Maintenance Projects Research Articles

Diyarbakır Hasan Pasha Inn: A thorough evaluation of risk analysis and accessibility concerns

The importance of accessibility in maintaining historical and cultural structures is evident across all facets of society. It is crucial to ensure that these structures remain secure, readily available, and sustainable, as they represent significant cultural heritage for both the local community and tourists. In this study, the risk analysis and accessibility status of the historic Hasan Pasha Inn in Diyarbakır’s Sur district were thoroughly explored. The Inn holds a significant historical and cultural location on Gazi Street, across from the Ulu Mosque. The primary goals of the research are to identify current risks, conduct a methodical analysis, and offer suggestions for risk mitigation. The Inn’s accessibility was assessed by aligning headings with the accessibility guide. The analysis utilized the 5x5 L-type matrix method to systematically evaluate risks based on specific criteria and determine their relative importance. Risk factors were categorized as minor (0–6), medium (8–12), major (16–20), and disaster (25 and above). A total of 31 risks were identified and grouped under different headings. Precautions were suggested for each risk with the goal of reducing the Inn’s overall risk levels. Measures such as improving physical access, enhancing emergency preparedness, implementing safety measures, and undertaking maintenance and repair projects are being pursued to promote tourism and enhance safety in the neighborhood for both locals and visitors. The study concludes by outlining the necessary actions to improve accessibility and safety at the Hasan Pasha Inn, while also contributing to the preservation of this historic building. The proposed measures aim to make the Inn more accessible to both locals and tourists, and to ensure the sustainability of this culturally significant site. The findings of the study will serve as a valuable resource for enhancing accessibility standards and conserving historic buildings. The limited number of publications on accessibility in historical buildings reveals the need to raise awareness in this field and offer solution suggestions; Therefore, the work we carry out is of great importance. It is expected that this study will offer insights for future risk analyses and accessibility evaluations of similar structures.

Enhancing infrastructure project outcomes through optimized contractual structures and long-term warranties

PurposeThis study delves into the influence of contractual frameworks on infrastructure project timelines and evaluates the role of long-term warranty agreements in maintenance efficacy. It underscores the correlation between construction contract structures and prevalent project delays, advocating for a revision in the allocation of responsibilities to mitigate such delays effectively.Design/methodology/approachWhile previous research has explored individual aspects of construction management, such as contractor incentives and risk allocation, our study uniquely integrates these elements to develop a comprehensive model that includes the effects of long-term warranty agreements and penalty clauses.FindingsThe findings advocate for contract revisions that entail clearly articulated responsibilities and thorough impact assessments, aimed at enhancing the efficiency of project execution and optimizing infrastructure investment returns. Concrete examples are provided from large-scale infrastructure and public works maintenance projects, illustrating the benefits of well-defined penalty clauses in curbing delays and ensuring sustained quality through long-term warranties. Our results demonstrate that optimized contractual structures can significantly reduce project delays and enhance maintenance effectiveness.Originality/valueThis study addresses significant gaps in understanding construction contract management dynamics, especially in transportation infrastructure. It rigorously analyzes how penalty clauses and long-term warranties impact contractor behavior and project outcomes. Key findings show that the benefits of long-term warranties, including social advantages, depend heavily on the strictness of penalty clauses. Innovatively, it employs a First-Price Sealed-Bid Auction framework with empirical data from various case studies, enhancing contract structure optimization for better stakeholder alignment and infrastructure integrity. These insights notably advance construction contract management methodologies.

The Effects of Temporary Portable Rumble Strips on Vehicle Speeds in Road Work Zones

