Maintenance Priority Research Articles

СИСТЕМАТИЗАЦИЯ СОВРЕМЕННОГО МЯСОРЕЗАТЕЛЬНОГО ОБОРУДОВАНИЯ И ОЦЕНКА НЕИСПРАВНОСТЕЙ ПРОМЫШЛЕННЫХ ВОЛЧКОВ

Based on the analysis of the designs of modern meat cutting equipment used by processing plants, their great diversity has been established, justified by the design and technological requirements for this type of machines. (Objective of the study) To establish the features characterizing industrial grinders, compile their classification, determine the main faults and the degree of their influence on the operability of industrial grinders. (Materials and methods) Design and technological requirements for industrial grinders have been determined. An analysis has been carried out and the main causes of malfunctions of industrial grinders have been identified. Structural parameters characterizing the technical condition of industrial grinders have been established. A priori ranking technique has been selected based on an expert assessment by specialists of the main faults of industrial grinder units. (Results and discussion) The features characterizing industrial grinders have been established, based on this, their classification has been compiled. A structural diagram of the "Industrial grinder" technical system is presented. The main faults and the degree of their influence on the loss of operability of the devices under consideration during operation have been determined. The entire set of industrial grinding machine malfunctions is grouped relative to three subsystems: cutting, feeding and driving. During the malfunction analysis, 10 most important of them were identified, affecting the grinder operability and its technological process performance. (Conclusions) The entire set of presented industrial grinding machine malfunctions was ranked by weight. A 10-point system was used for their assessment and points were assigned in accordance with complexity within the range from 1 to 10. The first group included malfunctions with ranks higher than 238 (malfunctions with a higher probability of occurrence). The second group included malfunctions with a rank value lower than 150 (malfunctions with a lower probability of occurrence). It was found that the maximum weight has malfunctions designated as n6, n10, n9. They characterize the technical condition of the cutting and feeding subsystems. Priority for maintenance and control should be given to these subsystems

Implementation of Risk Management in Asset Management Governance Towards Optimizing Asset Utilization at Public Service Agency State Universities (Case Study of UPN Veteran Yogyakarta)

This study aims to analyze the application of risk management in asset governance at UPN Veteran Yogyakarta to achieve optimal asset utilization. As a Public Service Agency State University (PTN-BLU), UPN Veteran Yogyakarta faces various challenges in asset management, including budget constraints, lack of consistent monitoring, and the unavailability of formal risk evaluation standards. Qualitative descriptive research methods are used to gain in-depth understanding through interviews with asset managers and field observations. The results show that the implementation of risk management can have a significant impact on the efficiency of budget allocation, which includes more appropriate budget distribution based on priority needs and risks. Risk management also has the potential to extend the useful life of assets, with risk mitigation measures taken on assets that show signs of wear or early damage, thus preventing major repair costs due to serious damage. This research highlights that a technology-based monitoring system is an indispensable aspect to support the effectiveness of risk management in asset management. The implementation of structured risk assessment procedures helps in determining asset maintenance priorities, so that the assets that are most critical to the sustainability of campus operations receive greater attention. With the implementation of this comprehensive risk management, optimization of asset utilization can be achieved, which in turn supports the stability and sustainability of UPN Veteran Yogyakarta's operations as a quality higher education institution.

Small data-based maintenance planning for a Tainter gate using component and system reliability

This paper presents a method using small data to enhance maintenance efficiency, addressing the limitations of solely qualitative maintenance records. It involves the use of a model based on the Bayesian–Weibull first-order reliability method (BW-FORM) for component analysis and a stochastic analytic hierarchy process for system-level assessment, including fault-tree analysis and reliability-centered maintenance for prioritizing tasks. Key components such as “gate body” and “wire rope” significantly affect system reliability, whereas “rusted crane base” and “bolt on base falling” are the top maintenance priorities. The Mudan Reservoir case study validates this approach, with the life expectation estimated using the BW-FORM aligning well with expert predictions.

