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The purpose of this paper is to identify the key aspects of building defects performance cases in relation to the building components focusing on the government-owned buildings and to enhance government’s role to curb the building defects to reoccur.

The qualitative research method approach was adopted with a total of 5,243 specific building defects identified and accumulated from actual building projects and provided feedback on the defects associated with the Government of Malaysia’s owned buildings.

This paper statistically validates that building defects are a staid delinquent matter fronting the construction industry in Malaysia. This matter needs to be tacked by all the parties involved in the industry. This paper proposes a factual statistical statement that is proved to be a practical and suitable measurement in correcting building defects and preventing them from reoccurring.

Future research could focus on developing a defect performance measurement on real projects now focusing on private buildings as well.

The defects performance statistical measurement is anticipated to prove the problematic rate of defects occurrence on government-owned structures, as the key elements on the national defect preventive strategy which have to be taken into account.

The outcome of this paper is significant in its own right and serves as a platform for future research in this area.

Building defects are becoming recurrent phenomena in most high-rise buildings. However, little research exists on the analysis of defects in high-rise buildings based on data from real-life projects. This study aims to develop dashboards and models for revealing the most common locations of defects, understanding associations among defects and predicting the rectification periods.

In total, 15,484 defect reports comprising qualitative and quantitative data were obtained from a company that provides consulting services for the construction industry in Victoria, Australia. Data mining methods were applied using a wide range of Python libraries including NumPy, Pandas, Natural Language Toolkit, SpaCy and Regular Expression, alongside association rule mining (ARM) and simulations.

Findings reveal that defects in multi-storey buildings often occur on lower levels, rather than on higher levels. Joinery defects were found to be the most recurrent problem on ground floors. The ARM outcomes show that the occurrence of one type of defect can be taken as an indication for the existence of other types of defects. For instance, in laundry, the chance of occurrence of plumbing and joinery defects, where paint defects are observed, is 88%. The stochastic model built for door defects showed that there is a 60% chance that defects on doors can be rectified within 60 days.

The dashboards provide original insight and novel ideas regarding the frequency of defects in various positions in multi-storey buildings. The stochastic models can provide a reliable point of reference for property managers, occupants and sub-contractors for taking measures to avoid reoccurring defects; so too, findings provide estimations of possible rectification periods for various types of defects.

Quality failures in the design and construction process can entail significant delays and costs. Databases of building defects have proven to be useful for drawing conclusions on underlying causes of building defects and for identifying potential improvement actions to reduce the occurrence of building defects.

The database comprising 27,074 cases from a Belgian insurance company was studied, and it was found that moisture problems account for 48% of all building defects, and stability problems 23%. To better analyse the geographical variability, the data were enriched with demographical, geographical and climatological factors of the municipality the concerned buildings were located in. This combined information was used to determine underlying external factors that impact the probability that specific types of building defects occur.

The analysis of the data shows that external factors do indeed have a statistically significant impact. The factor with the highest impact is the number of walls the building has in common with its neighbours. The most significant climatological factor is the wind speed.

A better understanding of the frequency of building defects and factors that contribute to the likelihood are important variables to consider in quality control and prevention.

Most residential building owners often report problems associated with the plumbing systems. If identified at the early stages, plumbing-related defects can be easily repaired. However, if unnoticed for a long period of time, they could lead to major damages and incur a significant cost to repair. Despite the problems, studies investigating plumbing anomalies and their root causes in residential buildings are limited. This study aims to explore plumbing defects and their potential causes, diagnosis methods and repair techniques in residential buildings.

This research used data collected through an extensive survey of both academic and grey literature. Through the content analysis, plumbing defects and the associated causes have been identified and presented in tabular format.

The study investigated the anomalies and causes in the residential plumbing system under five key sub-systems: water supply system; sanitary plumbing system; roof drainage system; heating, ventilation, air conditioning and gas system; and swimming pool. Accordingly, some of the identified plumbing defects include leakages, corrosion, water penetration, slow drainage and cracks. Damaged pipes, faulty equipment and installations are some of the common causes of the anomalies. Visual inspection, hydrostatic pressure test, thermography, high-tech pipe cameras, infrared cameras, leak noise correlators and leak loggers are techniques used for diagnosing anomalies. Reactive, preventive, predictive and reliability-centred maintenance strategies are identified to control or prevent anomalies.

