Maintenance Management Framework Research Articles

A decision-making framework for optimal maintenance management: An integrated simulation-mathematical programming-expert system approach

In this study, an integrated simulation- mathematical programming- expert system approach is proposed to develop an optimal solution for maintenance management in a complex public infrastructure system. As the first step, a model of maintenance system is made through a computerized simulation with respect to the collected data on maintenance programs and unexpected failures. Then, the Taguchi method is adopted to develop different scenarios for each of which a precise measurement of cost and reliability based on customer dissatisfaction rate (i.e. modified reliability) is made. Regression method is applied to observe the association of components’ maintenance workload with cost and modified- reliability. After that, the best solution for maintenance management is achieved by developing a mathematical model, with the aim of reliability improvement and cost savings. Finally, after identifying the most significant components in terms of cost and modified- reliability by sensitive analysis, the maintenance actions taken during the program are determined using an expert system. Results demonstrated that the optimization model Outdo Taguchi scenarios achieved the optimum one as it met both targets simultaneously. Having determined the significant components of the system and enhanced the methodology by signaling maintenance specialists to devote additional attention to them, it can be especially helpful in assisting administrators in lowering the accident rate arising from the shortcomings in maintenance plans.

Faktor Pengelolaan Operasi dan Pemeliharaan Irigasi Di Kabupaten Tanah Datar

In recent years, the Tanah Datar district government has focused more on the physical implementation of irrigation area development and has not prioritized the budget for operating and maintenance costs so that there are still many Irrigation Areas (DI) whose irrigation infrastructure is not functioning properly with a high level of network damage that requires high costs. In addition, low awareness of the provision of operational and maintenance (OP) funds, limited human resources for OP staff, and the participation of groups of farmers using water (P3A) or a combination of groups of farmers using water (GP3A) is also not optimal. In order to function optimally and can be used for a long time, the irrigation that has been built needs to be maintained and managed systemically and to develop an optimal operating and maintenance management framework. The purpose of this study was to identify the dominant factors and factors that influence the operation and maintenance of irrigation networks in Tanah Datar District, as well as to optimize the operation and maintenance of the network. This study used a quantitative method by distributing questionnaires to respondents. The results of the research conducted revealed that there were 2 factors that influenced the operation and maintenance of irrigation networks in Tanah Datar Regency, namely the condition of physical infrastructure and supporting facilities and P3A Personnel Organization and Institutions..

Digital twins in condition-based maintenance apps: A case study for train axle bearings

Digital Twins (DTs) are gaining popularity in the context of the fourth industrial revolution to replicate physical equipment and systems in the digital world. DTs promise increased productivity and sustainable performance by integrating data, models, and decision-support systems. However, before realizing the potential benefits of DTs for maintenance management, several challenges need to be addressed, including a lack of conceptual basis, functional description, and established requirements. Hence, the paper presents, in a practical manner, how to cover this gap in digital configurations for maintenance management, designed to benefit of DTs. The scope of the paper includes the design and implementation of an innovative condition-based maintenance application (CBM App) based on a DT of train axle bearings, and uses a generic framework for digital maintenance management for the functional description of the DT within the CBM App. The paper provides details of the models and algorithms used to build the DT and ensures that recommended features are fulfilled. To test the DT's effectiveness and robustness, the design and framework are implemented in real CBM applications of TALGO, a high-speed train manufacturer. These tools are deemed helpful for easing DT implementation within the CBM App and can be replicated in other operational contexts.

