Maintenance Management System Research Articles

Enhancing maintenance efficiency in energy assets through AI: a case study of maintAI

Energy assets demand periodic regular maintenance to ensure safe, reliable and efficient operations. The dynamic nature of operating conditions and evolving best practices necessitate frequent optimisation of maintenance programs. Traditionally, these programs were labour-intensive and costly to deploy, often yielding unclear outcomes due to subjective decision-making. The advent of artificial intelligence (AI) presents an opportunity to challenge traditional approaches. This paper presents a case study where asset knowledge, data, and AI capabilities are leveraged to streamline maintenance optimisation using our ‘maintAI’ approach. The program addresses maintenance strategy, backlog, spares, and predictive maintenance optimisation with a focus on value creation, data-driven decisions, and consistent recommendations. A systematic methodology employs AI to sift through and eliminate non-value-adding tasks, enabling prioritisation of work and enhancing reliability and productivity throughout the production facility lifecycle. AI, including Natural Language Processing and Generative AI algorithms, enhances the speed and accuracy of failure mode classification from operational maintenance data. Reliability modelling techniques provide insights into equipment reliability. Recommendations undergo expert review before integration into a Computerised Maintenance Management System. Implementation of this data-driven approach demonstrates rapid deployment and sustained efficiency, yielding substantial gains in production uptime, cost reduction, and safety. The user-centric design ensures agility and ease of configuration. A recent project, which took only 6 weeks to deliver, led to a ~28% reduction in maintenance backlog, freeing capacity for critical focus areas. The maintAI approach proves a meaningful change for energy producers, offering a new solution in maintenance optimisation for enhanced reliability and productivity.

A Comprehensive Review on the Global Aviation Industry and Aircraft Maintenance Management Processes

The vision of the Turkish Republic is to surpass the level of contemporary civilization, and one of the main principles to achieve this is "The future is in the skies." To make this a reality, it is imperative to establish a national and domestic aviation industry. The first step towards this goal is to ensure the safe operation of aircraft, which requires a maintenance management system. To create and use the necessary maintenance documents, an international standard management process should be followed for airframe manufacturers and component and part manufacturers in the aviation industry. Airline operators should then create their maintenance documentation according to this system and work with airplane maintenance organizations to ensure the airworthiness of their aircraft. This study discusses and evaluates the documents used within the essential management and organization principles framework, primarily focusing on the aircraft maintenance management system.

Development and Usability Evaluation of VulcanH, a CMMS Prototype for Preventive and Predictive Maintenance of Mobile Mining Equipment

This paper details the design, development, and evaluation of VulcanH, a computerized maintenance management system (CMMS) specialized in preventive maintenance (PM) and predictive maintenance (PdM) management for underground mobile mining equipment. Further, it aims to expand knowledge on trust in automation (TiA) for PdM as well as contribute to the literature on explainability requirements of a PdM-capable artificial intelligence (AI). This study adopted an empirical approach through the execution of user tests with nine maintenance experts from five East-Canadian mines and implemented the User Experience Questionnaire Plus (UEQ+) and the Reliance Intentions Scale (RIS) to evaluate usability and TiA, respectively. It was found that the usability and efficiency of VulcanH were satisfactory for expert users and encouraged the gradual transition from PM to PdM practices. Quantitative and qualitative results documented participants’ willingness to rely on PdM predictions as long as suitable explanations are provided. Graphical explanations covering the full spectrum of the derived data were preferred. Due to the prototypical nature of VulcanH, certain relevant aspects of maintenance planning were not considered. Researchers are encouraged to include these notions in the evaluation of future CMMS proposals. This paper suggests a harmonious integration of both preventive and predictive maintenance practices in the mining industry. It may also guide future research in PdM to select an analytical algorithm capable of supplying adequate and causal justifications for informed decision making. This study fulfills an identified need to adopt a user-centered approach in the development of CMMSs in the mining industry. Hence, both researchers and industry stakeholders may benefit from the findings.