Performability analysis for the SPVC line system of leaf spring production plant using probabilistic approach

PurposeThis work ensures the higher performability of this complex system, which consists of five different subsystems, i.e. shearing machine, V-cutting machine, center hole punch, edge cutting burr and drilling machine. These subsystems are placed in combinations of both series and parallel arrangement. The concerned plant management must be aware of the failures that have the greatest/least impact on the system’s performance.Design/methodology/approachPerformability analysis has been done for the Shearing, Punch and V- Cutting (SPVC) line system by using a probabilistic approach (i.e. Markov method). This system was further divided into five subsystems, and single-order differential equations are derived using the transition diagram. MATLAB software was used to determine the performability of the system for various combinations of repair and failure rates.FindingsIn this research work, performability analysis was done using different combinations of repair and failure rates for these subsystems. Further, a decision matrix (DM) has been developed that indicates that edge cutting burr is the most critical subsystem, which requires the top level of maintenance priorities among the various subsystems. This matrix will facilitate policymaking related to various maintenance activities for the respective system.Originality/valueIn this research work, a mathematical modeling based on a single differential equation using a transition diagram has been developed for the SPVC line system. The novelty of this work is to consider interaction among different subsystem, which generates more realistic situation during modeling. The purposed DM helps make future maintenance planning, which reduces maintenance costs and enhances system's performability.

Optimizing asset management for Structure System Components of RSG-GAS: A reliability-centric approach

This study focuses on the Structure, System, and Components (SSC) of G.A Siwabessy Multipurpose Reactor (RSG-GAS), emphasizing the integration of reliability improvement within asset management optimization. The research aims to derive Maintenance Priority Index (MPI) values, contributing to system reliability ratings, crucial for assessing component functionality and estimating Remaining Useful Life (RUL) The methodology involves measuring critical aspects of system quality, safety, and cost. The MPI value, representing 10 % of SSC critical components, guides subsequent reliability calculations. Utilizing failure data from RSG-GAS components (2010–2018) and reactor core configurations (70th-96th core), SSC reliability is simulated using Monte Carlo simulation, with RUL based on real data. High MPI values are identified for critical components such as KBE01/AP01-02_B in the primary purification system, JE-01/AP01-02_A in the primary cooling system, and PA01-02/CR001_A in the secondary cooling system. Maintenance intervals of 100 days are recommended for KBE01/AP 01–02_B and JE-01/AP01-02_A, exceeding 50 % reliability, while PA01-02/CR001_A maintenance can extend to 75 days. Monte Carlo simulation results, with 1000 samples, closely align with real reliability values. The RUL result projects operational lifetimes of 225.6, 221.4, and 171.5 days for KBE01/AP 01–02_B, JE-01/AP01-02_A, and PA01-02/CR001_A components. This study improves asset management, offering practical insights for critical safety system component maintenance planning.

Application of Network Reconstruction Algorithm to Compute Maximum Flow for Water Supply Network: A Case Study of the City of Bulawayo, Zimbabwe

Determining the maximum flow value in Water Supply Networks (WSN) is a common problem that is being faced by many cities during and after designing of WSN. In this article, the network reconstruction (NR) algorithm is applied to compute the maximum flow value for the city’s WSN based on the actual data. The city of Bulawayo has been selected for the following reasons, availability of research data, the city is facing severe water shedding and several studies have focused only on other issues such as alternative water sources, leakage detection and demand forecasting. The goal of this study is to determine the maximum flow value from the sources to the reservoirs. The results have revealed that the computed maximum flow value is within the estimated range of 110,000 cubic meters to 190,000 cubic meters. Dam sensitivity analysis were considered to determine the sources to give maintenance priority before the rain season. Several recommendations were suggested to improve the water supply situation.

