Maintenance Processes Research Articles

Predictive maintenance issues and solutions for SMEs – a case study solving a joinery

Many SMEs are characterised by working with older machines that are not Industry 4.0 compliant and that try to meet the qualitative and quantitative standards that the market expects. The machine maintenance strategy and its implementation significantly impact the company's profitability. The research aims to define maintenance and adjustment processes that are difficult to predict and determine their execution times. In the framework of a case study, we analysed maintenance and adjustment processes in an SME that have a high impact on production quality, but the prediction of which is not solved. During the research, we created a mobile application-based microservice suitable for predicting the due dates of these maintenance tasks using historical data. Based on interviews with employees, they became more confident, motivated and engaged. Overall, it can be said that mobile application-based microservices are an effective tool for improve the production quality of SMEs and extend the production life of less advanced machines. In addition, the reduction in the number of complaints led to cost savings and more predictable production. We also found that the application can be easily adapted to other machines, thus further increasing the digital maturity of the SME.

Software-Defined Networking Challenges and Research Opportunities for Future Interest

Software Defined Network (SDN) has become one of the most preferred solutions for the management of large-scale complex networks. The network policies in the large-scale network are difficult to embed on entire network devices simultaneously, whereas in SDN these policies can be embedded on the top of the network. The SDN network is divided into two parts which are vertically integrated to form the entire network. Currently many aspects of the classical architecture of the Internet are etched in stone – a so-called ossification of the Internet – which has led to major obstacles in IPv6 deployment and difficulty in using IP multicast services. Yet, there exist many reasons to extend the Internet, e.g., for improving intra-domain and inter- domain routing for high availability of the network, providing end-to-end connectivity for users, and allowing dynamic management of network resources for new applications, such as data center, cloud computing, and network virtualization. To address these requirements, the next- generation architecture for the Future Internet has introduced the concept of Software-Defined Networking (SDN). At the core of this emerging paradigm is the separation and centralization of the control plane from the forwarding elements in the network as opposed to the distributed control plane of existing networks. With the advent of cloud computing, many ecosystem and business paradigms are encountering potential changes and may be able to eliminate their IT infrastructure maintenance processes. Real-time performance and high availability requirements have induced telecom networks to adopt the new concepts of the cloud model: software-defined networking (SDN) and network function virtualization (NFV). NFV introduces and deploys new network functions in an open and standardized IT environment, while SDN aims to transform the way network’s function. SDN and NFV are complementary technologies; they do not depend on each other. However, both concepts can be merged and have the potential to mitigate the challenges of legacy networks. In this paper, our aim is to describe the benefits of using SDN in a multitude of environments such as in data centers, data center networks, and Network as service offerings.

Monitoring and Improving Aircraft Maintenance Processes Using IT Systems

Aircraft maintenance is a complex, multifaceted process that greatly benefits from IT systems designed to improve supervision, record keeping, and task management. This study focuses on the role of a dedicated mobile application, integrated into the broader IT Aircraft Maintenance Support System, which supports maintenance operations for the M-346 BIELIK training aircraft. Aircraft maintenance is a highly intricate and multifaceted process that significantly benefits from advanced IT systems designed to enhance supervision, streamline record keeping, and optimize task management. This study explores the pivotal role of a dedicated mobile application integrated into the broader IT Aircraft Maintenance Support System, specifically tailored to support the maintenance operations of the M-346 BIELIK training aircraft. By focusing on the analysis of Intelligent Transportation Systems (ITSs), the research highlights how the application contributes to maintenance reliability and operational efficiency, with sustainability considerations in mind. The ITS-based approach assesses maintenance scheduling, tracking, and resource optimization, thereby enhancing the reliability of aircraft operations while reducing unnecessary resource consumption. This alignment with sustainable practices not only improves reliability characteristics and exploitation rates but also positively impacts the efficiency and effectiveness of aviation training. By accurately estimating the time requirements of specific maintenance tasks during periodic inspections, the application aids in identifying and addressing organizational bottlenecks, ultimately supporting both operational sustainability and improved task reliability across maintenance activities.