Blockchain Enabled Maintenance Management Framework for Military Equipment

Maintenance of military equipment plays a vital role in achieving higher war readiness. The vast number of military equipment and their deployment on distinct locations make their maintenance a challenging task. Decision-makers are always interested in knowing the latest status of equipment, develop effective maintenance strategies, and predict mission reliability as accurately as possible. To suffice this need, maintenance data of military equipment must be maintained with high granularity and accuracy, including maintenance information about every lowest maintainable unit of every military equipment. There is a profound need for a comprehensive maintenance management framework, which addresses several military-specific issues with equipment maintenance and stores the maintenance data in the utmost secure environment. In this article, we attempt to provide a novel blockchain enabled framework to make military maintenance management comprehensive and future ready. This article first provides a representation of the maintenance scenario of military equipment and later discusses the several choices made available within the blockchain technology, along with the architecture of the proposed blockchain. The proposed framework uses smart contracts to make monitoring and validation more uncompromising and with minimum human intervention. Some pragmatic analytics are presented in this article, along with the inherent blockchain advantages.

Data-driven optimization of repair schemes and inspection intervals for highway bridges

Routine bridge inspections enable timely maintenance plans based on potential risks. These inspections are performed at fixed time intervals, which may be unnecessarily short for bridges in excellent conditions and precariously long for those in poor conditions. Also, deterioration models used in current bridge management approaches fail to include the effect of age, causing inaccurate predictions. This paper develops a hazard-based bridge management approach where inspection frequencies and repair suggestions are optimized based on hazard levels. A two-dimensional Markov model describes the age-dependent bridge deterioration, and a semi-Markov decision process optimizes inspection intervals and repair decisions. The objective is to minimize the expected long-term total annual costs, including expenses associated with maintenance and traffic detours. The modeling process and maintenance management framework was demonstrated on an example bridge superstructure in New York. The results showed lower annual and total costs than the conventional management method. As expected, sensitivity analyses indicated that the pre-specified choices of inspection intervals for low and high hazard levels have a significant effect on the calculated hazard threshold levels. The proposed maintenance management method is adaptable and practical; bridge authorities can identify appropriate repair actions and make inspection decisions based on simple threshold comparisons.

An Information Granulated Based SVM Approach for Anomaly Detection of Main Transformers in Nuclear Power Plants

The main transformer is critical equipment for economically generating electricity in nuclear power plants (NPPs). Dissolved gas analysis (DGA) is an effective means of monitoring the transformer condition, and its parameters can reflect the transformer operating condition. This study introduces a framework for main transformer predictive-based maintenance management. A condition prediction method based on the online support vector machine (SVM) regression model is proposed, with the input data being preprocessed using the information granulation method, and the parameters of the model are optimized using the particle swarm optimization (PSO) algorithm. Using DGA data from the NPP data acquisition system, two experiments are designed to verify the trend tracing and prediction envelope ability of main transformers installed in NPPs with different operating ages of the proposed model. Finally, how to use this framework to benefit the maintenance plan of the main transformer is summarized.

Modeling a maintenance management framework for asset management based on ISO 55000 series guidelines

PurposeMaintenance management is perceived as fundamental for ensuring that physical assets contribute to business outcomes. In this context, the purpose of this paper is to elaborate a novel maintenance management framework for asset management (MMFAM) based on ISO 55000 series guidelines.Design/methodology/approachThe paper proposes an MMFAM that intends to translate the technical requirements set out in the ISO 550001 standard to the maintenance stage of asset management. First, the framework is modeled using consideration based on the analysis of the ISO 55000 series and the review of previous maintenance management frameworks. Then, support tools are presented that collaborate for the implementation of the processes and activities provided for in the MMFAM.FindingsThe proposed MMFAM was modeled using a Business Process Model and Notation since it is a standardized graphical notation for process modeling and contributes to the understanding of the framework. In addition, the applicable tools were presented for the practical implementation of MMFAM processes and activities.Practical implicationsThe paper is expected to contribute to maintenance practitioners and researchers in understanding and disseminating a novel maintenance management framework that is in line with asset management through the international ISO 55000 series.Originality/valueAs it is essentially multidisciplinary and complex, asset management has still been little explored. Moreover, the requirements for implementing an asset management system, as explained in the ISO 55001 standard, only provide what needs to be done, but not how to do it. Accordingly, the paper fills a gap in maintenance management literature, as it addresses the ISO 55000 series for asset management in depth.