The safety of construction and maintenance work zones has been highlighted as a crucial aspect of construction management that requires special attention due to the increasing number of fatal and non-fatal injuries in recent years. Temporary traffic control (TTC) is required by the Occupational Safety and Health Administration (OSHA) to improve overall safety performance during road construction and maintenance projects. The fact that speeding and distracted drivers may overlook TTC warning signs and directions has been reported as one of the leading causes of work zone incidents. This study aimed to examine both the impact of temporary portable rumble strips (TPRSs) on traffic speeds and the response of different vehicle types in road work zones, including trucks and cars. Accordingly, field experiments were conducted in collaboration with the Road Commission for Oakland County (RCOC) in Michigan. The findings indicate that TPRSs have a statistically significant impact on the driving speed of light vehicle drivers but not on medium and heavy vehicles, such as trucks. This study contributes to the existing literature by quantifying the safety benefits of TPRS use, providing valuable data for policymakers and construction professionals. By demonstrating the effectiveness of TPRSs in reducing the speed of light vehicles, this research supports the implementation of these systems as a practical measure for enhancing safety within road construction work zones. Additionally, this study highlights the need for tailored approaches to address the limited impact on larger vehicles, underscoring the importance of developing complementary strategies to ensure comprehensive safety improvements across all vehicle types.

Evaluation of Project Time Performance in the Upstream Oil and Gas Industry: The Case of Ghana

An emerging economy like Ghana, one of the developing nations in Africa, is fortunate to have started exploration not long ago, which means that it is still developing in the field of upstream oil and gas exploration compared to other industrialized nations that have a lot of experience in the field of project management and oil exploration. About 80% of the management style in the upstream oil and gas sector is project-based; therefore, any delays in project deliveries and completion will have a negative effect on completion time and, at the end of the day, affect the performance of the organization as a whole as well as the nation as a whole. Only Crude Oil Storage Tank Maintenance Project in the upstream oil and gas industry in Takoradi, Western Region, was included in the research. Secondary data was taken on nine completed Crude Oil Storage Tank Maintenance Project from managers preoccupied with project management in the Ghanaian upstream oil and gas industry in the Western Region of Ghana. These willing management staff have been employed in the sector for more than 3 years. The study used the budgeted cost of work scheduled (BCWS) and the budgeted cost of work performed (BCWP) as inputs to calculate the estimated schedule (ES) and actual time (AT) to finally calculate the schedule performance index (SPI) and schedule variance (SV). The purpose of the study is to evaluate the performance of project time in the Ghanaian upstream oil and gas industry. The study demonstrates that out of the nine Crude Oil Storage Tank Maintenance Project in the Ghanaian upstream oil and gas industry analyzed using both the schedule performance index and schedule variance, eight projects were completed on time and one project was delayed.

Corrigendum to Assessment of dispute causes in government building maintenance projects through adjusted importance rating and risk mapping Results in Engineering Volume 24, December (2024) 103551

Corrigendum to Assessment of dispute causes in government building maintenance projects through adjusted importance rating and risk mapping Results in Engineering Volume 24, December (2024) 103551

Assessment of dispute causes in government building maintenance projects through adjusted importance rating and risk mapping

Despite the reliance of Saudi Arabian government facilities on private contractors for maintenance, there is a persistent rise in disputes between these contractors and government entities. This ongoing issue raises concerns about the efficiency and effectiveness of contract management, ultimately affecting the quality of maintenance services and operational continuity. This study investigates the primary causes of disputes in government building maintenance projects, using both the Frequency Adjusted Importance Index (FAII) and risk mapping methods to analyze and prioritize the causes. A literature review and a designed questionnaire survey were employed to rank dispute causes. Thirty-six responses were analyzed. Cronbach's alpha and coefficient of variation were utilized to assess the collected data's validity and reliability. Three case studies then were utilized as a validation tool, compared against the findings of the survey to integrate practical insights with the theoretical results from the survey. The findings reveal that issues such as (1) the lack of original as-built drawings, (2) constant government interference, (3) delays in decision-making, (4) poorly defined scope of work, and (5) mistakes in bidding or cost estimation are the most critical causes of disputes in these projects. Cross-method validation with real-world case studies further strengthens the reliability of these findings, as these top-ranked causes consistently align with issues encountered in practice. The findings of this study could assist local authorities adopt alternative approaches in managing and executing maintenance contracts, thereby mitigating the causes of disputes.