Creation of a Computerized Maintenance Management System (CMMS) with Features and Planning Requirements

Creation of a Computerized Maintenance Management System (CMMS) with Features and Planning Requirements

An ontology-driven model for hospital equipment maintenance management: a case study

Purpose This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.Design/methodology/approach The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.Findings Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.Originality/value An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.

Research on Fault Prediction and Health Management System of Power Electronic Devices Based on Computer Deep Learning Algorithm

This paper proposes a power equipment maintenance management system based on network and deep learning algorithm. First of all, the actual power network equipment maintenance and maintenance management of the power company, so as to clarify the tasks to be completed by the system. ASPNET technology is used to realize the management of business form data and various transaction processes of each system, and the related technology of process engine is applied to the maintenance of each equipment. A load forecasting method of power system based on SVR is proposed. It makes the operation and maintenance work of this system more intelligent. Each function module of the whole system is designed in detail. The system basically meets the needs of power equipment maintenance and repair management.

CMMS- Streamlining Maintenance management for Food and Beverage Industry to capture breakdowns

CMMS stands for Computerized Maintenance Management System. In today’s world, when technology is advancing each day at an astonishing rate, any organization must have a detailed knowledge and understanding of its current state of machinery, the number of resources spent on the production floor to maintain equipment reliability, and resource allocation. CMMS is a critical and powerful tool that assists and helps any manufacturing industry to make full use of its capabilities, manage or direct workforce, improve the machine reliability, find innovative ways to improve productivity, stay in compliance with food and dietary regulatory standards as per the safe quality foods (SQF) and national sanitation foundation (NSF) standards and achieve series of goal and benefits the organization overall. Today, the food and beverage industry has grown tremendously and is the backbone of the manufacturing industry. Every company looks at creative ways to help them excel by selecting a reliable CMMS that suits their operations and processes to make educated decisions by monitoring their KPIs. This theoretical study aims to provide a building framework to set up plant maintenance modules to manage work orders, including emergency breakdowns and scheduled maintenance repairs in the food and beverage industry.

Integrating Parabolic Trough Solar Fields Into Computerized Maintenance Management Systems

Computerized maintenance management systems for power plants are not well suited for application in solar fields. They work well for tracking maintenance requirements on the hundreds or even thousands of pieces of equipment in conventional power plants, but they do not work as well tracking the maintenance requirements on hundreds of thousands of identical pieces of equipment found in a solar field. A database application, known as a field status program, is being developed for tracking the maintenance and status of collectors and components in parabolic trough solar fields as a complement to the computerized maintenance management system. This system, patterned after a similar system developed by the KJC Operating Company in the 1990s, provides a valuable tool for the O&M of parabolic trough solar fields. This paper describes the development and application of the tool and the new expanded capabilities that are being added to further enhance the O&M of solar fields.

Unlocking maintenance insights in industrial text through semantic search

Maintenance records in Computerized Maintenance Management Systems (CMMS) contain valuable human knowledge on maintenance activities. These records primarily consist of noisy and unstructured texts written by maintenance experts. The technical nature of the text, combined with a concise writing style and frequent use of abbreviations, makes it difficult to be processed through classical Natural Language Processing (NLP) pipelines. Due to these complexities, this text must be normalized before feeding to classical machine learning models. Developing these custom normalization pipelines requires manual labor and domain expertise and is a time-consuming process that demands constant updates. This leads to the under-utilization of this valuable source of information to generate insights to help with maintenance decision support. This study proposes a Technical Language Processing (TLP) pipeline for semantic search in industrial text using BERT (Bidirectional Encoder Representations), a transformer-based Large Language Model (LLM). The proposed pipeline can automatically process complex unstructured industrial text and does not require custom preprocessing. To adapt the BERT model for the target domain, three unsupervised domain fine-tuning techniques are compared to identify the best strategy for leveraging available tacit knowledge in industrial text. The proposed approach is validated on two industrial maintenance records from the mining and aviation domains. Semantic search results are analyzed from a quantitative and qualitative perspective. Analysis shows that TSDAE, a state-of-the-art unsupervised domain fine-tuning technique, can efficiently identify intricate patterns in the industrial text regardless of associated complexities. BERT model fine-tuned with TSDAE on industrial text achieved a precision of 0.94 and 0.97 for mining excavators and aviation maintenance records, respectively.