Optimized deep learning for steel bridge bolt corrosion detection and classification

Corrosion of steel bridge bolts poses a major threat to structural integrity. As a key component, bridge bolts are susceptible to corrosion and detachment, necessitating close monitoring during maintenance. However, the vast number of corroded bolts presents challenges. Conventional detection relies on subjective visual inspection without unified assessment criteria. Fast and accurate localization and classification of bolt corrosion levels thus became a research priority for bridge maintenance. This study puts forward a new two-stage corrosion detection method, integrating Deep Convolutional Generative Adversarial Network (DCGAN) and improved You Only Look Once version 5 (YOLOv5) networks, which enables rapid categorization of bridge bolts by different corrosion extents, providing an intelligent solution for bridge maintenance. First, in the image preprocessing stage, a DCGAN with least squares loss generates simulated corroded bolt images through adversarial learning to expand the dataset. Second, three corrosion levels are defined based on visual features and percentage of surface rust, with this classification scheme applied in dataset annotation. Finally, the annotated images are input into an enhanced YOLOv5 model named YOLOv5-SE for corrosion identification. To improve accuracy, Squeeze-and-Excitation blocks are added after each residual block in the YOLOv5 backbone. Comparative experiments prove YOLOv5-SE's superior performance over YOLOv5 and other models like Faster R-CNN and VGG16. A pytorch system enables model deployment for corrosion detection. The integration of DCGAN simulation and attention-optimized YOLOv5-SE enables precise classification and localization of corroded bolts. This study represented a significant step towards intelligent upgrades in steel bridge maintenance.

Building Maintenance Priority Decision Support System Using the Method Profile Matching

Along with the increasing age of a building, maintenance activities become things that need to be done to minimize damage that occurs such as damage to the ceiling or ceramics. Therefore, this study aims to determine the priority of building elements in the treatment of architectural components in buildings A and B ITK campus using Profile Matching method. Based on the results of analysis and observations in the field, the elements that are the main priority in the architectural component of Building A are ceiling elements, the second priority element is sanitary elements, the third priority element is floor elements and door and window elements, the fourth priority element is painting elements, and the last priority element is Wall pair elements. Whereas in the architectural component of Building B, the main priority elements are ceiling elements and sanitary elements, the second priority element is the wall pair element, the third priority element is the floor element and the door and window element, and the last priority element is the painting element.

Evaluation of building condition index, repair, and maintenance priority order (Case study: Lecture room of engineering faculty, Syiah Kuala University)

The Engineering Faculty building at Syiah Kuala University was constructed in 1963 and completed in 1998. Visible damages can be observed on the components. Therefore, this study aimed to evaluate the damages to these components, the condition index (CI) value, as well as the priority order for repairing and maintaining the building. The process commenced by evaluating the physical condition of the lecture hall. Questionnaires were also distributed and the data were then analysed using the Analytical Hierarchy Process (AHP) method to determine the weights of the component. These weights were combined with the volume of component damage to obtain the building’s CI values. The results showed that the majority of the damage in the Faculty of Engineering at Syiah Kuala University was related to architectural components. The Building Condition Index (BCI) classified all structures were in Zone 1 where indicated a very good condition with values ranging from 87.09% to 97.83%. Building A, received the highest priority for repair and maintenance, followed by the PPI and the D3 Civil Engineering structure. Regarding the building elements, columns were given the highest priority with a weight of 0.226, whereas carpet floor coverings were assigned the lowest with a mass of 0.003.

A Clustering-based Approach for Maintenance Prioritization of Medical Devices in a New Hospital

Medical devices are fundamental to preventing, diagnosing and treating disease and high availability of them is vital for the uninterrupted operation of a hospital. That is why hospitals should plan and carry out maintenance activities to keep their medical devices in a healthy operating condition. The effectiveness of these activities can be increased by determining the maintenance priorities of devices. On the other hand, setting individual priorities for each device becomes complicated when a hospital has hundreds of medical devices. In this concern, grouping medical devices and determining group-based maintenance priorities will be more advantageous for maintenance planning. In this study, a novel approach is proposed for the maintenance prioritization of medical devices in a new hospital. In the proposed approach, first prioritization attributes are defined and weighted using the analytical hierarchy process (AHP). Then, medical devices are grouped based on the predetermined attributes by using data clustering. Finally, maintenance priorities of medical device clusters are determined based on the weighted sum of cluster centers.