Monitoring and Evaluation Practices and the Performance of Kenya National Highways Authority Road Maintenance Projects in Central Region, Kenya

Monitoring and Evaluation Practices and the Performance of Kenya National Highways Authority Road Maintenance Projects in Central Region, Kenya

Advanced Monte Carlo simulations and benchmark of residual dose rate assessments in the ATLAS detector at CERN LHC

Background The European Organization for Nuclear Research (CERN) pushes the frontiers of physics through the Large Hadron Collider (LHC), a 27-kilometre hadron accelerator capable of producing proton-proton collisions at a center-of-mass energy of up to 13.6 TeV. Its four main detectors (ALICE, ATLAS, CMS, LHCb) are unique examples of advanced particle detection technology and complexity. Ensuring radiological safety throughout the LHC’s environments and lifecycle is a critical task managed by the CERN Radiation Protection group. In this context, assessing residual dose rates is crucial for planning exposure situations, such as maintenance and upgrade projects during LHC shutdowns. Methods This work presents advanced Monte Carlo techniques developed at CERN to predict residual dose rates in the LHC experimental caverns, focusing on the ATLAS detector. Predictions are made using the FLUKA Monte Carlo code and the SESAME toolkit for two-step simulations. The simulation results are benchmarked against experimental residual dose rate measurements collected during LHC Long Shutdown 2 at ATLAS. Additionally, forecasts for Long Shutdown 3 are also presented. Results The FLUKA benchmark for the ATLAS detector demonstrates a general agreement within a factor of 1.5. This consistency validates both the FLUKA geometry model of the ATLAS detector and the reliability of the Monte Carlo techniques used to predict residual dose rates in such complex environments. Conclusions The study highlights the predictive capabilities of the FLUKA and SESAME coupling for simulating residual dose rates in large LHC experiments. This method plays a crucial role in ensuring radiological safety, primarily for dose prediction and optimization. The reliability of this approach is significantly supported by the benchmark results obtained at ATLAS and presented in this paper.

Promoting cooperation in collective actions: Evidence from the reserve fund for maintenance in China

Cooperation among group members is the ultimate pursuit in any collective actions. Despite the presence of well-documented theories and experimental evidence in the collective action problem, the empirical evidence on promoting cooperation in the problem is scarce. We examine the collective tasks of using reserve funds for maintenance in urban residential areas using a unique administrative data that covers approximately 5,000 maintenance projects in Nanjing, China. Applying an instrumental variable approach, we show that a 1,000 yuan increase in extra cash payment increases the consent rates of implementing a maintenance plan by approximately 1 percentage point. Our results suggest that additional information revealed by uncovered maintenance costs could serve as a non-monetary tool to promote cooperation in making collective-action decisions. We confirm the conjecture by surveying 112 householders involved in the maintenance projects.

Assessment of Overflow Risk in Agricultural Reservoir Based on Water Balance Theory

The unexpected climate changes are causing rainfalls to exceed the design frequency, which complicates the management and operation of agricultural reservoirs and increases the risk of overflow. According to the “Planning and Design Standards for Agricultural Prediction Infrastructure Maintenance Project (Fill Dam Section),” agricultural reservoirs were originally designed without flood control functions, with the standard being to directly discharge incoming flood. Based on this foundation, this study assesses the overflow risk of agricultural reservoirs using the concepts of inflow and outflow theories as well as storage capacity. The balance when inflow and outflow are at their maximum was analyzed for prioritized areas, focusing on the flood management area (the area between the full water level and crest elevation) relative to the basin area, to examine the feasibility of balance through flood routing. The proposed method is easily accessible to facility managers, enabling them to assess the risk of reservoirs for efficient management and operation during floods.