EFFICIENCY OF CMMS (COMPUTERIZED MAINTENANCE MANAGEMENT SYSTEM) PROJECT STAGES WITH K-MEANS

This study scrutinized four CMMS (Computerized Maintenance Management System) development projects using the K-Means clustering method to evaluate stages that require improvement by the GrX team. The projects under consideration were named Tim, Lix, Akb, and Mnk. The results indicated that the Tim project leaned more towards efficient CMMS development stages, while the Lix and Akb projects were predominantly in less efficient clusters at the implementation stages. The Mnk project had stages in less efficient clusters located at stages other than implementation processes. This suggests that each project has its unique challenges in achieving efficiency. However, the overarching conclusion is that the GRX team needs to enhance efficiency in the CMMS software development process. Several stages need to be evaluated, particularly the “data analysis and coordination” and “implementation of asset, work order, preventive and spare part modules” stages. Inefficiency occurs when the designing work time has a value lower than twice the workload. The K-Means algorithm was employed in the clustering process because it was believed that the data to be grouped was well-suited for implementation with this algorithm. The variables involved in this study were time and workload. This research provides valuable insights into the efficiency of CMMS development projects and offers a roadmap for future improvements.

Reliability Improvement in the Traction System of Tanzania Standard Gauge Railway

In recent years, many African governments have been developing Standard Gauge Railway (SGR) to replace the old after becoming absolute, inefficient Meter Gauge System (MGR) to carry more loads at high mileage and speed while combating the oil and environmental crises. With the increase of SGR, the amount of traction systems has grown sharply, the service life of the traction system has increased gradually, and the components of the vehicle traction system have become worn and aged as a result. While Tanzania is transitioning to SGR with its gradually increasing traction systems, reliability improvement becomes a key for the sustainability of its high-speed train services. This paper, therefore, aims to improve the reliability of traction motors used in Tanzania’s SGR. Firstly, the factors affecting the reliability of the traction system of Tanzania’s SGR and their significance are evaluated. Secondly, the computerized maintenance management system (CMMS) is designed to streamline and automate the maintenance management processes of the traction system of Tanzania’s SGR. Finally, a regression model is established to forecast the uptime based on the established factors. The obtained uptime hours were predicted in order to compute the reliability of the traction motor and its criticality in operation. Critical factors for improving reliability have also been highlighted. These findings play vital roles in establishing the fundamentals of factors that affect reliability as well as strategies and countermeasures to extend the operational life of the traction motors cost-effectively.

Manajemen Perkandangan dan Biosekuriti Peternakan Radja kambing di Desa Langea, Kecamatan Ranomeeto, Kabupaten Konawe Selatan

Radja Kambing was a farm located in Langgea Village, Ranomeeto District of South Konawe Regency which maintained the Etawa crossbreed goat. The problems experienced by partner group of breeders/ aspiring farm entrepreneur of goat was cage managemen and also application of biosecuryt system that was not up to standard, so the step that needed to be taken was to transferred the technological innovation to breeder group partners. This community service programe was aimed to brought tha changes andimprovements to the maintenance of management system in generally and cage management also biosecurity system application the Radja Kambing in particularly. The method that used were non physical activity method which includes counseling, training and technical guidance as a transferred information media, knowledge and teknologi, also physical activity method for example procurement of materials and tools, demonstrantion of making compost from goat feces. Theprograme results shown that there was a increase in breeders knowledge about good livestock management and biosecurity as well as an increase in knowledge about processing goat fecess become compostKey word: biosecurity, feces, cage, goat, compost

The Importance of Spare Strategy in a Research Facility

This document shows the importance of spare part strategy in a research facility at one of the most important medical schools in the world. It presents technical concepts related to equipment criticality analysis and spare part management integrated with computerized maintenance management systems (CMMS). A case study utilizing VFDs on campus will be produced to reveals gaps, benefits, and opportunities to improve the current spare part management system. Challenges in the spare part process will also be addressed in this document, such as storage and external vendor support.