Pavement maintenance management framework for flexible roads: a case study of Pakistan.

Roads play a pivotal role in the overall economic growth of any country. Developed countries allocated sufficient budget to make new roads and to maintain the existing roads. They also have a proper pavement management system (PMS) in practice to manage roads, whereas developing countries suffer from budgetary issues to make new roads and maintain the existing road network. Therefore, this paper explores the awareness of PMS via direct and indirect methods in Pakistan with a proposed framework of the low-cost model and pavement maintenance indicators for developing countries. This paper also performs a scientometric assessment of PMS. A detailed literature review has been carried out for this study, followed by a quantitative study from experienced professionals. The scientometric data is collected from the Scopus database from 1975 to 2020, whereas the data for PMS awareness assessment has been collected using questionnaires from different experts working directly and indirectly in the road management sector. The data has been analyzed using the arithmetic mean because of the nature of the questions and scope of the study. The direct method results show that experts are aware of PMS for a new road, but they have no PMS to rehabilitate roads. The indirect method results show that the authorities are applying various components of PMS, but there is no proper PMS in practice. This paper helps decision-makers to make better decisions and policies for improved road maintenance and rehabilitation. The proposed framework in the study can significantly assist the UN-SDG 9 (Facilitate Sustainable Infrastructure in Developing Countries) and 11 (Affordable and Sustainable Transport System).

Integrating resource-based view and performance improvement theory in developing maintenance management continuous improvement model: A conceptual framework

The local authority in Malaysia is the giant holder of public assets and they are obligated in performing better management to ensure the assets are of prominent quality to serve the needs of the local people. The local authority should take initiatives in having the right systems in managing and maintaining their assets. Therefore, the purpose of this study is to explore the maintenance management practices and performance improvement techniques to be integrated into developing the continuous improvement model towards achieving a sustainable performance of public assets. The resource-based view (RBV) and performance improvement (PI) theory are integrated as the reference to develop the maintenance management framework. The RBV emphasizing the resources and capabilities to achieve the value of strategic management. While the PI provides a suitable tool which is the maturity model for improving the current practices. Nine key elements of maintenance management were identified which demonstrating the maintenance capabilities and resources. Grounded on the theory of RBV and PI, the conceptual framework was established as the foundation towards developing strategic maintenance practices for sustainable performance of public assets and continuous improvement in maintenance management by the local authority in Malaysia.

Investigation on the Mathematical Relation Model of Structural Reliability and Structural Robustness

Structural reliability and structural robustness, from different research fields, are usually employed for the evaluative analysis of building and civil engineering structures. Structural reliability has been widely used for structural analysis and optimization design, while structural robustness is still in rapid development. Several dimensionless evaluation indexes have been defined for structural robustness so far, such as the structural reliability-based redundancy index. However, these different evaluation indexes are usually based on subjective definitions, and they are also difficult to put into engineering practice. The mathematical relational model between structural reliability and structural robustness has not been established yet. This paper is a quantitative study, focusing on the mathematical relation between structural reliability and structural robustness so as to further develop the theory of structural robustness. A strain energy evaluation index for structural robustness is introduced firstly by considering the energy principle. The mathematical relation model of structural reliability and structural robustness is then derived followed by a further comparative study on sensitivity, structural damage, and random variation factor. A cantilever beam and a truss beam are also presented as two case studies. In this study, a parabolic curve mathematical model between structural reliability and structural robustness is established. A significant variation trend for their sensitivities is also observed. The complex interaction mechanism of the joint effect of structural damage and random variation factor is also reflected. With consideration of the variation trend of the structural reliability index that is affected by different degrees of structural damage (mild impairment, moderate impairment, and severe impairment), a three-stage framework for structural life-cycle maintenance management is also proposed. This study can help us gain a better understanding of structural robustness and structural reliability. Some practical references are also provided for the better decision-making of maintenance and management departments.

