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Design for maintainability (DfM) is a construction technique that links maintenance objectives with the design process. Adopting DfM within the construction industry is a solution that can make the maintenance of buildings cost-efficient and simpler. This study investigates the level of implementation of DfM among design professionals in the Ghanaian construction industry (GCI).

The data from design professionals comprising architects and civil/structural engineers were collected via a questionnaire survey. The data obtained were analyzed using descriptive and inferential statistical tests.

The findings revealed a high level of engagement of design professionals in DfM practices in the Ghanaian construction sector. This high level of engagement is credited to the high level of awareness of the concept of DfM among design professionals, the level of education of design professionals, experience in professional roles and familiarity with the principles of DfM.

This study offers information and fresh perspectives on how cutting-edge DfM principles are practiced in the GCI. The study raises awareness and the level of DfM implementation among design professionals in the GCI. It offers information on how the application of DfM principles enhances cost-effective maintenance that allows facilities to stand the test of time and prove more relevant for users. The understanding and application of DfM in different countries are important if such concepts are to take deep root in the global built environment sector.

Resilience as a novel concept has attracted the most attention in the management of engineering systems. The main goal of engineering systems is production assurance and increasing customer satisfaction which depends on the suitable performance of mechanical equipment. “A resilient system is defined as a system that is resistant to disruption and failures and can recover itself and returns to the state before failure as soon as possible in the case of failure.” Estimate the value of the system’s resilience to increase its resilience by covering the weakness in the resilience indexes of the system.

In this article, a suitable approach to estimating resilience in complex engineering systems management in the field of mining has been presented. Accordingly, indexes of reliability, maintainability, supportability, efficiency index of prognostics and health management of the system, and ultimately the organization resilience index, have been used to evaluate the system resilience.

The results of applying this approach indicate the value of 80% resilience if the risk factor is considered and 98% if the mentioned factors are ignored. Also, the value of 58% resilience of this organization’s management group indicates the weakness of situational awareness and weakness in the vulnerable points of the organization.

To evaluate the resilience in this article, five indicators of reliability, maintainability, and supportability are used as performance indicators. Also, organization resilience and the prognostic and health management of the system (PHM) are used as management indicators. To achieve more favorable results, the environmental and operational variables governing the system have been used in performance indicators, and expert experts' opinions have been used in management indicators.

The application of circular building adaptability (CBA) in adaptive reuse becomes an effective action for resource efficiency, long-lasting usability of the built environment and the sped-up transition to a circular economy (CE). This paper aims to explore to which extent CBA-related strategies are applied in adaptive reuse projects, considering enablers and obstacles.

A stepwise theory-practice-oriented approach was followed. Multiple-case studies of five circular adaptive reuse projects in The Netherlands were investigated, using archival research and in-depth interviews. A cross-case analysis of the findings was deductively conducted, to find and replicate common patterns.

The study revealed that configuration flexibility, product dismantlability and material reversibility were applied across the case studies, whereas functional convertibility and building maintainability were less applied. Low cost of material reuse, collaboration among team members and organisational motivation were frequently observed enabling factors. Lack of information, technical complexities, lack of circularity expertise and infeasibility of innovative circular solutions were frequently observed obstacles to applying CBA.

This paper provides practitioners with a set of CBA strategies that have been applied in the real world, facilitating the application of CBA in future adaptive reuse projects. Moreover, this set of strategies provides policymakers with tools for developing supportive regulations or amending existing regulations for facilitating CE through adaptive reuse.

This study provides empirical evidence on the application of CBA in different real-life contexts. It provides scholars and practitioners with a starting point for further developing guiding or decision-making tools for CBA in adaptive reuse.

This study aims to address the critical issue of machine breakdowns in industrial settings, which jeopardize operation economy, worker safety, productivity and environmental compliance. It explores the efficacy of a predictive maintenance program in mitigating these risks by proactively identifying and minimizing failures, thereby optimizing maintenance activities for higher efficiency.

The article implements Logical Analysis of Data (LAD) as a predictive maintenance approach on an industrial machine maintenance dataset. The aim is to (1) detect failure presence and (2) determine specific failure modes. Data resampling is applied to address asymmetrical class distribution.

LAD demonstrates its interpretability by extracting patterns facilitating the failure diagnosis. Results indicate that, in the first case study, LAD exhibits a high recall value for failure records within a balanced dataset. In the second case study involving smaller-scale datasets, enhancement across all evaluation metrics is observed when data is balanced and remains robust in the presence of imbalance, albeit with nuanced differences in between.

This research highlights the importance of transparency in predictive maintenance programs. The research shows the effectiveness of LAD in detecting failures and identifying specific failure modes from diagnostic sensor data. This maintenance strategy exhibits its distinction by offering explainable failure patterns for maintenance teams. The patterns facilitate the failure cause-effect analysis and serve as the core for failure prediction. Hence, this program has the potential to enhance machine reliability, availability and maintainability in industrial environments.