The findings of this research can be used as a useful tool or guideline for contractors, plumbers, facilities managers and building surveyors to identify and rectify plumbing system-related defects in residential buildings.

This paper aims to use convolutional neural networks (CNNs) to provide an objective approach to classify deteriorated building assets according to the type and extent of damage. This research supports automated inspection of buildings and focuses on roofing elements as one of the most critical and externally distressed elements in buildings.

In this paper, 5,000+ images of deteriorated roofs from several buildings were collected to design a CNN system that automatically identifies and sizes roofing defects. Experimenting with different CNN formulations, the best accuracy is achieved using two-stage CNNs. The first-stage CNN classifies images into defect/no defect, while the second stage classifies the defected images according to the damage type. Based on the image classification, optimization is used to prioritize roof repairs by maximizing the return from limited rehabilitation funds.

The developed CNNs reached 95% and 97% accuracy for the first and second phases, respectively, which is higher than achieved in previous literature efforts. Using the proposed model to automate inspection and condition assessment activities proved to be faster than conventional methods. Repair/replace strategy for a case study of 21 campus buildings based on their condition and budgetary constraints was suggested.

Future research includes testing different data acquisition technologies (e.g. infrared imaging), performing severity-based classification and integrating with BIM for defect localization.

This study provides an objective approach to automate asset condition assessment and improve funding decisions using a combination of image analysis and optimization techniques. The proposed approach is applicable toward other asset types and components.

The purpose of this study is to examine, review and analyse the current literature on building and construction quality and determine the related themes and gaps.

A systematic review approach was adopted on the building quality literature, and keywords such as “construction” or “building”; “defect” and “quality” or “rework” were searched through the Scopus, Web of Science and Google Scholar databases. A number of articles were found and filtered by title, abstract and keyword relevancy. Further articles were cross-referenced from these and again filtered by title, abstract and keyword relevancy. The time period for the search was 2000–2020. A total of 97 articles were found and analysed on the topic.

A number of recurring themes were found throughout the literature. They are safety, occupier satisfaction, cost, time, licensing, culture, training, software and building quality frameworks, classifications and recommendations. These themes were linked to display relationships between them from the literature. Based on the project lifecycle stages, an amalgamated classification system was developed and is presented here. The gaps in the current literature have been analysed and reported on.

A comprehensive descriptive, thematic and gap analysis was conducted on the available literature of building and construction quality. The emerging themes were discovered, their relationships were demonstrated and the research gaps were identified. A new classification system positioned in the project lifecycle stages is presented.

Construction defects in residential buildings are causing significant impacts both on consumers and the industry. As a consequence, several countries have established new home warranty schemes. However, designing a public policy for domestic building warranties can become a difficult task. In fact, many of these programs in the past have failed, collapsed or gone bankrupt. Therefore, the purpose of the current research is to provide a systematic comparative representation of various active programs internationally.

The methodology relied on a multiple-case study research design. The case selection covered a total of nine jurisdictions with compulsory home warranty programs. Those included Japan, France, United Kingdom, three provinces in Canada (Ontario, British Columbia and Alberta), and three states in Australia (New South Wales, Victoria and Queensland). The study applied a data collection protocol to gather all the evidence in a replicable manner for each individual case. Subsequently, a cross-case analysis was conducted to identify similarities and variations between programs.

The findings unveiled institutional practices that aimed to resolve, compensate, or rectify defects in residential constructions within these countries. The review mostly suggested that every home warranty program presents certain unique characteristics. At the end, this paper proposed an analytical illustration representing the diversification of components adopted by each jurisdiction.

Nowadays, there is still not a consensus within the academic community on what is an optimal solution when conceiving a new home warranty program. Hence, the current study aims to fill this knowledge gap by presenting the plurality of methods employed by several countries. This paper seeks to help policy makers and industry leaders to improve their home warranty scheme based on awareness derived from observations and analyses of what has been accomplished elsewhere in the world.

