Equipment Maintenance System Research Articles

Design and Development of a Pipeline Maintenance System for Pipe Surge and Water Hammer Equipment Based on Siemens S7-1200 PLC

Fluids play a crucial role in the lives of living beings, as they are substances that can flow. In a piping system, a common issue is water pressure fluctuation caused by sudden closures of water flow (Idul, 2021). Pipe surge and water hammer equipment are utilized to demonstrate the transient pressure effect resulting from abrupt changes in flow velocity within pipes (David, 1981). Water hammer can lead to pressure surges throughout the piping system, potentially causing failures that result in leaks in pipes, valves, pipe joints, and even pumps if the pressure exceeds the pipe's capacity (Prasetya, 2016). The likelihood of pipe ruptures or leaks at joints increases significantly. Additionally, equipment movement, slope, and precision of pipe installation can also contribute to leaks during water hammer events. This research aims to develop a pipe leakage monitoring system to address the impact of water hammer. The system will be installed in areas deemed susceptible to this phenomenon, along with a periodic maintenance indicator system to minimize the impact of pipe leaks. The research will also investigate the potential risks associated with varying fluid flow rates in the piping system. The monitoring, indicator, and sensor systems will be integrated into a PLC and HMI system for data processing.

Construction and Innovation of Management Mode of Laboratory in Regional and Local Universities

University laboratory is an important base for training students' innovative practice ability and teachers' scientific and technological innovation, and is an important part of university. Traditional laboratory management methods have been unable to adapt to modern practical teaching and scientific and technological innovation. Based on the comprehensive analysis of laboratory management in local colleges and universities and the actual situation of existing laboratories, a comprehensive laboratory management system was developed, which consisted of six functional modules: large-scale equipment sharing platform, instrument and equipment maintenance system, experimental consumables management system, laboratory and practice teaching integrated service platform and laboratory safety management and service platform. The system fully integrates and displays the laboratory teaching resources, realizes the open self-management mode, provides the convenience of experimental teaching, and effectively improves the efficiency and management level of the laboratory.

Research and Design of Industrial Equipment Maintenance Management System Based on the Internet of Things

With the continuous increase of industrial production scale, traditional industrial equipment management methods are no longer applicable to current industrial production. In this context, the application of industrial equipment management systems is in line with the current development trend of the industry. This article starts from the perspective of system design and implementation, and designs an industrial equipment maintenance and management system from the aspects of system architecture, system functional modules, etc. for practical application needs. By combining IoT technology with industrial equipment, real-time monitoring, intelligent diagnosis, predictive maintenance, and remote control functions are achieved, thereby achieving equipment health management.

ANALYSIS OF CORRECTIVE MAINTENANCE MONITOR CCA TOOL DVOR SELEX TYPE-1150A

In the aviation industry, navigation has a crucial role in supporting the smooth running of flight routes to maintain the safety and security of air transportation. Perum LPPNPI Pekanbaru branch provides communication, Navigation, Surveillance, and Data Processing facilities to ensure flight safety, regularity, and comfort. One of the navigation facilities available at Perum LPPNPI Pekanbaru branch is the Doppler VHF-Omnidirectional Range (DVOR), an air navigation system control tool that can guide aircraft to land precisely at the destination airport by providing information in the form of azimuth or artificial bearing. This research aimed to analyze the care and maintenance system for DVOR equipment, and identify several potential problems that have arisen during the operation of DVOR equipment at Perum LPPNPI Pekanbaru branch. In this research, evaluations and observations were carried out to assess the level of DVOR maintenance in accordance with Advisory Circular CASR Part 171-12. This research focused on evaluating Corrective Maintenance Monitor (CMM) analysis on DVOR Selex Type-1150A equipment at Perum LPPNPI Pekanbaru Branch. DVOR is a critical air navigation system that requires effective corrective maintenance. The method used in the research is procedural analysis of equipment maintenance as in research conducted by Widasari Mutiara, this research also focused on CMM evaluation, identification of potential problems, and performance analysis to improve maintenance efficiency. Research adopted a qualitative research method with a descriptive approach, because the data collected is textual in nature. This research method involved CMM system inspection, equipment maintenance analysis, and interviews with engineering personnel. The research results provide insights for improving corrective maintenance procedures, and increasing the availability and reliability of the DVOR system. The implications of these findings support safe and reliable flight operations at Perum LPPNPI Pekanbaru Branch.