The Impact of Traditional Chinese Medicines on Osteoclastogenesis through NF-κB Signaling Pathway: A Review

Osteoclasts are specialized cells responsible for bone resorption, which plays a crucial role in the dynamic processes of bone remodeling and maintenance. Osteolytic skeletal disorders, such as osteoporosis, arise from an imbalance between the activities of osteoclasts and osteoblasts. The regulatory mechanisms underlying osteoclast differentiation, known as osteoclastogenesis, are governed by the receptor activator of nuclear factor kappa-B ligand (RANKL)/receptor activator of NF-κB (RANK)/osteoprotegerin (OPG) signaling system. In this system, the RANK, a type 1 transmembrane protein, acts as a central regulator of osteoclastogenesis through various signaling pathways. This review seeks to explore the influence of Traditional Chinese Medicines (TCM) on osteoclastogenesis, focusing on the NF-κB signaling pathway. This study aims to offer valuable insights into potential therapeutic strategies for managing osteolytic skeletal disorders by investigating the interaction between TCM and the regulatory mechanisms that control osteoclast function. A comprehensive literature review was conducted, concentrating on studies that examine the effects of TCM on osteoclastogenesis and the NF-κB signaling pathway. Databases such as PubMed, Web of Science, and Google Scholar were searched for peer-reviewed articles, reviews, and clinical studies. The inclusion criteria focused on studies addressing the impact of TCM on osteoclast function and the associated molecular mechanisms, especially those involving the RANKL/RANK/OPG system and the NF-κB pathway. The review identified several TCM compounds with regulatory effects on osteoclastogenesis. These compounds were found to modulate the NF-κB pathway, influencing osteoclast differentiation and activity. Key findings highlighted the discovery of specific TCM herbs and their active ingredients that can inhibit osteoclast formation and function, promoting bone health. The mechanisms of action often involved suppressing RANKL-induced NF-κB activation, a crucial process for osteoclast differentiation and bone resorption. This review underscores the potential of TCMs as therapeutic agents for osteolytic skeletal disorders through their modulation of the NF-κB signaling pathway. The findings suggest that TCM may significantly regulate osteoclastogenesis, offering new avenues for developing treatments for conditions like osteoporosis. However, further research and clinical trials are necessary to fully elucidate the therapeutic potential of TCM and translate these findings into clinical practice.

A Digital Twin Framework for Nuclear Power Equipment Maintenance: Design, Prototyping, and Preliminary Validation

Throughout the lifecycle of Nuclear Power Equipment (NPE), maintaining high-safety maintenance services is essential for optimal operation. Traditional time-based maintenance strategies are limited in NPE contexts due to stringent safety requirements and high costs of complex systems. Specifically, maintenance processes lack transparency, state monitoring relies heavily on manual inspections, and decisions depend passively on individual expertise. Digital Twin (DT) effectively breaks down "information silos," leverages data value, and enables proactive maintenance decision-making for NPE. However, DT application in the nuclear industry is still exploratory, with limited systematic and practical research, especially for critical equipment maintenance. This paper introduces a DT-based intelligent maintenance decision system featuring three key technologies: DT modeling, state monitoring with dynamic early warning, and systematic intelligent decision-making and verification. A DT-based prototype using a cooling water pump case study preliminarily validates the state monitoring model's accuracy. Results indicate that the proposed framework and methods are feasible and hold significant application potential.