Preliminary Study on the Maintenance Level of Waqf Properties: Federal Territory, Kuala Lumpur

There has been a growing interest in the development of income-generating Waqf (endowments) properties in recent times. This is quite justifiable considering the fact that Waqf properties estimated to worth up to USD 1 Trillion globally have failed to generate adequate income to meet up the maintenance costs thus resulting in poor maintenance and the inability of these properties to meet Waqf objectives. Consequently, this paper presents preliminary findings on an on-going research aimed at developing a maintenance management framework for income-generating Waqf properties. Data were gathered through content analysis and secondary sources. Findings in this paper indicate that the inadequate maintenance of Waqf properties is partly due to relatively low rents and high rental arrears. The paper also gathered that despite the unique features of Waqf, there is no specific study aimed at developing a user-driven maintenance management framework for income-generating Waqf properties. Such omission could slow down the much-anticipated progress particularly at this point in time when different funding initiatives have resulted in the construction of high-rise income-generating properties on Waqf lands. The paper also provided current information on the state of income-generating Waqf properties in Kuala Lumpur.

Sustainability of maintenance management practices in hydropower plant: A conceptual framework

The study aims to promote sustainable of Hydropower plant by building conceptual framework and sharing knowledge. The aim is to assess the impact of maintenance management practices on economic, social and environmental performances to achieve the sustainability by proposing maintenance management conceptual framework. In this paper, literature and expert opinion based conceptual maintenance management framework for sustainable hydropower plant is proposed and certain key variables/aspects have been considered, such as Maintenance Management Policy, Production Loss, Digitalization, Record Keeping, Machine health Condition, Maintenance Workforce, Maintenance Decision Making, Smart Information and communication system, Operational Performance, workers health and Safety, cyber security, water management and environmental impact. It’s a known factor that Composite materials are making inroads in construction of turbine blades for hydroelectric power industry. Therefore this paper besides discussing other variables also investigates into composite material application in hydro power turbine development as main variable in maintenance Management policy.

A BIM-based PSS Approach for the Management of Maintenance Operations of Building Equipment

The service-centered economy has grown considerably in the last few years, shifting from product-based solutions towards service centered offerings, i.e., Product-Service System (PSS) solutions. Such an approach is also emerging in the context of building equipment, where maintenance activities play a fundamental role in facility management. In this field, Building Information Modeling (BIM) based tools are diffusely used to improve the performances of facility management. However, few studies have addressed the above issues while considering a shift from product-based approaches in favor of more advanced servitization models. The study aims at integrating BIM based approaches in a PSS context for the improvement of the management of maintenance operations of building equipment. A general framework for maintenance management has been developed, merging the implementation of the PSS components in a BIM model for the definition of maintenance management. A first application of this methodology to a real case study concerning the elevators of an existing building has shown the efficacy of the proposed approach. The study highlighted the benefits that can be achieved, especially in terms of reduced periods of equipment unavailability, reduced costs and augmented customer satisfaction, while enhancing the information exchange between the PSS actors. Hence, although further research is still needed for its validation, the proposed approach can offer practical insights for the development of promising BIM-based PSS solutions for facility management in the construction industry.

Railroad infrastructure 4.0: Development and application of an automatic ballast support condition assessment system

