate the Independent and Identical Distribution (IID) nature of the data sets. Based on the above tests, the Renewal Process was adopted to carry out the RAM analysis. The best-fit approximation of datasets was selected by performing the Kolmogorov–Smirnov (K–S) test. In addition to that, the reliability-based Preventive Maintenance time intervals were estimated to improve the percentage of reliability.

Bad smells are indicators of possible problems in software. Refactoring is usually undertaken to eradicate bad smells. Many studies have investigated the impact of bad smells on software quality, however, only a few have proposed methods to prioritize bad smells. The objective of this paper is to propose a model to prioritize bad smells based on their impact on software maintainability. We use the analytical hierarchy process (AHP) to prioritize bad smells based on their maintainability impact by measuring the code before and after refactoring. The model is validated against five bad smells and five open-source projects. In addition, a visualization of the relationships between classes’ maintainability and its bad smells’ ranking is presented. The prioritization model can help software practitioners in prioritizing their effort and better utilizing their resources. The proposed prioritization model provides an effective method to prioritize the impact of bad smells on maintainability and it can be extended to prioritize the impact of bad smells on other quality attributes.

The methodical bases of complex substantiation of requirements to reproducibility of difficult technical systems of military purpose are considered in the article. The procedure for conducting a comprehensive assessment of the possibility of restoring complex technical systems for military purposes is proposed. It is shown that in order to solve this problem it is necessary to solve a whole set of problems. The main ones are: failure analysis (disability) of complex technical systems for military purposes. Why it is necessary to decompose; analysis of the defeat of complex technical systems for military use when used for its intended purpose during hostilities; analysis of features of restoration repair and possibilities of repair bodies; substantiation of the relationship between damage, survivability of complex technical systems for military purposes and their reproducibility; to substantiate the need to make changes to the regulatory documentation when substantiating the requirements for the reproducibility of complex technical systems for military purposes. The solution of these problems, as shown in the article, can be based on a systematic approach, which is the basis of the article, the results of which are: the classification of possible damages of difficult technical systems of military purpose in the course of operation is offered; the technique of functional-morphological decomposition of complex technical systems of military purpose is considered; the main features of restoration repair of complex technical systems of military purpose are considered; the relationship between the reproducibility and survivability of complex technical systems for military purposes. It is shown that the considered methodical bases are the basis for substantiation of requirements to maintainability of difficult technical systems of military purpose.

Software Quality is the key priority of today’s marketplace and software development organization to which a system, technique, or factor meets particular requirements and conditions. Soft computing techniques play a vital role in developing software engineering applications. In this paper, we have identified five parameters: Reliability, Efficiency, Usability, Maintainability, and Portability for accessing the level of quality of software. A fuzzy logic-based intelligent identification methodology has been proposed to access the quality of particular software-based on five parameters. The proposed identification scheme takes these five parameters as input and predicts the quality of the software using the fuzzy rule base which is generated using various studies. As this scheme takes five inputs and each input is divided into three regions i.e. ‘Low’, ‘Medium’, ‘High’ and thus a total of 35 i.e. 243 rules has been generated to analyze the software quality. Furthermore, Mamdani fuzzy model has been used as the reference model. To show the effectiveness of the proposed methodology, simulation results have been performed in MATLAB, which shows that the software's quality closely matches with the actual one.

Bad smells represent imperfection in the design of the software system and trigger the urge to refactor the source code. The quality of object-oriented software has always been a major concern for the developer team and refactoring techniques help them to focus on this aspect by transforming the code in a way such that the behavior of the software can be preserved. Rigorous research has been done in this field to improve the quality of the software using various techniques. But, one of the issues still remains unsettled, i.e. the overhead effort to refactor the code in order to yield the maximum maintainability value. In this paper, a quantitative evaluation method has been proposed to improve the maintainability value by identifying the most optimum refactoring dependencies in advance with the help of various meta-heuristic algorithms, including A*, AO*, Hill-Climbing and Greedy approaches. A comparison has been done between the maintainability values of the software used, before and after applying the proposed methodology. The results of this study show that the Greedy algorithm is the most promising algorithm amongst all the algorithms in determining the most optimum refactoring sequence resulting in 18.56% and 9.90% improvements in the maintainability values of jTDS and ArtOfIllusion projects, respectively. Further, this study would be beneficial for the software maintenance team as refactoring sequences will be available beforehand, thereby helping the team in maintaining the software with much ease to enhance the maintainability of the software. The proposed methodology will help the maintenance team to focus on a limited portion of the software due to prioritization of the classes, in turn helping them in completing their work within the budget and time constraints.