Development of a highly sensitive method to detect translational infidelity

Abstract Protein homeostasis (proteostasis) is the balance of protein synthesis, protein maintenance and degradation. Loss of proteostasis contributes to the aging process and characterizes neurodegenerative diseases. It is well established that the processes of protein maintenance and degradation are declining with aging, however, the contribution of a declining quality of protein synthesis to the loss of proteostasis is less well understood. In fact, protein synthesis at the ribosome is an error-prone process and challenges the cell with misfolded proteins. Here we present the development of a highly sensitive and reproducible reporter assay for the detection of translational errors and the measurement of translational fidelity. Using Nano-luciferase, an enzyme three times smaller and 50 times more sensitive than the hitherto used Firefly-luciferase, we introduced stop-codon and amino-acid exchanges that inactivate the enzyme. Erroneous re-activation of luciferase activity indicates ribosomal inaccuracy and translational infidelity. This highly sensitive and reproducible method has broad applications for studying the molecular mechanisms underlying diseases associated with defective protein synthesis and can be used for drug screening to modulate translational fidelity.

Modeling of the processes of functioning of an organizational and technical system based on Markov random processes

Objective. In this paper, the main approaches to modeling the processes of functioning of the organizational and technical system, in particular the processes of maintenance and repair (MRO) of weapons, military and special equipment (VVST) by repair units of the operating organization (EO) using a mathematical model of Markov random processes, which will allow to evaluate the probabilistic characteristics of MRO processes of the VVST at carrying out activities of daily activities, which consist in carrying out work to restore the serviceability of the VST, as well as carrying out maintenance and operation of the OTS. Method. The modeling of processes is based on probabilistic models, in particular, the theory of random processes. Result. The use of a mathematical model of Markov random processes is justified. A graph of the states of the processes for maintenance and repair of VVST has been developed. A decision support system based on PTC Mathcad Prime has been implemented. The averaged generalized statistical information on the reliability of the VST was used as the initial modeling parameters in the work. Conclusion. The results obtained will make it possible to restore the serviceability and operability of the military-industrial complex both at the enterprises of the military-industrial complex and in the conditions of the operating organization without going beyond the time limits established in the regulatory and technical regulations. The considered approaches to modeling the processes of functioning of an organizational and technical system are a powerful tool for making informed and effective management decisions, they allow you to take into account many factors, conduct scenario analysis and optimize solutions, as well as use computers for more accurate and complex calculations.

System analysis and information processing to solve the problem of detecting breakdowns of computer information storage

Objective. One of the important aspects of maintaining the efficient operation of information systems is the condition of computer equipment. The purpose of the study is to describe a method for effective system analysis of the state of a computer's information storage device. Method. The study is based on the use of machine learning algorithms to analyze and interpret data obtained from SMART tests. Includes a comprehensive analysis and experimental study. It involves conducting experiments with a data set and the Google Colab cloud environment, creating and analyzing a machine learning model, and evaluating the effectiveness and quality of training. Result. A tool for assessing the state of computer equipment based on the Random Forest algorithm has been developed using historical data from SMART tests. Conclusion. The results not only allow the implementation of a working data analysis tool in the field of computer equipment maintenance, but also contain a practical example of increasing the reliability and efficiency of information systems. The results are useful for IT specialists and for organizations optimizing equipment maintenance processes and increasing competitiveness.

Designing Resilient and Autonomous Systems for Smart Infrastructure: Advancing Reliability, Efficiency, and Sustainability in Modern Networks

The design of resilient and autonomous systems for smart infrastructure represents a critical advancement in modern networked systems, addressing the growing need for reliability, efficiency, and sustainability in urban and industrial applications. This research investigates the integration of advanced technologies, including artificial intelligence (AI), machine learning (ML), and Internet of Things (IoT)-enabled devices, to develop robust systems capable of real-time monitoring, self-optimization, and fault-tolerant operations. By emphasizing decentralized architectures, adaptive system design, and intelligent data analytics, this study explores solutions for enhancing the performance and reliability of smart infrastructure in dynamic and complex environments. Additionally, the research considers the role of sustainability, examining how resilient systems can reduce resource consumption, optimize maintenance processes, and support long-term ecological goals. This work provides a comprehensive framework for the design and implementation of resilient and autonomous systems, addressing key challenges such as scalability, interoperability, and security. The findings offer transformative insights for various sectors, including transportation, urban planning, and industrial automation.