Insights into potential of banana leaf powder as a mud soil stabilizer

This study proposes a novel method for managing surplus soil in urban construction projects by investigating the use of banana leaf powder (BLP) as an eco-friendly and efficient mud-soil stabilizer. This study is pioneering in its focus on the use of an agricultural waste product, BLP, as an alternative to conventional methods that frequently rely on cement or lime, which pose environmental concerns owing to their high alkalinity and carbon emissions. BLP, derived from dried and pulverized banana leaves, traditionally used in various industries, was evaluated for its suitability as a stabilizer against orange peel biopolymer (OBP) and fly ash (FA). The findings of this study are groundbreaking. BLP's water absorption capacity, Wab, although lower than that of OBP, was significantly higher than that of FA, demonstrating its potential as a mud soil stabilizer. BLP increased the compaction and strength of the treated clay, whereas OBP made it more challenging to compact the clay owing to gelatinization. The ease of compaction with BLP is attributed to the absorption of free water into the pores of the particles. These results suggest that differences in the stabilizer's water absorption mechanism affect the effectiveness of the post-treatment compaction process on the treated soil. An analysis of the impact of water absorption capacity on the cone index, qc, revealed a material-independent relationship between the parameter β (=Wab × A, where A denotes stabilizer addition content) and qc for BLP and FA. This is because, in contrast to OBP, BLP and FA did not gelatinize the free water that was not absorbed by the stabilizer and remained in the same form within the treated clay. This indicates that understanding the water absorption capacity and mechanism of organic- or inorganic-based stabilizers is important for predicting the strength of treated soil. The same relationship between β and qc holds true for the hybrid-treated clay using both BLP and FA, with β considered to be the sum of β for both BLP and FA. Furthermore, this study innovatively addresses the concern of BLP decay in treated soil by creating a hybrid stabilizer with FA and conducting experiments to accelerate BLP decay using fungal mycelia. These experiments revealed that the hybrid-treated clay exhibited a more gradual decrease in carbon content and stabilized pH levels, implying that FA could inhibit decay by fungal mycelia, improving the BLP-treated soil's long-term durability. These findings suggest that agricultural wastes with high organic content can be effectively used for soil stabilization and ground improvement in civil engineering construction and maintenance projects by combining inorganic materials and taking advantage of their properties, such as high water absorbency. This can address the issues (such as high alkalinity and high carbon dioxide emissions) associated with cement- and lime-based stabilizers, which were previously widely used.

Multi-Source Data Fusion for Vehicle Maintenance Project Prediction

Ensuring road safety is heavily reliant on the effective maintenance of vehicles. Accurate predictions of maintenance requirements can substantially reduce ownership costs for vehicle owners. Consequently, this field has attracted increasing attention from researchers in recent years. However, existing studies primarily focus on predicting a limited number of maintenance needs, predominantly based solely on vehicle mileage and driving time. This approach often falls short, as it does not comprehensively monitor the overall health condition of vehicles, thus posing potential safety risks. To address this issue, we propose a deep fusion network model that utilizes multi-source data, including vehicle maintenance record data and vehicle base information data, to provide comprehensive predictions for vehicle maintenance projects. To capture the relationships among various maintenance projects, we create a correlation representation using the maintenance project co-occurrence matrix. Furthermore, building on the correlation representation, we propose a deep fusion network that employs the attention mechanism to efficiently merge vehicle mileage and vehicle base information. Experiments conducted on real data demonstrate the superior performance of our proposed model relative to competitive baseline models in predicting vehicle maintenance projects.

Research on risk management of ship maintenance projects based on multi agent swarm model simulation method

In recent years, the role of naval ship power has become increasingly prominent in regional conflicts and military operations worldwide, and the powerful capabilities demonstrated by naval forces have also been valued by countries around the world. While naval forces are frequently deployed to carry out various tasks, the intensity of equipment wear and tear on ships is also significantly increasing, posing a huge challenge to the maintenance and support capabilities of ship equipment. In the actual process of ship equipment maintenance, a series of risk factors such as cost, schedule, and quality will have a significant impact on the entire ship maintenance project, and even affect the success or failure of the entire project. This article first decomposes the project process of ship maintenance projects, further analyzes the various risk factors of ship maintenance projects based on the project decomposition situation, and then distinguishes the overall project, project process, and project risk factors to establish an intelligent agent group model for simulation analysis. Through the above simulation analysis, we will conduct in-depth research on the specific impact of project risks on ship maintenance projects, and analyze and verify the positive role and practical significance of project risk management in project risk control and project efficiency improvement. In the process of the above research content, methods and measures for risk management of ship maintenance projects are proposed, providing scientific and efficient risk management suggestions for such projects, improving the scientific management efficiency of ship maintenance projects, and contributing to the improvement of the quality and efficiency of project management.

