Impacts of Industrial Cyber‐Physical Systems on the Building Trades

This chapter provides a non-exhaustive picture of the opportunities, experiences and transformations that have taken place over the last 10 years. Many of these have been, and increasingly will be, supported by the emergence of “new” technologies originally developed for the manufacturing sector. The chapter presents an example of an industrial cyber-physical systems (ICPS) prototype under construction. Following in the footsteps of the major groups, and in order to finally change the paradigm, the construction sector is stepping up its efforts and attempting to embark on the digital path. The best example of this is the digital mock-up and more specifically building information modeling. ICPS can be the source of important transformations in the construction sector. Several examples of the use of technologies and principles are detailed, according to the four functions of an ICPS, i.e. control, learn and interact, sense and distribute information, and digitalize

Recreating historical Malay architecture with BIM process

In South-East Asia, the Malay architecture is among the popular subject of research because of its historical importance within the region, apart from many others. To some researchers, the Malay architecture is unique because of its intangible meaning and historically rich design characters. It is difficult to be reproduced, and only limited numbers of people are acknowledged as experts. With the introduction of technology such as BIM, it is hypothesized that the gap can be minimized. The idea of this paper is to outline the process of recreating cultural architectural design using a modern process such as Building Information Modelling (BIM) platform in specific, from data collection using Terrestrial Laser Scanning (TLS) and digitalization process in Revit software. This paper employs observation approach using data from laser scanner collected from case study and content analysis technique. While normally most of the cultural architecture is undocumented, the findings of this activity are aimed to provide guideline to develop geometrical information for heritage-enthusiast in practicing their undertakings. It is hoped that more historical and cultural architecture can be recreated and appreciated for the use and inspiration of current construction industry

A Knowledge-driven Method for 3D Reconstruction of Technical Installations in Building Rehabilitations

Rehabilitation of buildings often requires analysing the scene and measuring the dimension of different elements. Normally this task is done by visiting the real scene. In many cases, the planes are lost or unavailable, so the area must be measured again. Building a 3D model of the scene enables to work remotely. The scene is captured using a 3D laser scanner, which creates a point cloud. Applying a segmentation method to the point cloud, the features of the data can be extracted. In this thesis a method for processing the point cloud data obtaining the information of each wall and pipe is developed. The point cloud is cleaned of unnecessary points and segmented applying different segmentation methods. Region growing algorithm and RANSAC algorithms are combined for an accurate detection of pipes and planes. Once the features of each element are detected, a knowledge-based model, in this case an ontological model, is created. This ontological model provides information for building the 3D model in a web application. Furthermore, it contains data about the suppliers and products, which after applying some reasoning, the purchase options for a pipe is shown. The research work is about scanning the scene with a 3D laser scanner and building an application for creating the model out of the scanned data. The web application recreates the structure and pipes on a 3D model, making the intersections between pipes and providing information about the replacement’s purchasing options

Algorithm-aided Information Design: Hybrid Design approach on the edge of associative methodologies in AEC