Optimization of selective maintenance problem with stochastic durations in mission-oriented system subjecting to [formula omitted]-dependent competing risks

The mission-oriented systems (MOS) are often required to operate a consecutive of missions interspersed with finite breaks. For MOS, an appropriate maintenance strategy is the selective maintenance (SM). The SM problem (SMP) aims then to identify an optimal set of components to be maintained under maintenance resource constraints such as limited break durations. However, most existing SM models merely deals with either stochastic independent (s-independent) components in MOS or deterministic mission and break durations. To overcome this unrealistic restriction, this paper develops a novel SM model for optimizing the SMP in MOS operating under stochastic mission and break durations and s-dependent competing risks (CRs). Durations of missions and breaks are respectively governed by normal and uniform distributions, while the s-dependent CRs are captured by the copula function of which the unknown parameters are estimated relying on the two-stage MLE method. Furthermore, due to the stochastic break durations, an integrated importance measure (IIM) is introduced to measure the maintenance priority on selected components. The resulting SM optimization model is therefore formulated as a mixed-integer nonlinear program (MINLP) whose objective is to minimize the total cost while ensuring the required minimum mission reliability. A differential evolution (DE) algorithm is designed to solve the MINLP. Two numerical experiments are conducted on a ball screw system. Results obtained demonstrate the validity of our proposed model, in addition to the robustness of the solution algorithm designed.

Indexing the Maintenance Priority of Road Safety Barriers in Urban and Peri-Urban Contexts: Application of a Ranking Methodology in Bologna, Italy

The need for clear and updated information is pivotal when authorities plan and perform routinary, periodic and emergency maintenance of both road network and their roadside assets, e.g., curbs, signals, and barriers. With particular regard to road barriers, the development of remote sensing technologies, such as Laser Imaging Detection and Ranging (LiDAR), has played a disruptive role in acquiring information, so the surveys today are predominantly automatic, faster, and less biased than the traditional (i.e., visual and manual) inventorying methodologies. However, even though they are accurate, these emerging procedures usually focus only on the surveyed elements and do not provide any other information about the surrounding environment or about the qualitative degradation of the elements. The primary objective of this research effort was to present a ranking methodology for enhancing road safety in urban contexts. Due to an innovative synthetic index which takes into account both the deterioration and the location of the surveyed elements, maintenance priority of road barriers was outlined in Bologna, Italy. All the collected information was georeferenced in a Geographic Information System (GIS) environment and hence plotted in thematic maps for an easier analysis. In addition, compliance to the norm was verified. The research was tested to provide public authorities with an effective tool in the evaluation of maintenance activities and road safety policies.

Sustainable Prioritization of Public Asphalt Paved Road Maintenance

The development of transportation infrastructure is crucial for a country's progress as it enables access to social and economic amenities and acts as a vital link between production and consumption. This is particularly significant for landlocked nations like Zambia, which heavily rely on a wide network of public highways, including both paved and unsurfaced roads. Regardless of their quality and construction, all road surfaces degrade over time due to the combined effects of traffic load and environmental factors. If not properly managed, this can lead to costly repairs and rehabilitation efforts. Government organizations face a dilemma when deciding which public roads to prioritize for maintenance. This follows that the inherent hurdle is competing needs within limited finances for infrastructure development. However, the challenge of road maintenance prioritization can be addressed by adopting a multi-criteria approach. This study aims to address the issue of sustainability and provides insights into which public roads should be given priority for maintenance. The research proposes a comprehensive set of criteria focusing on sustainability and assigns relative importance to them, with emphasis on state of deterioration, emergency function, climate resilience, environment, strategic importance, social considerations, economic factors, and political importance. It suggests that road maintenance decision-making should prioritize sustainability, resilience, and societal well-being, challenging traditional assumptions.