Predictive maintenance system for high-end equipment in nuclear power plant under limited degradation knowledge

To ensure the safe operation of high-end equipment, the three-stage maintenance strategy comprising unplanned shutdown, temporary shutdown, and scheduled shutdown is currently employed in nuclear power plants. However, this strategy hinders the acquisition of degradation knowledge (run-to-failure data or degradation mechanism), thereby impeding the application of traditional predictive maintenance systems. Hence, the responsibility for determining the maintenance stage primarily lies with experienced field engineers, and an incorrect decision could potentially result in an unplanned shutdown. To this challenge, we integrate the three-stage maintenance strategy and prognosis methods to form a predictive maintenance system for nuclear power plants. The system framework is first established, and prognosis methods, including sensor selection, degradation trend prediction for short-term prognosis, and remaining useful life (RUL) prediction for long-term prognosis, are then developed under limited degradation knowledge. Finally, the system is deployed in the circulating water pump of a nuclear power plant utilizing an Internet of Things (IoT) architecture. An industry case study verifies that the proposed system can provide decision-making support and further achieve predictive maintenance for high-end equipment in nuclear power plants.

Research on Large Language Model for Coal Mine Equipment Maintenance Based on Multi-Source Text

The efficient management and utilization of coal mine equipment maintenance knowledge is an indispensable foundation for advancing the establishment of intelligent mines. This knowledge has problems such as scattered, low sharing, and insufficient management, which restricts the development of coal mine intelligence. For the above-mentioned problems, a large language model for the maintenance of coal mine equipment based on multi-source text (XCoalChat) was proposed to better manage and utilize the existing massive knowledge of coal mine equipment maintenance. The dataset of coal mine equipment maintenance based on ReliableCEMK-Self-Instruction was constructed to obtain a wide and diverse amount of knowledge through sample generation. Aiming at the illusory problem of the large language model, a knowledge graph enhancement method based on the “Coal Mine Equipment Maintenance System—Full Life Cycle—Specification” was proposed to improve the knowledge density. A triple-LoRA fine-tuning mechanism and DPO direct preference optimization method were introduced into the top of the baseline model, which guarantees that XCoalChat can handle multiple Q&A and maintenance decision analysis tasks with limited computing power. Compared with ChatGLM, Bloom, and LLama, the comprehensive assessment of XCoalChat was performed by experiments including coal mine dialog consulting, coal mine professional consulting, and maintenance decision analysis. The results showed that XCoalChat achieved the best response accuracy in professional consulting and maintenance decision analysis; XCoalChat also took the least reasoning time on average. XCoalChat outperformed other mainstream large language models, which verify that XCoalChat is an effective large language model in the field of coal mine equipment maintenance.

Analiza i ocena systemu obsługiwania sprzętu technicznego w Wojsku Polskim

Utrzymanie wysokiego poziomu gotowości operacyjnej wojska wymaga zapewnienia stałej wysokiej gotowości technicznej sprzętu stanowiącego jego wyposażenie. Niezawodność urządzenia technicznego wynika z jego cech konstrukcyjnych i eksploatacyjnych, a w fazie eksploatacji jest zależna wyłącznie od sprawności działania systemu zaopatrzenia logistycznego, obsługiwania, w tym diagnozowania. Zasady realizacji tych procesów i funkcjonowania systemów determinuje przyjęta strategia eksploatacji sprzętu. W opracowaniu przedstawiono wyniki oceny funkcjonowania systemu obsługiwania sprzętu technicznego w wojsku polskim. Scharakteryzowano metody, procedury i narzędzia pozyskiwania danych dla realizacji postawionego celu, metody przetwarzania i opracowania danych oraz analizy uzyskanej informacji. Informacje i dane charakteryzujące funkcjonowanie systemu obsługiwania uzyskano w wyniku zastosowania techniki wywiadu z ekspertami dysponującymi wiedzą teoretyczną jak i praktyczną o funkcjonowaniu systemu w siłach zbrojnych, za pomocą techniki obserwacji, analizy dokumentacji eksploatacyjnej w formie papierowej, jak również zgromadzonej w systemach informatycznych. Podstawowe znaczenie w procesie badawczym miała metoda ankietowania dwóch grup ekspertów, uczestników kursu logistycznego związanych z realizacją i zarządzających eksploatacją sprzętu. Do opracowania uzyskanych wyników liczbowych i lingwistycznych wykorzystano narzędzia informatyczne w postaci MS Excel, MatLab i Statistica. W opracowaniu wyznaczono parametry statystyki opisowej, histogramy i rozkłady prawdopodobieństwa oraz wykorzystano logikę rozmytą. W wyniku przeprowadzonego badania ujawniono przyczyny aktualnie nie w pełni zadowalającego poziomu funkcjonowania systemu utrzymania stanu technicznego sprzętu oraz wskazano możliwe do zastosowania rozwiązania pozwalające na podniesienie sprawności i efektywności systemu, a tym samym gotowości technicznej sprzętu.