Abstract Industry 4.0, or the fourth industrial revolution, is the current trend of automation and data exchange in manufacturing technologies. Even though Industry 4.0 emerged as a manufacturing initiative, the idea of bridging digital and physical systems can be expanded beyond the manufacturing industry. “Railroad Infrastructure 4.0” is thus proposed in this study to revolutionize the maintenance operations of the railroad industry. In North America, most primary freight and passenger rail corridors are constructed using ballasted track. One of the primary maintenance activities is to ensure the ballast is performing adequately. Being able to monitor the ballast condition and conduct tamping operations (e.g. maintenance activities) at optimal intervals can increase the safety and efficiency of railroad operations. Previously, techniques such as ground penetrating radar (GPR) and Matrix Based Tactile Surface Sensors (MBTSS) have been used to assess the condition of ballast, but these investigative tools lack the capability of automatically and continuously monitoring the track system. Researchers at the University of Illinois at Urbana-Champaign and the University of South Carolina have developed a non-intrusive method as a key component of Railroad Infrastructure 4.0 to continuously quantify ballast pressure distribution (i.e. ballast condition) under the sleeper (also known as a “crosstie”). This method innovatively uses the bending moment profile across the concrete sleeper, and the approximated rail seat loads as inputs, to back-calculate the ballast support condition through the use of an optimization algorithm. The ballast support condition assessment system that was developed has been validated for accuracy from extensive laboratory experimentation. The laboratory validated system was deployed in the field on a Class I heavy axle load (HAL) freight railroad in the United States to continuously monitor the ballast pressure distribution beneath concrete sleepers in real-time under revenue service operating conditions. The evaluation of ballast pressure distributions between adjacent sleepers as well as tonnage accumulated are also included. To better quantify the variation of ballast pressure beneath the sleepers, the Ballast Pressure Index (BPI) is also proposed. The information presented in this paper demonstrates the concept and potential of Railroad Infrastructure 4.0 as a future framework for railroad maintenance planning and management.

Analysis of SCADA data for early fault detection, with application to the maintenance management of wind turbines

Wind turbines are, generally, placed at remote locations and are subject to harsh environmental conditions throughout their lifetimes. Consequently, major failures in wind turbines are expensive to repair and cause losses of revenue due to long down times. Asset management using optimal maintenance strategies can aid in improving the reliability and the availability of wind turbines, thereby making them more competitive. Various mathematical optimization models for maintenance scheduling have been developed for application with wind turbines. Typically, these models provide either an age based or a condition based preventive maintenance schedule. This paper proposes a wind turbine maintenance management framework which utilizes operation and maintenance data from different sources to combine the benefits of age based and condition based maintenance scheduling. A mathematical model called Preventive Maintenance Scheduling Problem with Interval Costs (PMSPIC) is presented with modification for the maintenance optimization considering both age based and condition based failure rate models. The application of the maintenance management framework is demonstrated with case studies which illustrate the advantage of the proposed approach.

A DECISION-MAKING FRAMEWORK FOR EFFECTIVE MAINTENANCE MANAGEMENT USING LIFE CYCLE COSTING (LCC) IN A ROLLING STOCK ENVIRONMENT

In this paper, a life cycle costing (LCC) framework for effective maintenance management is investigated and developed for use in a railway rolling stock environment. The framework consists of combining typical mission-critical components together with their failure and maintenance history. All costs related to the operation and maintenance of these components throughout their life cycle are also determined. The next step involves considering different scenarios under which the components can be used in relation to operations, maintenance, and replacements. The decision about which scenario to take is based on the one with the most favourable net present value after life cycle costing is performed over a specified period of time. A typical railway rolling-stock maintenance organisation in South Africa was used to highlight the practical implications of such a framework and how the company could make informed and appropriate decisions. The conclusion of this study is that such a framework is useful, and that it can be used as a basis for estimating LCC across a spectrum of critical assets found in the rolling stock environment.

Framework for maintenance management of shield tunnel using structural performance and life cycle cost as indicators

In the past decades, many shield tunnels have been constructed for use in important lifeline infrastructure such as roads, railways, water supply systems and sewers. A good performance of the tunnel requires appropriate maintenance associated with a substantial cost; therefore, a rational maintenance approach is required. Preventive maintenance has been previously applied in an efficient and effective manner. However, the evaluation of structural performance, as well as the choosing an appropriate maintenance management strategy, is still a challenge. This paper proposes a maintenance framework for the shield tunnel. Structural performance and life cycle cost are evaluated as the major indicators accounting for the major deterioration (e.g. steel corrosion, cracking, etc.). The structural performance-based strength cost for an expected service time is used as the criterion to select a rational maintenance plan. Furthermore, structural reliability analysis is performed to validate the proposed framework and investigate the influence of deterioration model. The proposed framework was successfully applied to the maintenance of a trunk sewerage pipe for choosing a rational maintenance plan.