Performance metrics for the corrective building maintenance of hospital facilities

ABSTRACT Performance metrics (PMs) are essential in aiding hospital building maintenance managers in their decision-making processes. Although computerized maintenance management systems (CMMSs) are widely used in hospital maintenance and can store extensive data, there is limited literature documenting PMs derived from these sources. This study aimed to identify PMs in corrective building maintenance using a CMMS dataset from a Brazilian public hospital covering the years 2017–2022. A case study was conducted by analysing the evolution of work orders (WOs) over time and investigating lead times across hospital sectors and maintenance services. Textual analysis was used to explore the relationship between specific terms within WOs and lead times. The findings revealed (i) the impact of COVID-19 on WOs, (ii) a lack of evidence that requests were prioritized based on their origin and (iii) the relationship between specific keywords in user requests and faster responses. This study demonstrates that analysing past WOs can potentially enhance hospital corrective maintenance processes.

Optimal control of production and maintenance: A cost-efficient approach through inventory and preventive strategies

<p>Using an optimal control framework, the optimization of production and maintenance processes is investigated in this paper. We focused on analyzing system behavior, managing costs, and controlling quality. Differential equations are utilized to model the relationship between inventory level, production, and maintenance strategies. A cost function is built combining different cost elements, and the optimal production and maintenance rates were obtained. A sensitivity analysis is performed to assess the impact of different parameters on the total cost and on the optimal solution. The key findings demonstrated that higher initial inventory levels significantly decreased long-term costs and improved production efficiency. The optimal preventive maintenance strategy emphasized the importance of early investments in quality and maintenance, leading to sustained operational stability.</p>

Transnational learning and teaching activities: Smart Healthcare Engineering.

The new maintenance engineers become self-taught and learn from daily dedication, from solving repetitive problems, from exchanging experiences with a colleague, from reading a recommended book and little else. Their own experience has been the main reference for maintenance professionals who have not given up and have become experts. And within the maintenance activities, sanitary engineering plays a very important role. Through the Smart Healthcare Engineering project we have facilitated a close connection between 3 universities and 3 hospitals from 3 countries (Spain, Turkey and Romania), which benefit from each other's experience, transferring the know-how available in a single country. The study involves 7 students from each university, meaning that 21 students have worked and studied together for 2 weeks in Spain in the field of healthcare engineering. The chosen hospital was Dr. Negrin Hospital from Gran Canaria. Results at the organizational level include the modernization of content and the provision of resources for healthcare engineering training, the introduction of innovative educational concepts in healthcare engineering and the integration of blended learning methodologies in practical teaching and training activities. A tighter connection and transnational collaboration were established between European hospitals and universities in healthcare engineering, together with unrestricted access to routinely updated information. The specific results for each participant indicated their capacity to engage in the intricate processes of repair and maintenance within a practical context, making real-time judgments on-site.

A Fuzzy‐AHP Decision‐Making Framework for Optimizing Software Maintenance and Deployment in Information Security Systems