Multi-temporal analysis to support the management of torrent control structures

In the last decade with increasing frequency of extreme weather events, an accurate, sustainable, and effective planning of torrent control structures has become essential to reduce hydro-geomorphic risk. Quite often in planning interventions, there is a lack of information on the effectiveness of existing structures, the evolution of the ongoing hydro-geomorphic process, and a priori in-depth study to analyze the sediment morphology dynamics and the interaction with possible existing torrent control structures.Nowadays, High-Resolution Topography data (HRT) greatly simplifies the monitoring of sediment morphology dynamics and the understanding of the interaction with torrent control structures over time. Therefore, thanks to repeated HRT surveys, it is possible to derive multi-temporal Digital Terrain Models (DTMs), and DTMs of Difference (DoDs) to quantify the morphological changes and study continuously the catchment morphodynamics. This information can be very valuable to support watershed management plans if combined with up-to-date field surveys that identify the existing torrent control structures, and asses their current status and functionality.The present work aims at introducing a methodological approach based on the integration of the sediment morphology dynamics data over large time spans (e.g., from 2003 to 2022), obtained by multi-temporal DoDs (realized from three DTMs at 1 m resolution), with an updating cadastre of torrent control structures enriched by a very simple, quick, and user-friendly Maintenance Priority index (MPi). The proposed workflow proved to be very useful in the test basins analysed, providing more complete data on torrent control structures and sediment dynamics evidence to stakeholders compared to the past. Moreover, it served as a proxy to assess the long-term effectiveness of the management interventions. The approach also helped to constantly identify the areas most prone to hazards, improve the intervention planning, and find more appropriate solutions or direct the maintenance works.Finally, the suggested workflow could be the starting point to outline up-to-date guidelines to be used in other catchments equipped with torrent control structures, emphasizing possible intervention priorities on where decision-makers could better invest resources. By providing current information and accurate tools to realize a more complete decision-making chain, which is often neglected, it is certainly possible to support more sustainable and effective risk management decisions.

The Applicability of Multiple MCDM Techniques for Implementation in the Priority of Road Maintenance

Priority of road maintenance can be viewed as a process influenced by decision-makers with varying decision-making power. Each decision-maker may have their view and judgment depending on their function and responsibilities. Therefore, determining the priority of road maintenance can be thought of as a process of MCDM. Regarding the priority of road maintenance, this is a difficult MCDM problem involving uncertainty, qualitative criteria, and possible causal relationships between choice criteria. This paper aims to examine the applicability of multiple MCDM techniques, which are used for assessing the priority of road maintenance, by adapting them to this sector. Priority of road maintenance problems subject to internal uncertainty caused by imprecise human judgments will be reviewed and investigated, as well as the most popular theories and methods in group MCDM for presenting uncertain information, creating weights for decision criteria, examining causal relationships, and ranking alternatives. The study concluded that through the strengths and weaknesses reached, fuzzy set theory is the most appropriate and best used in modeling uncertain information. In addition, the methods that are employed the most common in the literature that has been done to explore the correlations between decision criteria have been examined, and it is concluded that the fuzzy best-worst method may be utilized in this research. The Fuzzy VIKOR approach is most likely the best method for ranking the decision alternatives.

Maintenance priority towards the features and facilities in Malaysian public parks: Visitors’ perspective versus actual experience

Maintenance priority towards the features and facilities in Malaysian public parks: Visitors’ perspective versus actual experience

Priorities in Croatian School Building Maintenance: A Comparison of the Main Stakeholders’ Views

This paper aims to examine the opinions of the main recognized stakeholders in the maintenance of school buildings (i.e., the construction experts within the founders’ organization, the school staff, and the students), compare their views on the maintenance priorities, and identify certain differences. These data provide information about user needs, can help school founders make maintenance decisions, and are the basis for developing a new, balanced system of maintenance priorities. In the research, the survey questionnaire method was used to collect the data, whereby three groups of stakeholders evaluated the priority of eliminating certain defects in school buildings on a 5-point scale. For the purposes of the questionnaire, a model of 32 defects of the school buildings was created. In the questionnaire, 76 experts, 338 school staff, and 297 students participated. The research is limited to the Republic of Croatia. By conducting non-parametric statistical tests (Kruskal–Wallis and Mann–Whitney), it was shown that there were statistically significant differences in the stakeholders’ attitudes towards most maintenance priorities. There were also defects where statistically significant differences were not recognized, namely, regarding faulty lighting fixtures, faulty toilets, faulty sinks, faulty space cooling systems, faulty space heating systems, and faulty hot water heating systems. According to the experts, it is most urgent to remove faulty electrical installations, while according to the school staff, the highest priority is faulty sewage installations. The students believe that the priority is faulty toilets. The lowest priority is removing damage to the external environment (experts) and the facade (school staff and students).