Decision Analysis to Find Best Solution of Operation and Maintenance Management System in Central Processing Plant (CPP) Gundih Using The SMART Method at PT. Pertamina EP

Central Processing Plant (CPP) Gundih is a gas field owned by PT. Pertamina EP Cepu Field area which is located in Blora Regency, Central Java. The gas produced by the CPP Gundih is channelled to the Tambak Lorok Gas and Steam Power Plant (PLTGU) with a capacity of 1,469MW in the Semarang City area, Central Java. Therefore, the CPP Gundih is a vital national object that supports national energy security, especially for the Central Java area. CPP Gundih first operated in 2013 with the operation and maintenance management system being fully handled by a third party with a contract term of one decade. In the coming year, the contract system will approach the end of the collaboration so that PT. Pertamina EP needs more efficient management schemes and strategies and more agile business processes. In the past decade, there have been several evaluations that have become a concern for companies in implementing contract systems with third parties. These obstacles mean that several aspects are not managed well and result in problems that reduce the level of customer satisfaction, decrease profits, and increase operational and maintenance costs. So that PT. Pertamina EP is considering several options for better management of the CPP Gundih in the future, namely the option of detailing third party contracts in the future, the option of transferring management by PT. Pertamina EP partially, full management transfer option by PT. Pertamina EP without any third-party involvement. From several proposed options, the author will use the Simple Multi Attribute Rating Technique (SMART) method to select the best option by considering aspects of Cost, Durability and Plant Availability, Manpower Competency Management, Remuneration, Communication Flow, and Integrated Work Procedure. The research results obtained from this method will become a reference for the PT management team. Pertamina EP for decision making related to the operation and maintenance implementation system at the Central Processing Plant (CPP) Gundih gas field.

Application of a decision support system for monitoring and maintenance management of water valley tank facilities: A technological transformation toward sector sustainability

The conventional approach of monitoring and maintaining water valley tank facilities (WVTFs) by field visiting is allied to time and resource wastage and data inaccuracies due to human error. These shortcomings hinder the sustainable monitoring and maintenance management of WVTFs. Therefore, this study investigates the development of a user-friendly decision support system (DSS) for supporting the monitoring and maintenance management activities of WVTFs in Nakasongola, Uganda. An open-source cloud-based “Google AppSheet” was interlinked with “Google Sheets” to develop the “MWEMA” mobile application (App), built with four modules (i.e., PM plan and schedule, work order, functional status, and mapping). Additionally, the MWEMA-app was implemented in the case study area to monitor the operational status of WVTFs. A total of 41 WVTFs were monitored, and acquired data was plotted instantly on the map. Results showed that out of 41 WVTFs, 4 were functional, 27 were partially functional, 8 were non-functional, and 2 were pending construction. An economic estimation demonstrated that the implementation of the project initiative is profitable with benefit/cost ratio (B/C) and net-present worth (NPW) values of 2 and US$ 39,809, respectively. Implementing the proposed innovative DSS would support achieving society-, economy-, and environment-related targets of sustainable development goals (SDGs) for the United Nations 2030 Agenda. The technology would assist policymakers and technical managers in keeping track of the operational status of WVTFs for sustainable management and development of scarce water resources.

Maintenance system for vehicles of the Military Police of Paraná – PMPR

The general objective of this article was to analyze the current maintenance system for Paraná Military Police vehicles and its effectiveness, results and possible improvements. This is a literature review based on the qualitative analysis of the material found in the literature review and, therefore, it was a descriptive and exploratory research developed based on material already prepared, consisting mainly of scientific articles and related legislation researched in the Scielo, Google Scholar and thesis bank search engines using the descriptors maintenance management, military police, vehicle maintenance and Prime system. The results showed that vehicles are made up of parts whose useful life is directly related to the care that the user takes with their maintenance and for this to occur, periodic inspections recommended by car manufacturers are necessary, as well as preventive and corrective maintenance of the vehicles. It was noticed that there is a complex system involving the maintenance system managed by the Company Prime Benefícios and therefore some corrections are necessary to adapt it to the company that wins the competition to manage the maintenance system for the State's vehicle fleet.