ABSTRACTInformation System Security (ISS) is the primary economic lever for the global economy. It is the cornerstone for value generation, and its absence undeniably affects technology, people, and finances. The emergence of the worldwide information society has introduced fresh economic and legal challenges attributed to the surge in Internet utilization and advancements in the digital economy. Ensuring the security of advancements within information systems has emerged as a primary concern in propelling the evolution of information processes within the software development industry. This study aims to develop and propose a Fuzzy Analytic Hierarchy Process (Fuzzy‐AHP) framework to enhance decision‐making for software maintenance and deployment in ISS. This framework aims to provide a systematic, flexible method for evaluating and prioritizing multiple conflicting criteria under conditions of uncertainty. The study initially adopts an empirical survey to identify software security maintenance and deployment risks and their practices for ISS organizations. Then adopts the Fuzzy‐AHP method to handle the imprecision of expert judgments and organizes decision‐making into a hierarchical structure. The framework is applied to evaluate key criteria related to software maintenance and deployment, including security risks, system performance, operational costs, and compliance requirements. Data from 50 ISS experts were collected and used to validate the framework. The paper identifies 52 security risks in maintenance and deployment (SRMD) processes in ISS and also identified 139 best practices for ensuring security, including regular updates, patch management, and adherence to industry‐standard security protocols. The Fuzzy‐AHP framework effectively structured the decision‐making process by prioritizing criteria and sub‐criteria. The results demonstrated that the framework helps mitigate the subjective biases in expert judgment and provides a more balanced assessment of maintenance and deployment strategies. Prioritizing security risks and compliance emerged as key factors in the decision‐making process. The proposed Fuzzy‐AHP framework provides an innovative and adaptable solution for optimizing ISS organizations' software maintenance and deployment decisions. It addresses the complexity and uncertainty involved in such decisions, offering a transparent and structured approach that improves the accuracy and reliability of outcomes. Future research should focus on empirical validation of the framework in real‐world case studies and expand its application to other industries with similar decision‐making needs.

Case Study: Operational Processes of sensors.AFRICA in Developing Low-Cost IoT Sensors Across Africa

sensors.AFRICA develops low-cost sensors for monitoring air quality, noise levels, and gases, designed and produced through a globally distributed process. This case study explores the design, manufacturing, deployment, and maintenance processes managed by a small team of hardware and software engineers spread across multiple cities in Africa. With manufacturing activities spanning four continents, the initiative delivers real-time environmental monitoring solutions, empowering communities with actionable insights. The study highlights the iterative design process, the challenges faced in operations, and the team’s approach to fostering innovation and resilience in a hybrid work environment.

Design and Use of AsLOV2-Based Optogenetic Tools for Actin Imaging.

We present protocols for using an optogenetic tool called LILAC for actin imaging. LILAC is a light-controlled version of Lifeact that uses the Avena sativa LOV2 (AsLOV2) domain. By significantly reducing Lifeact's affinity for the cytoskeleton in the dark, LILAC reduces concentration-dependent negative side effects while enabling new image processing methods. We discuss the considerations for using this probe of live-cell actin dynamics, including fluorescent protein selection, cell maintenance, microscopy protocols, and image processing. Our work highlights the potential of AsLOV2-based optogenetics for novel imaging and control tools in cell biology.

Between Decay and Maintenance: Tuberculosis Sanatoriums, Care Infrastructures and U.S. Health Policy Debates, 1945–1972

The development of streptomycin and isoniazid transformed the landscape of tuberculosis treatment in the United States in the mid-twentieth century. Sanatoriums continued to play a role in tuberculosis treatment in the early antibiotic era; yet, changing perceptions of tuberculosis as curable and a waning public health crisis sparked medical and legislative debates over their relevance and cost-effectiveness. By 1972, most specialized tuberculosis treatment facilities had closed. The sanatorium's legitimacy as an infrastructure supporting individual patient recovery and wider community health was negotiated in complex ways in 1950s and 1960s medical and public health literature. Examining changing imaginaries of sanatoriums as their relevance declined and their closure was debated enables a temporal analysis of how processes of maintenance and repair in infrastructure impact larger policy debates. The evolving role of sanatoriums figured prominently in national health policy debates because they were a multiscalar infrastructure that took shape through individual local sites and statewide (and nationwide) networks. By thinking infrastructurally about specific sites of care, this study contributes to a growing science and technology studies literature about opportunities for repair in care infrastructures as enabling more adaptable, equity-focused responses to enduring public health challenges, particularly as societies respond to limitations in biomedicine.

