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The purpose of this paper is to present a study of reliability-centred maintenance (RCM), which is conducted on the key sub-assets of a newly constructed road junction infrastructure in Nigeria.

The classical RCM methodology, a type of RCM, which has a top down, zero-based approach for maintenance analysis, is implemented in this study.

The implementation of the classical RCM is successful in its application of various PM policies assigned to the assets and it shows that its application in the highway industry could reduce excessive maintenance backlog and frequent reactive maintenance by effective optimisation of its preventive maintenance (PM) intervals.

Road junctions are originators of more than 70 per cent of road traffic congestion and account for high accident rate. The traditional methods of reliability assurance used in the highway industry such as reactive maintenance and routine maintenance are often inadequate to meet the round the clock usage demands of these assets, thus the consideration for the application of a systematic RCM process for maintaining the system function by selecting and applying effective PM tasks.

It uses an approach that critically develops and analyses thoroughly preventive and continuous maintenance strategy in a new circumstance with environment of uncertainty and limited operating data. The case-based reasoning cycle has been applied in the RCM approach with real-time data obtained from a UK-based network maintenance management system for highway infrastructures.

This study presents a reliability-based and sustainability-informed maintenance optimization model for telecommunications equipment. It considers several risk attributes associated with sustainability dimensions (i.e. social, economic and environmental aspects).

Many companies have developed long-term strategies to promote higher resource utilization, which has led to a paradigm shift in the role of maintenance. In parallel, reliability has been recognized as a fundamental factor in characterizing the optimal blend of maintenance strategies for a given system. It is essential for accurate failure prediction, which contributes toward more efficient use of all resources.

The corresponding subattributes are identified based on expert opinions and then incorporated into the proposed model. Subsequently, using the multiobjective particle swarm optimization (MOPSO), the proposed sustainability risks together with the maintenance costs are optimized, and the proper blend of maintenance strategies is identified.

Effective management of all human and natural resources, which are particularly emphasized by the concept of sustainability, has attracted much attention in recent years. However, contributions that effectively apply this concept in maintenance problems are very few and very few studies have attempted to quantify sustainability.

Automation of detecting cracked surfaces on buildings or in any industrially manufactured products is emerging nowadays. Detection of the cracked surface is a challenging task for inspectors. Image-based automatic inspection of cracks can be very effective when compared to human eye inspection. With the advancement in deep learning techniques, by utilizing these methods the authors can create automation of work in a particular sector of various industries.

In this study, an upgraded convolutional neural network-based crack detection method has been proposed. The dataset consists of 3,886 images which include cracked and non-cracked images. Further, these data have been split into training and validation data. To inspect the cracks more accurately, data augmentation was performed on the dataset, and regularization techniques have been utilized to reduce the overfitting problems. In this work, VGG19, Xception and Inception V3, along with Resnet50 V2 CNN architectures to train the data.

A comparison between the trained models has been performed and from the obtained results, Xception performs better than other algorithms with 99.54% test accuracy. The results show detecting cracked regions and firm non-cracked regions is very efficient by the Xception algorithm.

The proposed method can be way better back to an automatic inspection of cracks in buildings with different design patterns such as decorated historical monuments.

The purpose of this paper is to propose and confer a strategic cost model as a concept for good decision making for highway asset treatment in the transport industry.

The paper is based on asset performance condition and treatment renewals using a five-point performance for developing prospective treatment strategies. The strategic cost model is presented in the similitude of picturesque and its outcomes via an exploratory data analysis.

The results articulate the best maintenance plan for the forthcoming and future years. The strategic cost model uses the combination of the current condition band, the sample area and likely treatment cost for proposing the optimal treatment solution based on consideration of desired treatment level.

The strategic cost model is suitable for outlining the asset performance condition, treatment renewals and analytical cost optimisation. The formulated analytical cost model and developed prospective strategies enable good decision making, long-term contract negotiations and whole life cost maintenance and management.

Embracing eminent performance condition from the research area of lifecycle planning and deterioration models of a physical asset, a prospective cost strategy for asset maintenance is proposed in the study. The resultant treatment strategies using the analytical approach portray the ability that enables the adaptation of expected outcomes.

Automated condition surveys have been recently introduced for condition assessment of highway infrastructures worldwide. Accurate predictions of the current state, median life (ML) and future state of highway infrastructures are crucial for developing appropriate inspection and maintenance strategies for newly created as well as existing aging highway infrastructures. The paper aims to discuss these issues.

This paper proposes Markov Chain based deterioration modelling using a linear transition probability (LTP) matrix method and a median life expectancy (MLE) algorithm. The proposed method is applied and evaluated using condition improvement between the two successive inspections from the Surface Condition Assessment of National Network of Roads survey of the UK Pavement Management System.

The proposed LTP matrix model utilises better insight than the generic or decoupling linear approach used in estimating transition probabilities formulated in the past. The simulated LTP predicted conditions are portrayed in a deterioration profile and a pairwise correlation. The MLs are computed statistically with a cumulative distribution function plot.

The paper concludes that MLE is ideal for projecting half asset life, and the LTP matrix approach presents a feasible approach for new maintenance regime when more certain deterioration data become available.

Online spiral pipe manufacturing is one of the most common processes for producing water and gas transmission pipes. Weld quality and pipe circumstances are the most important qualitative characteristics of these pipes determining the overall cost of production. The purpose of this paper is describing how to implement Six Sigma on the production of spiral welded pipes with a real case study.

First, the capability of the pipe production process has been performed by using the defects per million opportunities to allow for comparison and analysis of the project effectiveness. Then, the variation pattern of this index, after an improvement project, has been investigated. Finally, Taguchi's loss functions are used to evaluate the effectiveness of these projects.