Development of a methodology for asset integrity management in Universities and Research Centers

This article describes the application of a differentiated methodology that I developed to enhance and facilitate asset management work in renowned universities and research centers. Frequently, important scientific studies and research are interrupted or wasted due to unexpected failures in equipment and infrastructure systems provided by universities and research centers for researchers’ use. To address this issue, this methodology incorporates structured concepts and practices commonly employed in the field of asset integrity. These are uniquely integrated into comprehensive engineering assessment reports developed over several years during my fieldwork in various countries. This integration occurs within a computerized maintenance management system. The ultimate goal of this process is to maximize the reliability and performance of critical systems and equipment used in the infrastructure and conduct of highly relevant research at the national and international levels. Through case studies conducted at two major universities in the United States, the efficiency of this innovative methodology was analyzed quantitatively and qualitatively. As presented in this article, the main results obtained include a reduction in the number of unplanned repairs or shutdowns, improved quality and efficiency of maintenance programs, increased reliability and lifespan of critical research equipment and systems, an increase in the number of assets with an appropriate maintenance plan, and the enhancement of computerized maintenance management systems used by these institutions. These results translate into faster completion of scientific studies and research with more reliable data.

Current Overview of CMMS Operationality: Brazilian Scenario

Currently, the impacts of Industry 4.0 are observed in the construction industry, commonly referred to as Construction 4.0, emerging linked to technological innovations. Construction 4.0 presents a standardized model for smart cities and buildings, with the existence of some important points being essential, such as the capacity for adaptation, improvement and efficiency of resources and connections for everyone involved. As a result, new technologies and applications have been emerging that directly impact building maintenance activities, enabling increased efficiency and productivity in this sector, which reduces the risk of errors, failures and defects by maintenance managers. One of these applications is the use of computerized maintenance management systems (CMMS), which is a software solution designed to simplify building maintenance processes, in addition to improving the management of organizations' assets. In this sense, the present work aims to evaluate the CMMS available in the Brazilian scenario, showing the current panorama in which this technology has been presented to the market. To this end, we carried out a survey of the CMMS used by Brazilian maintenance companies using the snowball method to list the CMMS to be analyzed. The research carried out in 16 maintenance companies identified 9 CMMS, which were evaluated using the method proposed by Roscoff; Costella; Pilz (2020), which evaluates CMMS functionalities and activities. As a result, the sample analyzed presents heterogeneity in the results linked to CMMS functionalities and activities. In short, the registration items, a basic function, were met by all CMMS analyzed. However, advanced functions that are linked to the principles of Industry 4.0, such as interoperability, virtualization, real-time and service orientation, present disparities in results. Because among the nine CMMS evaluated, only three reached the levels proposed in the methodology.

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.

Multiple aspects maintenance ontology-based intelligent maintenance optimization framework for safety-critical systems

Abstract Maintenance optimization is a process for improving the efficiency of maintenance strategies and activities, considering various aspects of the target system and components, such as the probabilities of system failures and the cost of repair and replacement of a failed component. The improvement of maintenance optimization algorithms generally requires information from various data sources. For example, it may require the system risk information derived from risk analysis tools or the residual lifetime of a component from fault prognosis tools. The requirements of data acquisition (DAQ) and aggregation pose new challenges for maintenance management systems (MMSs) that implement and use these maintenance optimization algorithms. This paper proposes a multiple aspects maintenance ontology-based framework to facilitate DAQ from MMSs, online monitoring systems, fault detection and discrimination tools, risk assessment tools, decision-making tools, and component identification tools, and accelerate the implementation and verification of contemporary maintenance optimization models and algorithms. The proposed framework consists of a multi-aspect maintenance ontology with critical information for maintenance optimization and application interfaces for collecting information from various data sources, such as fault prognosis tools, online monitoring tools, risk assessment tools, and decision-making algorithms. In addition, this paper proposes a heuristic method for integrating concepts and properties from other existing ontologies into the proposed framework when the existing ontology is not fully compatible with the ontology under construction. Finally, the paper verifies the proposed ontology framework using a feedwater system designed for nuclear power plants with valves and filters as the components under maintenance.