Main Switch Board Plan Maintenance System on MV. Kirana III

The Plan Maintenance System (PMS) is a continuous and scheduled maintenance system for equipment and supplies on a ship. Its purpose is to ensure that the ship is always in a seaworthy condition and ready to operate. In order to achieve smooth operation of the ship, it is essential to have a good, efficient, and effective work and maintenance system for the ship's electricity and systems. One way to do this is by formulating and implementing maintenance system plans by shipping companies in Indonesia. During research carried out on the KM Ship, KIRANA, it was found that there was a lack of maintenance on the Main Switch Board, leading to problems with the indicator lights and needles. Infrequent maintenance was also ignored, leading to undesirable events due to inadequate implementation of the planned maintenance system. To avoid damage or short circuits, it is important to schedule and regularly check the components of the switch board weekly and monthly. This will help maintain the components and minimize malfunctions on the switch board, with the help of scheduling in the Plan Maintenance System.

Maintenance architecture design of equipment operation and maintenance system based on digital twins

The digital twins process of equipment operation and maintenance involves massive data and complex business logic. Through data awareness of equipment and workshop environment. According to the characteristics of equipment operation and maintenance, the data characteristics and requirements are analysed, an equipment operation and maintenance management system based on the micro-service framework is proposed, a set of equipment operation and maintenance digital twins are designed and a general reference software architecture is designed and by checking the underlying in-heap pattern reduces high-impact portions of memory to provide accurate follow-up complex digital twins modelling provides the architectural foundation.

Research on Key Technologies of Remote Operation and Maintenance System for Substation Automation Equipment

Abstract With the help of automation technology, the efficiency and reliability of substation operations are synchronized. However, the equipment will operate under abnormal problems for a long time. If the problem is not resolved promptly, the consequences will be unimaginable. For timely detection of problems, this paper proposes a method for the construction of remote operation and maintenance systems. The remote operation and maintenance system is mainly composed of two-factor authentication, responsibility area authentication, and permission authentication. The security of remote operations and maintenance operations is guaranteed with the support of these key technologies. This paper enhances the safety and stability of automation equipment by offering remote wake-up, remote reset, historical information retrieval, and forwarding table monitoring services in the operation and maintenance service module. Adopting IoT technology, the core management module of remote management of master stations is constructed to ensure the safety of remote operations and maintenance data interaction between master stations and sub-stations. Simulation experiments are being conducted to evaluate the performance of IoT technology in remote operations and maintenance interactions at the main station. The energy consumption of the data interaction module of substation automation equipment is 0.19 and 0.012 mA for 1 hour and 1 day, respectively, for the equipment to operate for 5-10 days, where the advantages of IoT technology are reflected. The processing time of the operation and maintenance personnel under the traditional operation and maintenance and remote operation and maintenance modes were analyzed through comparative experiments, and the processing time of the device dead time was reduced from 175.46 minutes to 4.356 minutes after using the remote operation and maintenance system, and the efficiency of the operation and maintenance personnel was improved.