INSPECTIFY: MOBILE APPLICATION FOR SUPPORTING AIRPORT FACILITY TERMINAL INSPECTION SERVICE

Operational activities at the airport are highly dependent on the efficiency and reliability of facilities, and formal reporting evidence is needed to improve the quality of facilities inspections at the Terminal Inspection Service (TIS) unit, as well as to serve as monitoring evidence that will be used as a basis for facility improvement evaluations. This study aims to design and develop the Inspectify application. The research methodology used is the Research and Development (R&D) method with the Borg and Gall research model. The study results show that the Inspectify application can facilitate the reporting process of facility damages and maintenance while improving the response to issues occurring since this application has features to track the status of repairs and receive real-time notifications. This application supported TIS personnel in conducting inspections more effectively and efficiently. Implementing this application is expected to contribute positively to airport operations, improve the efficiency of TIS personnel’s work, become the TIS data center, and increase overall passenger satisfaction.

Exploring modern methods for predicting well failures in the fields of NC «KazMunayGas» JSC

In the development of brownfields, various geological and technological complications can arise. To enhance the smooth operation of downhole pumping equipment, companies implement a range of methods and techniques. This article analyzes the potential of using machine learning to improve the reliability of underground well equipment in the fields of NC KazMunayGas JSC. The research focuses on the development and validation of predictive models that accurately forecast potential downhole equipment failures. It thoroughly analyzes existing machine learning methods, approaches and their real-life application, highlighting key success factors and limitations. The results of the study demonstrate the significant potential for using a well failure prediction model when selecting the optimal machine learning approach to reduce unscheduled downtime and optimize well maintenance processes. The authors assessed the potential for using failure prediction techniques for downhole pumping equipment in wells that utilizes sucker rod pumps. Implementing failure prediction techniques for downhole pumping equipment can help ensure uninterrupted well operation by minimizing well failures and reducing downtime for repairs.

Prospects for PARG inhibitors in cancer therapy.

Poly(ADP-ribose) glycosylhydrolase (PARG) is an enzyme involved in hydrolyzing the ribose-ribose bonds present in poly(ADP-ribose) (PAR), which are primarily found in the nucleus. Along with poly(ADP-ribose) polymerase (PARP), PARG regulates the level of PAR in cells, playing a crucial role in DNA maintenance and repair processes. Recent studies have revealed elevated levels of PARG in various cancers, such as breast, liver, prostate, and esophageal cancers, indicating a link to unfavorable cancer outcomes. PARG is a significant molecular target for treating PAR-related cancers. This review provides a comprehensive overview of the physiological role of PARG and the development of its inhibitors, highlighting its potential as an innovative target for cancer treatment.

Maintenance in aviation enabled by Industry 4.0 technologies: exploring the current research trends using a topic modeling approach

PurposeSince passenger safety is critical, aviation maintenance is essential. Aviation maintenance management is changing due to Industry 4.0 (I4.0). According to earlier research, I4.0 technologies improve aircraft manufacturing efficiency and responsiveness through automation, predictive maintenance and process self-optimization. Thus, this study examines I4.0 research and aircraft maintenance's potential interaction.Design/methodology/approachUsing a text-mining methodology, this paper looks at the state of the art in aviation maintenance research in the I4.0 era. We used the topic modeling approach and Latent Dirichlet Allocation (LDA) technique to analyze the abstracts and indexed keywords of 929 research articles on the intersection of aviation maintenance and I4.0, subsequently clustering them into eight topics.FindingsWe have mapped out the emerging research trends at the intersection of “aviation maintenance” and “I4.0 technologies”, and presented suggestions for theoretical frameworks, applied frameworks and future lines of inquiry. This paper makes a theoretical contribution to the systematization of literature on I4.0 technologies in aviation maintenance. It provides valuable insight for managers by exploring the implications and opportunities that arise in light of recent innovations brought by I4.0 in aviation maintenance.Originality/valueThis study focuses on the use of Industry 4.0 technologies in aircraft maintenance processes, contributing to the growing research on digital technology in maintenance and maintenance, repair and overhaul (MRO). Furthermore, the study's analysis of the LDA topic model provides valuable insights for future research on using I4.0 technologies to investigate specific areas of application in the context of digital maintenance.