Cracks are pathologies whose appearance in ceramic tiles can cause various damages due to the coating system losing water tightness and impermeability functions. Besides, the detachment of a ceramic plate, exposing the building structure, can still reach people who move around the building. Manual inspection is the most common method for addressing this problem. However, it depends on the knowledge and experience of those who perform the analysis and demands a long time and a high cost to map the entire area. This work focuses on automated optical inspection to find faults in ceramic tiles performing the segmentation of cracks in ceramic images using deep learning to segment these defects. We propose an architecture for segmenting cracks in facades with Deep Learning that includes an image pre-processing step. We also propose the Ceramic Crack Database, a set of images to segment defects in ceramic tiles. The proposed model can adequately identify the crack even when it is close to or within the grout.

Purpose: The purpose of this paper is to present a case study about the diagnosis perform of the building maintenance process in a Brazilian Government public institution. Design/methodology/approach: The research methodology involved interviews, maintenance process diagnosis and request database analysis. Findings: The results showed that the average attendance rate of the received requests is 86 percent and the greatest demands are related to the refrigeration, electrical and hydrosanitary installations, which represent 55 percent of the total requests. According to maintenance management, it was verified the need for a better structuring of the requests receiving system and greater rigor to the services quality. Originality/value: The paper extends the knowledge relating to the building maintenance process in government public institutions. The government building maintenance management characterization can serve as reference and benchmark for similar institutions.

Resumo O mundo passa por uma revolução de ordem abrangente, destacando-se a demanda por inserção tecnológica nos processos industriais, notadamente pela necessidade da otimização do tempo. Em especial, os veículos aéreos não tripulados (VANT), ou “drones”, estão tendo crescente relevância como novo mecanismo de obtenção de dados e inspeções visuais, mais ágeis e seguros. Este artigo teve o objetivo de realizar o estudo experimental do uso de VANT como ferramenta visual para inspeção de manifestações patológicas em fachadas de edifícios. A metodologia contemplou a realização de dois estudos de caso em edificações de mediana e grande altura, em que foram contempladas as etapas de coleta de imagens e processamento. Os resultados da pesquisa exibiram a viabilidade técnica e a eficácia da inspeção, e mostraram que entre os ativos visuais produzidos as fotografias digitais geradas pela aeronave foram mais efetivas para a detecção de manifestações patológicas quando comparadas com os modelos gerados pelo software Agisoft PhotoScan. Como principal contribuição, têm-se a validação do pacote tecnológico destinado a auxiliar no diagnóstico de manifestações patológicas a partir da formulação do protocolo para a inspeção de fachadas com uso de VANT e a análise comparativa dos ativos visuais que podem ser gerados.

Purpose: The purpose of this paper is to establish and evaluate the concrete loss and labor productivity (LP) indicators in the concreting step of aluminum formwork system (AFS) in construction in Brazil. The loss and productivity indicators are directed to a regional database (Pernambuco, Brazil). Design/methodology/approach: Case study was selected as the most appropriate approach. The methodology included data collection in the construction project with 10 residential towers of 320 apartments, in the city of Jaboatão dos Guararapes, Brazil, throughout 82 concrete pouring days using 415 concrete mixer trucks, with a total of 2,582.50 m³ of concrete. Findings: The findings identified an average concrete loss of 2.6 percent and the LP indicator varying between 0.15 and 0.97 WH/m³. It could be verified that the loss indicators were influenced mainly by the learning effect associated to the qualification of the labor. In addition, the productivity indicators were strongly influenced by delays at the beginning of the concrete pouring and by problems coming from the sequence of concrete supply. Originality/value: LP indicators are still literature restricted, especially considering only the concreting step. The direct observations of this study allow the identification of factors that inhibit productivity. The comparison of indicators for the concreting service between the ASF and the conventional system attests to the speed, low cost and efficiency of the system studied in this paper.

Resumo Va fase de diagnóstico das manifestações patológicas em fachadas, a etapa de inspeção visual merece destacada atenção em virtude da inerente complexidade (altura, tamanho, dificuldades de acesso e condições de exposição). Nos últimos anos, o uso de técnicas de deep learning para detectar e classificar características específicas em imagens e vídeos vem crescendo cada vez mais e, quando combinado com o uso de veículos aéreos não tripulados (VANT) para a captura de imagens, constitui uma ferramenta que pode auxiliar e automatizar o procedimento de inspeção visual de fachadas. Este artigo teve o objetivo de realizar a análise do processamento digital de imagens para detecção automática de fissuras em revestimentos cerâmicos de edifícios, associada ao VANT ou drone, o que, potencialmente, resultaria em benefícios (prazo, custo e segurança) no que diz respeito ao diagnóstico. Assim, os resultados da pesquisa exibiram a viabilidade técnica da detecção de fissuras por técnicas de PDI. O procedimento é considerado um trabalho complexo quando há elevada variação nas imagens de estudo. No entanto, mesmo diante de um cenário limitante como a falta de datasets públicos para o problema, o projeto conseguiu desenvolver uma metodologia simples e eficiente para o tema para o qual foi proposto.

This article presents an evaluation of the influence on the natural carbonation process of the use of granite cutting residue as a replacement for fine aggregate in mortars. The methodology adopted consisted of replacing the fine aggregate with granite cutting residue, analysing the carbonation depth with the aid of an experimental planning matrix of 2³ + 3 repetitions at the central point. The influence of the exposure time, the percentage of residue in the mixture, and the particle size of the residue used were evaluated. The exposure time variable was found to have the greatest influence on the carbonation process. Under the conditions analysed, granite residue was found to be beneficial, reducing the carbonation depth.