Operation and maintenance (O&M) processes projects such as identification, assessment, planning and execution, embody a variety of standards such as technical (method of statement), environmental, economic (campus development) and social (health and wellbeing). Because these standards have proven to be challenging to integrate, local governments are increasingly experimenting with social innovation (SI) as a bottom-up form of standard integration. This study aims to apply the concept of SI to the O&M processes of facilities management at polytechnics in Malaysia to identify problems with conventional working practices in this area and to recommend potential solutions.

The paper reviews evidence that conventional working methods generate significant problems related to paper-based forms, improper database management and flawed decision-making processes. Because of the lack knowledge about different ways of how standard integration is achieved, the comparison of three polytechnic institutions which are Rensselaer Polytechnic Institute (RPI) and Southern Polytechnic College of Engineering and Engineering Technology (SPCEET) in USA as well as Seberang Perai Polytechnic, Pulau Pinang (PSP) in Malaysia shares the ambition to realise standard integration of O&M through SI.

The findings reveal that SI leads to four ways of standard integration: computerised maintenance management system, online customer complaint, electronic form and relational database. Application of the concept of SI reveals the need for more sophisticated management solutions in the O&M processes of facilities management.

These standard integration arrangements unfortunately seem to mainly contribute to greater alignment between standard rather than true standard integration. The concept of SI will guide future improvements and developments in maintenance management systems to fulfil requirements in this area.

Defects in concrete surfaces are inevitably recurring during construction, which needs to be checked and accepted during construction and completion. Traditional manual inspection of surface defects requires inspectors to judge, evaluate and make decisions, which requires sufficient experience and is time-consuming and labor-intensive, and the expertise cannot be effectively preserved and transferred. In addition, the evaluation standards of different inspectors are not identical, which may lead to cause discrepancies in inspection results. Although computer vision can achieve defect recognition, there is a gap between the low-level semantics acquired by computer vision and the high-level semantics that humans understand from images. Therefore, computer vision and ontology are combined to achieve intelligent evaluation and decision-making and to bridge the above gap.

Combining ontology and computer vision, this paper establishes an evaluation and decision-making framework for concrete surface quality. By establishing concrete surface quality ontology model and defect identification quantification model, ontology reasoning technology is used to realize concrete surface quality evaluation and decision-making.

Computer vision can identify and quantify defects, obtain low-level image semantics, and ontology can structurally express expert knowledge in the field of defects. This proposed framework can automatically identify and quantify defects, and infer the causes, responsibility, severity and repair methods of defects. Through case analysis of various scenarios, the proposed evaluation and decision-making framework is feasible.

This paper establishes an evaluation and decision-making framework for concrete surface quality, so as to improve the standardization and intelligence of surface defect inspection and potentially provide reusable knowledge for inspecting concrete surface quality. The research results in this paper can be used to detect the concrete surface quality, reduce the subjectivity of evaluation and improve the inspection efficiency. In addition, the proposed framework enriches the application scenarios of ontology and computer vision, and to a certain extent bridges the gap between the image features extracted by computer vision and the information that people obtain from images.

This research proposes the study of the pathology in floor finishes, focussing on proactive maintenance strategies to promote the durability of these elements. A model to assess the floorings' performance levels was designed to support decision-making regarding maintenance activities to be carried out, in order to prevent the defects and extend the floors' service life.

The model to measure the floorings' level of performance was developed based on the literature and applied in fieldwork, focussed on visual inspections of floor finishes. Photographs were taken and standardized inspection forms were used to collect the data about the defects in the floors.

This study provides a simple classification model to assess floorings' performance levels, capable to define priorities and help decision-makers in adopting maintenance activities. The model was validated through a case study, which showed that occasionally the choice of the floor finishes is incorrectly made only based on aesthetic criteria and not taking into account the main criteria, i.e. the use of space.

This work contributes to a development of methodologies to assess floorings' performance levels, to study the behavior of different floor finishes, to propose maintenance strategies to improve their performance in service and adopt better solutions in the buildings' design phase.