A framework for maintenance and combat readiness management of a jet fighter aircraft

The study is focused on the application of maintainability analysis in a jet fighter aircraft in order to point out weaknesses of maintenance operations. Descriptive statistics of the repair data were carried out and both maintainability and repair rate modes for the entire aircraft were calculated. Maintainability for different time periods for aircraft’s principal subsystems has been estimated on the basis of fitted distribution models. Quality function deployment (QFD) method was applied to link customer requirements and maintenance characteristics in military squadron, revealing the relationship among the prevailing factors affecting maintenance operations. The QFD is proposed as a quality planning methodology to reduce aircraft repair time increasing at the same time squadron’s combat readiness. The highest maintainabilities were associated with the engine, the communication/navigation and the fuel subsystems, whereas the airplane general, the flight control and the structure subsystems bottomed out in maintainability performance. Furthermore, top management involvement, resources availability, maintenance procedures, maintenance planning as well as technical experience were the main factors responsible for the current maintainability level of this aircraft. The paper is based on practical actions being undertaken in an Airforce and therefore, is demonstrated to be practical in an aviation environment. This study may be used for long‐term, strategic assessment and planning decisions in order to sustain unit availability and overall air force combat readiness at a high level.

Maintenance Management:A Study of Reliability-CenteredMaintenance for Irrigation System

<abstract> <b><i>Abstract. </i></b> Irrigation systems constantly experience new developments, and decision makers are always concerned with their efficient management. Routine maintenance must be performed to ensure that the system fulfills the functions for which it was designed. Irrigation systems include many subsystems and to ensure proper functioning, a maintenance plan should be followed. System failures can have negative consequences for irrigated crops. This study demonstrates the implementation of RCM (reliability-centered maintenance) in an irrigation system for a real-world case. By implementing RCM in an irrigation system, it is possible to plan maintenance activities and make guided decisions within a structured plan. An efficient maintenance management framework for irrigation systems is the only way both to ensure the continued availability of the irrigation systems and to extend their useful life span. To these ends, the RCM methodology has achieved positive results in several areas of this study. The results indicated that the RCM methodology implemented for irrigation systems brought about greater accuracy in the maintenance decisions and activities applied to these systems, where the decision-maker of the irrigation system can define, based on the demand of a specific crop, the most appropriate maintenance actions for each consequence of failure. The use of this methodology highlights that effective maintenance management has to be aligned with the specificities of a crop and the functions and features of the system. In cases that do not use a standard maintenance policy, money and time is wasted, when non-effective maintenance is carried out unnecessarily, in addition to which total loss of a crop could result from not undertaking necessary maintenance activities.

An Artificial Neural Network Approach for Early Fault Detection of Gearbox Bearings

Gearbox has proven to be a major contributor toward downtime in wind turbines. The majority of failures in the gearbox originate from the gearbox bearings. An early indication of possible wear and tear in the gearbox bearings may be used for effective predictive maintenance, thereby reducing the overall cost of maintenance. This paper introduces a self-evolving maintenance scheduler framework for maintenance management of wind turbines. Furthermore, an artificial neural network (ANN)-based condition monitoring approach using data from supervisory control and data acquisition system is proposed. The ANN-based condition monitoring approach is applied to gearbox bearings with real data from onshore wind turbines, rated 2 MW, and located in the south of Sweden. The results demonstrate that the proposed ANN-based condition monitoring approach is capable of indicating severe damage in the components being monitored in advance.