Failure rate analysis and maintenance plan optimization method for civil aircraft parts based on data fusion

In the face of data scarcity in the optimization of maintenance strategies for civil aircraft, traditional failure data-driven methods are encountering challenges owing to the increasing reliability of aircraft design. This study addresses this issue by presenting a novel combined data fusion algorithm, which serves to enhance the accuracy and reliability of failure rate analysis for a specific aircraft model by integrating historical failure data from similar models as supplementary information. Through a comprehensive analysis of two different maintenance projects, this study illustrates the application process of the algorithm. Building upon the analysis results, this paper introduces the innovative equal integral value method as a replacement for the conventional equal interval method in the context of maintenance schedule optimization. The Monte Carlo simulation example validates that the equivalent essential value method surpasses the traditional method by over 20% in terms of inspection efficiency ratio. This discovery indicates that the equal critical value method not only upholds maintenance efficiency but also substantially decreases workload and maintenance costs. The findings of this study open up novel perspectives for airlines grappling with data scarcity, offer fresh strategies for the optimization of aviation maintenance practices, and chart a new course toward achieving more efficient and cost-effective maintenance schedule optimization through refined data analysis.

Population Characteristics and Habitat Management of the Useful Seaweed Silvetia siliquosa

We aimed to analyze the natural population characteristics and habitat growth conditions of the valuable seaweed Silvetia siliquosa. Its population characteristics and habitat conditions were assessed monthly from May 2022 to April 2023 and April to August 2022, respectively, on selected habitats. The average population density, coverage, and frequency of S. siliquosa were 579 ± 94.18 ind./m2, 27.82 ± 6.92%/m2, and 78.37 ± 5.98/m2, respectively. The average thallus length and width were 47.53 ± 4.35 and 46.33 ± 4.17 mm, respectively, while the branch width, thickness, and frequency were 2.35 ± 0.03 mm, 0.59 ± 0.12 mm, and 2.8 ± 0.2 times, with a receptacle length and width of 24.13 ± 2.07 and 2.81 ± 0.19 mm, respectively. Among the 40 previously known natural habitats of S. siliquosa, growth was confirmed only in Sepo, Sebang, and Bangpo. The causes for the declining S. siliquosa populations could be attributed to habitat changes due to construction, coastal road maintenance projects, habitat disturbances, and increased pollutants. Habitat substrate disturbances and changes were the main causes of the decrease in S. siliquosa growth. Studies on environmental factors and habitat degradation, growth related to environmental factors, mass cultivation, and the marine ecosystem restoration of S. siliquosa are needed.

The Prospect of Introduction of Tourism Tax as a Source of Increase of Own Income of Yerevan City

In order to get a general idea about the financial sector of the city of Yerevan, one should study the financial opportunities of Yerevan. By concentrating people, resources and investment in one place, big cities have the opportunity to influence economic development, stimulate innovation and deepen social relations. This circumstance is the basis for the need to study the features of financial management of large cities and identify the problems, because they are one of the main driving forces of the country's development program. One of the main problems of the city of Yerevan is the effective management of limited resources, ensuring the realization of not only the right, but also the ability to provide efficient public services to the population of the community. In this regard, we emphasize the provision of a stable and flexible base of financial resources equivalent to the implementation of the powers assigned to the Yerevan community by law, the use of opportunities for the formation of own financial resources and the implementation of independent financial policy. Using the resources of the city of Yerevan, we can pay attention to the flow of tourists, which is a possible way to increase Yerevan's own income. Tourism taxes are small fees, usually levied indirectly by accommodation or leisure establishments, and usually go towards the city's maintenance and development projects, as well as providing favorable conditions for the tourism industry.