Application of big data technology in electromechanical operation and maintenance intelligent platform

Abstract Aiming at the data preprocessing requirements and label data cost issues arising from the intelligent operation and maintenance of electromechanical equipment, this article mainly studies structured data cleaning methods and fault prediction algorithms for a small number of label samples. First, this article introduces the overall architecture of the intelligent operation and maintenance system for electromechanical equipment. Second, based on the electromechanical equipment operation and maintenance data access service, data cleaning, and fault prediction, this article constructs an electromechanical equipment intelligent operation and maintenance platform based on Kafka message queue, Spark cluster, and other components, and introduces the functional composition of the system in detail. Finally, the article describes the functions of each component of data access service, data cleaning, and fault prediction in detail. To address the cost issue associated with sufficient labeled sample data for data analysis, we propose a semi-supervised learning algorithm, IF-GBDT, based on improved independent forests and Gradient Boosting Decision Tree. The independent forest algorithm supplements labels for unlabeled data based on the learning results of a small number of labeled samples. We also use the gradient lifting tree algorithm to train the model based on the new tag data set for fault prediction, thereby reducing the impact of lack of tags on the accuracy of the prediction model. Experiments show that this method improves classification accuracy and has good adaptability and concurrency performance for a small number of tags.

Concept for the formation of technical service of agricultural machinery in Western Siberia

The service concept for agricultural machinery can only be viable if priority is given to the use of machines in agricultural work. The main contradiction in the maintenance and machine usage system is the overlapping timing: the higher the operating time, the more maintenance work needs to be done. The specifics of determining maintenance load are that current issues and trends in machine maintenance need to be taken into account. They consist in the fact that the technical and financial basis for the formation of an effective specialised service system is now virtually non-existent on the one hand, and the virtual absence of a service consumer because of the insufficient profitability of agricultural enterprises on the other. For the time being, therefore, machinery will have to be repaired and maintained mainly by the farms themselves by replacing worn units and parts with new or second-hand ones in the workshops of the farms. How to make this work more effectively? In the research, the use of agricultural machinery has been considered. Proposed and substantiated the concept of technical service formation at the enterprises of agroindustrial complex of Western Siberia. The main advantages of the proposed agricultural equipment maintenance system concept are discussed.

Analysis of approaches to assessing the actual condition, residual life and reliability of hydraulic turbines

In order to increase the resource and reliability of power equipment, reduce downtime and repair costs, modern methods of monitoring and resource diagnostics are used to build an equipment maintenance system based on the actual technical condition of the equipment. The main content of the work performed with different prevention strategies is considered. The current situation with the wear of the main power equipment in the country and the results of research indicate the need to create and develop more advanced methods for assessing the resource of power equipment both in hydropower and in the energy sector as a whole.

Tensile and fatigue behaviors of hybrid laser welded A7N01 alloy with repairing for railway vehicles

As one of the key concerns in the health maintenance system for modern railway equipment, defect repair plays an important role in enhancing the running safety reliability and economic benefits. In this study, welding defects of A7N01 alloy commonly used in high-speed trains were repaired by hybrid laser welding. The surface integrity of the welded zone before and after repairing was evaluated by various characterization methods in terms of the microstructures, tensile and fatigue properties. The results show that the original incomplete penetration defects would be eliminated by welding repair, giving rise to some microstructural changes such as the grain refinement and the widening of fine grain zone in the original welded joints. The heat input during welding repairing induced significantly reduction of the hardness and tensile strength from 105 HV to 75 HV and from 358 MPa to 338 MPa, respectively. Nevertheless, the fatigue properties of hybrid welded A7N01 alloy with the hybrid welding repairing were improved by 33.8%, probably because of reduced defects.

Competence-Based Assessment of Biomedical Equipment Management and Maintenance System (e-Upkaran) Using Benefit Evaluation Framework.

Introduction To establish a centralized inventory management system for the efficient functioning of all healthcare facilities, e-Upkaran (equipment management and maintenance system) was launched in 2015 in the state of Rajasthan. This study is conducted to assess the functioning of e-Upkaran in Rajasthan. Methods The assessment of the e-Upkaran system for primary and secondary healthcare centers was carried out using a systematic review of the literature and a multi-indicator stakeholderquestionnaire. The benefits evaluation framework focused on the system quality, information and service quality, use and user satisfaction, and net benefits utilized for the assessment. A review of the literature was done to highlight the importance of computerized medical equipment management and maintenance systems and appraise the challenges and benefits associated with such systems as compared to the traditional pen-paper register. Information was gathered based on available documents, field observation, and data obtained from specific hospital staff, including the bioengineers and other users of e-Upkaran. Results The finding of this study suggests that e-Upkaran efficiently improves documentation, reporting, maintenance, and management of medical equipment.It is more efficient than the traditional paper-pen system. It is designed to minimize downtime and maintain equipment in good operating condition and has potential benefits in terms of improving information quality, use, and net benefit. The cost of service ratio is within the benchmark value. This system has also considerably reduced out-of-pocket expenditure. Computer proficiency and the workload of other e-health programs pose a challenge in the implementation of this program. Conclusion The e-Upkaran system is competent in terms of improving information quality, use, and net benefit. Other Indian states could also adopt this system to improve their biomedical equipment management and maintenance system.