The results represent a significant improvement in the production process and a reduction in production costs regarding both weld quality and pipe circumstances. Due to the successful implementation of Six Sigma project in welding and pipe quality improvement, the Define, Measure, Analyze, Improve and Control (DMAIC) method can be used effectively in defining weld and pipe quality.

In this proposed work, for the first time, research on the implementation of Six Sigma in the pipeline and welding industries on two online spiral production machines has been investigated. The DMAIC method has been used for the first time to improve the dimensional quality and weld quality of spiral pipes.

The drill string vibrations can create harmful effects on drilling performance because they generate the stick-slip phenomenon which reduces the quality of drilling and decreases the penetration rate and may affect the robustness of the designed controller. For this reason, it is necessary to carefully test the different rock-bit contact models and analyze their influences on system stability in order to mitigate the vibrations. The purpose of this paper is to investigate the effects of rock-bit interaction on high-frequency stick-slip vibration severity in rotary drilling systems.

The main objective of this study is an overview of the influence of the rock-bit interaction models on the bit dynamics. A total of three models have been considered, and the drilling parameters have been varied in order to study the reliability of the models. Moreover, a comparison between these models has allowed the determination of the most reliable function for stick-slip phenomenon.

The torsional model with three degrees of freedom has been considered in order to highlight the effectiveness of the comparative study. Based on the obtained results, it has been concluded that the rock-bit interaction model has big influences on the response of the rotary drilling system. Therefore, it is recommended to consider the results of this study in order to design and implement a robust control system to mitigate harmful vibrations; the practical implementation of this model can be advantageous in designing a smart rotary drilling system.

Many rock-bit functions have been proposed in the literature, but no study has been dedicated to compare them; this is the main contribution of this study. Moreover, a case study of harmonic torsional vibrations analysis has been carried out in well-A, which is located in an Algerian hydrocarbons field, the indices of vibrations detection are given with their preventions.

While efficient design in engineering projects is crucial, this paper aims to examine the integration of Building Information Modeling (BIM) into railway Intelligent Transportation Systems (ITS). The paper provides some key understanding of integrating BIM and ITS to improve the efficiency of railway infrastructure projects.

An in-depth qualitative analysis of three ITS case studies was conducted to understand BIM’s global impact and benefits in railway infrastructure projects. While case study one investigated the Crossrail (UK), the other two case studies were TUC Rail (Belgium) and the Intercity railway network (Norway).

The findings include the specific benefits of BIM, regarding the railway infrastructure. The result indicated that BIM benefits were consistently the same across all case studies. Although Case study 1 was the only one that boasts a high reduction in waste and reworks, all of the case studies showed less rework and delays due to BIM. The results indicated that the advantages of BIM for such projects are cost optimization, reduction in waste, rework and lessening delays. Subsequently, this leads to the ease and efficiency with which structures and railways can be built. The outcomes can ultimately assist transportation planners in better planning and managing railway projects.

This study proposes the integration of BIM into railway projects as a part of their ITS. The BIM integration into railway projects as a part of their ITS fits within the overall planning to handover phases. Specifically, the BIM integration improves the design process of typical railway projects. Thus, the most significant advantage of BIM for railway projects is to further improve their design process leading to a higher degree of constructability.

Railway infrastructure performs a major role in economic and regional development. The complexity of railway projects continues to increase as the need for more railway infrastructure is on the rise globally. BIM is proving to be an effective tool for improving the efficiency of railway infrastructure projects. As the utilization of BIM is intensifying, the railway industry can further exploit BIM to improve project delivery adeptness by offering greater collaboration leading to efficient design processes. As a result, the understanding of BIM for horizontal projects such as railway infrastructure on a global scale is a substantial exercise that this research aims to respond to.

In successfully meeting city and metropolitan growth, sustainable development is compulsory. Sustainability is a must-focus for any project, particularly for large and mega rail infrastructure. This paper aims to investigate to what degree social, environmental and economic factors influence the government when planning sustainable rail infrastructure projects. To respond to such a matter, this paper focuses on two Australian mega-rail projects: the South West Rail Link (SWRL) and the Mernda Rail Extension (MRE).

As the basis of an experimental evaluation framework strengths, weaknesses, opportunities and threats (SWOT) and factor analysis were used. These two methods were specifically selected as comparative tools for SWRL and SWRL projects, to measure their overall sustainability effect.

Using factor analysis, in the MRE, the factors of network capacity, accessibility, employment and urban planning were seen frequently throughout the case study. However, politics and economic growth had lower frequencies throughout this case study. This difference between the high-weighted factors is likely a key element that determined the SWRL to be more sustainable than the MRE. The SWOT analysis showed the strengths the MRE had over the SWRL such as resource use and waste management, and natural habitat preservation. These two analyses have shown that overall, calculating the sustainability levels of a project can be subjective, based on the conditions surrounding various analysis techniques.

This paper first introduces SWRL and MRE projects followed by a discussion about their overall sustainable development. Both projects go beyond the traditional megaprojects' goal of improving economic growth by developing and enhancing infrastructure. Globally, for such projects, sustainability measures are now considered alongside the goal of economic growth. Second, SWOT and factor analysis are undertaken to further evaluate the complexity of such projects. This includes their overall sustainable development vision alignment with environmental, economic and social factors.

The growing popularity of the use of cellular steel beams in composite floors comes at the same time as an increasing attention to the fire safety engineering design. The recommendation for their design in fire limit states remains very primitive and this is due to the lack of general research in this area. Four composite cellular steel beams were tested at the University of Ulster with two models of different steel geometries and loading conditions under monotonic loading and at elevated temperatures. This paper presents a finite element model and simple hand calculation methods to calculate the shear buckling at the web post, the bending resistance in fire, deflection and temperature distribution in the cross section of composite cellular beams.