A novel facet of the construction industry's (CI) digital transformation relates to the rise of smart contracts, and the contribution of blockchain technology in this domain appears to be nascent but rapidly gaining traction. Although the benefits of digitalisation for technologically less enthusiastic CI are irrefutable, the adoption of smart contracts has been found to be low pertaining to industry professionals' behavioural factors stimulated by technological perception. The challenge undertook by this study, therefore, is to develop a knowledge framework for blockchain-enabled smart contract adoption in the CI.

From a methodological perspective, this study employed a qualitative approach that involved semi-structured interviews with ten (10) highly experienced CI practitioners involved in digital innovations for data collection. Directed content analysis was performed using NVivo 12 software, which enabled the creation of preliminary open codes. Subsequently, these open codes were grouped into similar categories to develop axial codes. Finally, the study presented final themes along with their corresponding descriptions.

Notably, research findings expanded the current body of knowledge on perceived attributes and their measurement items to determine the perception of innovation adoption in CI, where a total of nine (9) perceived attributes were associated with thirty-two (32) measurement items.

The measurement items were seen as having an extensive impact on the CI professionals' decision to adopt blockchain-enabled smart contracts. With ensuing implications, this study represents one of the first to present a knowledge framework exclusively customised for blockchain-enabled smart contracts, laying the groundwork for effective technological adoption by CI professionals.

The slow adoption of unmanned aerial vehicles (UAVs) in the construction industry, particularly in developing countries like Nigeria, underscores the need for a deeper understanding of the critical factors influencing their adoption. This study aims to identify these factors using the Technology-Organization-Environment (TOE) framework and address uncertainties in their prioritization through Fuzzy Synthetic Evaluation (FSE). The utility of this approach lies in its ability to provide construction organizations with actionable insights to enhance operational efficiency and competitiveness through effective UAV adoption.

A post-positivist philosophical stance was adopted, wherein quantitative data were gathered from construction professionals in Nigeria via a questionnaire survey. The collected data were analyzed using the Cronbach alpha test as a measure of internal consistency and the FSE test to synthesize critical drivers for the adoption of UAVs.

The study found that drivers related to technology and organization are the most critical drivers. This implies that variables related to technology and organization warrant a higher level of focus if UAVs are to continue gaining popularity within the construction industry. Additionally, this study identified that logistic management, construction monitoring and site surveying represent the most critical areas of UAV application within the construction industry.

The emphasis on technology and organizational drivers as critical factors suggests that construction companies should prioritize investments in technology infrastructure and cultivate an organizational culture that embraces innovation. This may involve providing training to construction professionals to enhance their technological skills and fostering a leadership culture that champions technology adoption.

This study introduces novelty by applying the TOE framework, which has received limited attention in UAV adoption studies within construction. Additionally, the use of FSE addresses uncertainties in prioritizing critical drivers, particularly relevant in developing countries facing unique technological challenges. By assigning priority to these factors, this research lays the groundwork for a more informed and strategic approach to UAV adoption.

The Internet of Things (IoT) cloud platforms provide end-to-end solutions that integrate various capabilities such as application development, device and connectivity management, data storage, data analysis and data visualization. The high use of these platforms results in their huge availability provided by different capabilities. Therefore, choosing the optimal IoT cloud platform to develop IoT applications successfully has become crucial. The key purpose of the present study is to implement a hybrid multi-attribute decision-making approach (MADM) to evaluate and select IoT cloud platforms.

The optimal selection of the IoT cloud platforms seems to be dependent on multiple attributes. Hence, the optimal selection of IoT cloud platforms problem is modeled as a MADM problem, and a hybrid approach named neutrosophic fuzzy set-Euclidean taxicab distance-based approach (NFS-ETDBA) is implemented to solve the same. NFS-ETDBA works on the calculation of assessment score for each alternative, i.e. IoT cloud platforms, by combining two different measures: Euclidean and taxicab distance.

A case study to illustrate the working of the proposed NFS-ETDBA for optimal selection of IoT cloud platforms is given. The results obtained on the basis of calculated assessment scores depict that “Azure IoT suite” is the most preferable IoT cloud platform, whereas “Salesman IoT cloud” is the least preferable.

The proposed NFS-ETDBA methodology for the IoT cloud platform selection is implemented for the first time in this field. ETDBA is highly capable of handling the large number of alternatives and the selection attributes involved in any decision-making process. Further, the use of fuzzy set theory (FST) makes it very easy to handle the impreciseness that may occur during the data collection through a questionnaire from a group of experts.

This paper aims to develop and validate a strategy for reducing construction waste (CW) generated during the design process (DP) in architectural design firms (ADFs) in Egypt.

Qualitative and quantitative research methodology was designed to accomplish four objectives. The literature review investigated DP, CW, waste management (WM) and WM strategies (WMS). Three case studies were analysed to investigate the role of WMS towards reducing CW during DP. A survey questionnaire was conducted with a representative sample of ADFs in Egypt to assess their perception and application of WMS during DP. Lastly, a strategy was developed and validated to reduce CW generated during DP.