Development and Assessment of Augmented Reality Technology for Using in an Equipment Maintenance and Diagnostic System

This study presented work considering the development and initial assessment of an augmented reality approach to provide a user interface for operators that could be a part of an equipment maintenance and diagnostics system. Its purpose was to provide an equipment system for graduate students of engineering and technology to experiment with the design of augmented reality technology. The proposed system took place three hours per week over a period of four weeks of corrective actions that were triggered in the Department of Industrial Education and Technology at the National Changhua University of Education, Taiwan. The students adopted augmented reality technology to achieve big data acquisition and analysis for pre-diagnostic and maintenance applications. Preliminary assessment of the proposed system was encouraging and showed that it achieved success in helping students understand concepts and using augmented reality technology for equipment maintenance and diagnostics. The study provided important initial insights into its impact on student learning.

Research on Design Method of Intelligent Operation and Maintenance System for Secondary Equipment in Intelligent Substation

Abstract Smart substations are an important part of establishing a strong smart grid. In view of the large variety of secondary equipment in the current power system, the rapid increase in quantity, and the complex working conditions of the current power supply company maintenance classes to inspect substations, a design method for the intelligent operation and maintenance system of secondary equipment in smart substations is proposed in this article. First, the intelligent operation and maintenance system architecture of the secondary equipment of the smart substation is established via Redis and ActiveMQ technologies. Then the system function module model is established. Finally, taking a 220kV substation in a certain area of southern China as an example, a new type of intelligent substation secondary equipment intelligent operation and maintenance system was installed and connected to the main line system, and the effectiveness of the proposed method was verified.

Integrated Prescriptive Maintenance System (PREMSYS) for Construction Equipment Based on Productivity

It is now imperative to create smart systems that prevent mechanical damage through timely preventive maintenance, particularly in construction projects with strict time schedules and budgets. Construction equipment is the largest capital investment for construction companies. Proper maintenance is of major importance for efficiency, productivity, minimization of equipment costs, and environmental management. The aim of this study is to propose an integrated smart system that will monitor the condition based on productivity of the equipment and will provide diagnostic data, helping to optimize the production process, achieve timely maintenance and increasing the expected “economic” life of the equipment. At the same time, it will positively provide the concept for sustainable or green construction with the minimization and elimination of harmful effects on the environment and on the human. The system will include sensors, placed on specific construction equipment components, and will collect measurements for their use and condition, through real-time data export. These data will then be sent using wireless networks to a main server. Extraction of performance measurements and machine learning (ML) data processing will determine when the equipment needs predictive maintenance and repair. Proper, timely and prescriptive maintenance of construction equipment will reduce their environmental footprint and any human harmful emissions, while saving energy during their operating phase and optimizing production processes through monitoring “dead” time.

Fault identification using a structural and functional approach for digitalization conditions

One of the fundamental components in equipment maintenance and repair systems that implement modern risk-oriented strategies is information. The effectiveness of taken decisions is determined not only by the volume, but also by the quality of information data. The article formulates and justifies the requirements for the collected information on the technical condition of equipment and data for the analysis of its failures, taking into account modern capabilities and conditions of universal digitalization. The role of mathematical modeling in the formation of data on the functional parameters of the machine is shown, the main stages of construction are outlined and a set of developed mathematical models of the refrigerator is presented. Methods of equipment fault analysis are considered, their characteristics are given, areas and application features are indicated. An algorithm for analyzing events related to the operability of equipment based on entries in the equipment maintenance log is described. The proposed approaches are demonstrated by the example of a refrigerator with walking beams and a hydraulic drive, which is an integral part of the technological line of the CCM and has the most characteristic features of metallurgical equipment, which allows to use the solution of the problem of collecting and processing information about the technical condition of the CCM refrigerator as a standard.

Solution of a mining equipment maintenance system model in imprecise environment

Solution of a mining equipment maintenance system model in imprecise environment