Mileage-Aware for Vehicle Maintenance Demand Prediction

It is of paramount importance to accurately predict the maintenance demands of vehicles in order to guarantee their sustainable use. Nevertheless, the current methodologies merely predict a partial aspect of a vehicle’s maintenance demands, rather than the comprehensive maintenance demands. Moreover, the process of predicting vehicle maintenance demands must give due consideration to the influence of mileage on such demands. In light of the aforementioned considerations, we put forth a vehicle overall maintenance demand prediction method that incorporates vehicle mileage awareness. In order to address the discrepancy between the vector space of mileage and that of the project, we put forth a mileage representation method for the maintenance demand prediction task. To capture the significant impact of key mileage and projects on future demand, we propose a learning module for key temporal information using a fusion of Long Short-Term Memory (LSTM) networks and attention mechanism. Moreover, to integrate maintenance mileage and projects, we propose a fusion method based on a gated unit. The experimental results obtained from real datasets demonstrate that the proposed model exhibits a superior performance compared to existing methods.

A framework for analysis of stakeholder dynamics and value creation in industrial maintenance projects: the stakeholder ipot

This paper proposes a methodological approach that can be applied in practice for evaluating stakeholder dynamics and assessing projects against appropriate value propositions within an industrial maintenance project context. A conceptual framework is proposed and is demonstrated through a case analysis. It is expected that the proposed methodology, the Stakeholder Interdependent Performance Opportunities and Threats, (Stakeholder iPOT), can advance project management practice by offering a mechanism for analysing stakeholder expectations and responses to the opportunities and threats that different project events present. This study highlights the need for continued investigation not only within the context of industrial maintenance projects but also in other sectors to improve our understanding and ability to effectively manage stakeholder dynamics.

Characteristics of life-cycle carbon dioxide emissions of arterial highway maintenance and the influencing factors

With the focus of highway development transitioning from construction to maintenance, a comprehensive understanding of the characteristics and influencing factors of carbon dioxide (CO2) emissions from highway maintenance activities is crucial for formulating effective strategies to promote the low-carbon development of road infrastructure. However, the quantitative relationships between CO2 emissions from highway maintenance schemes and factors such as pavement deterioration, traffic volume, and road grade remain unclear owing to a lack of comprehensive, multi-category, and real data. Using real maintenance data from 340 arterial highway segments in China, this study conducts the life cycle assessment (LCA) to estimate CO2 emissions from maintenance activities and examines the primary emission sources among various structural layers and materials. Furthermore, multiple linear regression (MLR) analysis is conducted to investigate the impact of traffic volume, road grade, and pavement deterioration on CO2 emissions from maintenance projects, and factors influencing the early-stage degradation of pavement performance. The results demonstrate that average CO2 emissions from heavy rehabilitation projects are 6.97 times higher than those from medium rehabilitation projects. Emissions from heavy rehabilitation projects exhibit a significantly negative linear relationship with the riding quality index (RQI) before maintenance (p < 0.05), and emissions from medium rehabilitation projects show a significant negative linear relationship with the pavement condition index (PCI) before maintenance (p < 0.05). Emissions from heavy and medium rehabilitation projects are significantly positively correlated with heavy vehicle traffic volume before maintenance (p < 0.05). Moreover, the early-stage degradation of PCI after heavy rehabilitation and RQI after medium rehabilitation exhibit significantly negative linear relationships with their respective indicators before maintenance (p < 0.05). The early-stage degradation of RQI after heavy rehabilitation is significantly positively correlated with CO2 emissions from the base course and cushion layers (p < 0.05). The findings emphasize that timely maintenance and reduction of CO2 emissions from asphalt mixing equipment are essential for mitigating emissions from road maintenance. This study offers valuable insights for advancing the low-carbon development of highways in temperate regions.

Public clients pursue innovation, but what’s going on at the project level? A case study of infrastructure operation and maintenance

This paper examines the gap between macro-level calls for innovation and the micro-level enactment, by exploring the discrepancies between a public client’s pursuit of innovation and the actions taken at the project level. Through empirical analysis of four infrastructure operation and maintenance projects, we identify discrepancies within and between procurement strategies and project-level practices. Taking a strategy-as-practice perspective, our study shows how procurement strategies are adapted and enacted by inter-organizational project actors, shedding light on why macro-level innovation intent may not translate into expected outcomes at the project level. Our findings underscore the importance of aligning macro-level directives with micro-level actions to drive innovation in construction projects effectively. This research contributes to a better understanding of the dynamics shaping innovation in construction projects, highlighting the critical role of procurement strategies in bridging macro and micro contexts to achieve sustainable development goals.