Through literature review, the research identified the highest 40 causes of CW during the DP and classified them into 13 categories. Despite early promotion of WMS to reduce CW at its source, Egypt and other countries with similar construction market characteristics lack laws and regulations to address CW during the DP, with current codes primarily focusing on post-occurrence issues. In addition, analysis of three case studies showed that CW was reduced by adopting WMS during the DP. Findings of data analysis revealed that ADFs have an average knowledge of WMS and a low awareness of Egyptian laws and WMS during DP. “Prefabrication” was the highest-ranked strategy for CW reduction during DP. Several challenges hamper the implementation of WMS. The “preparation and briefing” was ranked the most common design stage where CW causes occur, while “waiting” was ranked the most common form of CW. These findings informed the research outcome and helped in the development of the proposed strategy.

The proposed strategy was developed taking into account the results of the survey questionnaire which was conducted in ADFs in Egypt where the authors reside, and such a strategy is needed. However, it could be applied in other countries that share the same characteristics of the architectural DP as well as the causes of CW and WMS implementation challenges.

This research presents a practical strategy to reduce CW generated during the DP. It was based on the findings of literature review, case studies and survey questionnaire. The strategy was explained in a workable way to include the required activities; tools and techniques; involved personnel and needed resources. The strategy was validated by a representative sample of ADFs in Egypt to ensure its practicability and viability for implementation towards developing a sustainable built environment. The practical application of the strategy will have long-term and short-term benefits. The long-term benefits include improving the social, economic and environmental aspects of sustainability during the design and construction phases in Egypt. In the short term, application of the strategy will improve the cooperation between design and construction teams, reduce the negative impact of CW production and enhance the quality of construction projects in Egypt.

Despite the need to reduce CW during DP, a practical strategy is lacking in Egypt, where laws are focused on dealing with CW after its existence. This research studied a topic that received scant attention in construction literature. It developed and validated a strategy to reduce CW during DP, which represents a synthesis that is novel and creative in thought and adds value in a manner that has not been previously explored.

This paper aims to analyze the impact of sustainability measures taken during the design and construction phases, by examining two categories of sustainability: energy efficiency and reducing carbon emissions and material selection and waste management. These aspects are examined from the perspectives of long-term building performance and maintenance practices, as well as user/tenant satisfaction.

This study includes a literature review related to the two topics under consideration, followed by a comparative case study analysis of four projects to determine practical validity. All case studies in this paper used a semi-structured survey with various project stakeholders, which helped the authors identify measures taken as well as obstacles and challenges during the process.

According to the four case studies, adequate attention should be paid to the two areas of interest during a project’s design and construction phases. Including case studies from around the world (four case studies from three different countries) offers insights into effective sustainability practices in building design and construction, providing instances of successful implementation and emphasizing the obstacles and potential when incorporating sustainability into the design and construction phases.

The findings also show that design and construction participants and companies should reduce waste generation and carbon emissions. In addition, they should make decisions on material selection to enhance projects’ sustainability and to contribute to creating a habitable planet for the future.

The influence of the design and construction phases on long-term project sustainability is of major importance and concern to users, owners, designers, contractors and facility managers. This study illustrates the necessity of including sustainability measures in the design and construction phases, highlighting the importance of sustainability in building design and construction through effective implementation techniques and interdisciplinary teamwork to realize sustainable goals.

Engineering knowledge continuity is crucial for the life cycle management of long-lived and complex assets, such as nuclear plants, locks and storm surge barriers. At the storm surge barriers in the Netherlands, engineering knowledge continuity is not yet fully assured, despite long-standing efforts. This study aims to explore the relationship between system characteristics, the organizational demarcation of maintenance and operation and the challenges in achieving engineering knowledge continuity and provides suggestions for improvement of theory and policy.

Ten semi-structured interviews were conducted with professionals from various backgrounds in construction, engineering and asset management of the Dutch storm surge barriers, augmented with visits to barriers and barrier teams. A thematic analysis was used to identify and describe the challenges to engineering continuity, their origins and potential solutions. We reviewed knowledge management policy documents and asset management consultancy reports to validate the findings. Additionally, we engaged in frequent interactions with professionals at the barriers. We achieved saturation and validation once no new issues were raised during these discussions.

The thematic analysis developed multiple themes describing the challenges to engineering continuity, their origins and potential solutions. The key findings are that expert engineers are critically important to deal with redesigns induced by obsolescence. Moreover, due to barrier uniqueness, long redesign cycles and reliability requirements, conventional knowledge continuity tools are insufficient to enable new engineers to reach expert level. Finally, the thematic analysis shows that, in some cases, outsourcing should be reduced to facilitate internal learning.

The study introduces the application of the knowledge-based view of the firm and the concept of requisite knowledge redundancy to the long-term management of complex assets. It calls for more attention to long gaps in the use of unique knowledge and the effect on knowledge continuity.