Climate Change Adaptation Zones for Terrestrial Ecosystems—A Demonstration with Pinyon-Juniper Woodlands in the USA

Decision support tools are needed to ensure that appropriately timed and place-based adaptation is deployed in natural resource policy, planning, and management. Driven by accelerating climate change, analytical frameworks for adaptation are emerging to assist with these decisions. There is a natural relationship between climate change vulnerability assessments and adaptation responses, where low to high relative climate change vulnerability suggests “resistance” to “transformation” strategies for adaptation. The NatureServe Habitat Climate Change Vulnerability Index (HCCVI) embodies a process for ecosystem assessment that integrates both climate and non-climate data and knowledge to document the relative vulnerability of a given habitat or ecosystem type. The framework addresses climate exposure and ecosystem resilience. Since most measures of exposure and resilience are mapped, they can be utilized to create map zones that suggest climate-smart adaptation. We applied the HCCVI to a cross-section of 10 pinyon pine and juniper woodland ecosystem types in western North America. We then demonstrate the application of these outputs to adaptation zonation. Climate exposure defines relative adaptation strategies, while measures of resilience suggest specific priorities for habitat restoration and maintenance. By the mid-21st century, 3% and 23% of the combined area of these types in the United States was categorized as Directed Transformation or Autonomous Transformation, respectively. In just 10% of the combined areas for these types, Passive Resistance strategies are suggested.

Assessment and Prioritization of Highway Stretch Deploying Functional and Structural Characteristics

Asphalt pavements deteriorate over time when subjected to fatigue; hence, it is critical to evaluate in-service pavements to keep them in good condition. The goal of pavement evaluation is to assess the functional and structural performance of a pavement section, with a view to improving both the pavement's serviceability and riding quality. Through field and laboratory experiments, the current study attempts to evaluate the performance of pavement stretches. The sections are ranked and prioritized based on the test results. Medchal-Dabilpur national highway was evaluated for pavement roughness, skid resistance and deflections. In addition, core samples with diameters of 100mm and 150mm were collected and tested in the laboratory for moisture susceptibility, tensile strength, stiffness and fracture characteristics. The current study also intends to establish a unique technique for prioritizing pavement maintenance sections based on functional and structural performance in the field and laboratory. The Artificial Neural Network (ANN) approach was used to develop the relationship between pavement functional and structural performance. Heat maps were created and ranked in Python Jupyter notebook to better visualize the performance of functional and structural characteristics of the pavement. The final evaluation results can be validated by supporting them with laboratory investigations based on the pavement-section field samples. The results demonstrate that there is a strong relationship between the structural and functional properties of the pavement. The developed Maintenance Priority Index (MPI) will be useful in rating the maintenance and rehabilitation actions depending on the level of necessity. KEYWORDS: Functional and structural evaluation, Resilient modulus, Tensile strength ratio, Fracture properties, ANN technique, Maintenance priority index.

Optimisation of maintenance policies for a deteriorating multi-component system under external shocks

Many engineering systems are affected by shocks from their operating environments. When the state of a component degrades to a certain threshold level, preventive maintenance is needed for the purpose of reliability improvement. However, existing studies usually ignore the impact of shocks on different components of a system and therefore on the maintenance policies. This paper proposes to model the degradation processes of components with a k-dimensional Wiener process. Under both deterministic and stochastic environmental conditions, the Eyring model is used to measure the environmental importance of the multi-dimensional degradation process. Based on different failure scenarios, different maintenance strategies are therefore proposed. A periodic inspection policy is considered for each component that may fail due to external shocks. As for multiple components, the maintenance priority is determined based on the joint importance, and optimal preventive maintenance is obtained under the constraint of limited resources. Finally, a robot system is taken as an example to illustrate the proposed methods.