Dissertação de mestrado em European Master in Building Information ModellingLast three decades have brought colossal progress to design methodologies within the common pursuit toward a seamless fusion between digital and physical worlds and augmenting it with the of computation power and network coverage. For this historically short period, two generations of methodologies and tools have emerged: Additive generation and parametric Associative generation of CAD. Currently, designers worldwide engaged in new forms of design exploration. From this race, two prominent methodologies have developed from Associative Design approach – Object-Oriented Design (OOD) and Algorithm-Aided Design (AAD). The primary research objective is to investigate, examine, and push boundaries between OOD and AAD for new design space determination, where advantages of both design methods are fused to produce a new generation methodology which is called in the present study AID (Algorithm-aided Information Design). The study methodology is structured into two flows. In the first flow, existing CAD methodologies are investigated, and the conceptual framework is extracted based on the state of art analysis, then analysed data is synthesized into the subject proposal. In the second flow, tools and workflows are elaborated and examined on practice to confirm the subject proposal. In compliance, the content of the research consists of two theoretical and practical parts. In the first theoretical part, a literature review is conducted, and assumptions are made to speculate about AID methodology, its tools, possible advantages and drawbacks. Next, case studies are performed according to sequential stages of digital design through the lens of practical AID methodology implementation. Case studies are covering such design aspects as model & documentation generation, design automation, interoperability, manufacturing control, performance analysis and optimization. Ultimately, a set of test projects is developed with the AID methodology applied. After the practical part, research returns to the theory where analytical information is gathered based on the literature review, conceptual framework, and experimental practice reports. In summary, the study synthesizes AID methodology as part of Hybrid Design, which enables creative use of tools and elaborating of agile design systems integrating additive and associative methodologies of Digital Design. In general, the study is based on agile methods and cyclic research development mixed between practice and theory to achieve a comprehensive vision of the subject.Last three decades have brought colossal progress to design methodologies within the common pursuit toward a seamless fusion between digital and physical worlds and augmenting it with the of computation power and network coverage. For this historically short period, two generations of methodologies and tools have emerged: Additive generation and parametric Associative generation of CAD. Currently, designers worldwide engaged in new forms of design exploration. From this race, two prominent methodologies have developed from Associative Design approach – Object-Oriented Design (OOD) and Algorithm-Aided Design (AAD). The primary research objective is to investigate, examine, and push boundaries between OOD and AAD for new design space determination, where advantages of both design methods are fused to produce a new generation methodology which is called in the present study AID (Algorithm-aided Information Design). The study methodology is structured into two flows. In the first flow, existing CAD methodologies are investigated, and the conceptual framework is extracted based on the state of art analysis, then analysed data is synthesized into the subject proposal. In the second flow, tools and workflows are elaborated and examined on practice to confirm the subject proposal. In compliance, the content of the research consists of two theoretical and practical parts. In the first theoretical part, a literature review is conducted, and assumptions are made to speculate about AID methodology, its tools, possible advantages and drawbacks. Next, case studies are performed according to sequential stages of digital design through the lens of practical AID methodology implementation. Case studies are covering such design aspects as model & documentation generation, design automation, interoperability, manufacturing control, performance analysis and optimization. Ultimately, a set of test projects is developed with the AID methodology applied. After the practical part, research returns to the theory where analytical information is gathered based on the literature review, conceptual framework, and experimental practice reports. In summary, the study synthesizes AID methodology as part of Hybrid Design, which enables creative use of tools and elaborating of agile design systems integrating additive and associative methodologies of Digital Design. In general, the study is based on agile methods and cyclic research development mixed between practice and theory to achieve a comprehensive vision of the subject

Automated production of synthetic point clouds of truss bridges for semantic and instance segmentation using deep learning models

The cost of obtaining large volumes of bridge data with technologies like laser scanners hinders the training of deep learning models. To address this, this paper introduces a new method for creating synthetic point clouds of truss bridges and demonstrates the effectiveness of a deep learning approach for semantic and instance segmentation of these point clouds. The method generates point clouds by specifying the dimensions and components of the bridge, resulting in high variability in the generated dataset. A deep learning model is trained using the generated point clouds, which is an adapted version of JSNet. The accuracy of the results surpasses previous heuristic methods. The proposed methodology has significant implications for the development of automated inspection and monitoring systems for truss bridges. Furthermore, the success of the deep learning approach suggests its potential for semantic and instance segmentation of complex point clouds beyond truss bridges.Agencia Estatal de Investigación | Ref. PID2021-124236OB-C33Agencia Estatal de Investigación | Ref. RYC2021-033560-IUniversidade de Vigo/CISU

Enabling the Development and Implementation of Digital Twins : Proceedings of the 20th International Conference on Construction Applications of Virtual Reality

Welcome to the 20th International Conference on Construction Applications of Virtual Reality (CONVR 2020). This year we are meeting on-line due to the current Coronavirus pandemic. The overarching theme for CONVR2020 is "Enabling the development and implementation of Digital Twins". CONVR is one of the world-leading conferences in the areas of virtual reality, augmented reality and building information modelling. Each year, more than 100 participants from all around the globe meet to discuss and exchange the latest developments and applications of virtual technologies in the architectural, engineering, construction and operation industry (AECO). The conference is also known for having a unique blend of participants from both academia and industry. This year, with all the difficulties of replicating a real face to face meetings, we are carefully planning the conference to ensure that all participants have a perfect experience. We have a group of leading keynote speakers from industry and academia who are covering up to date hot topics and are enthusiastic and keen to share their knowledge with you. CONVR participants are very loyal to the conference and have attended most of the editions over the last eighteen editions. This year we are welcoming numerous first timers and we aim to help them make the most of the conference by introducing them to other participants

Digitalization of Battery Manufacturing: Current Status, Challenges, and Opportunities

As the world races to respond to the diverse and expanding demands for electrochemical energy storage solutions, lithium-ion batteries (LIBs) remain the most advanced technology in the battery ecosystem. Even as unprecedented demand for state-of-the-art batteries drives gigascale production around the world, there are increasing calls for next-generation batteries that are safer, more affordable, and energy-dense. These trends motivate the intense pursuit of battery manufacturing processes that are cost effective, scalable, and sustainable. The digital transformation of battery manufacturing plants can help meet these needs. This review provides a detailed discussion of the current and near-term developments for the digitalization of the battery cell manufacturing chain and presents future perspectives in this field. Current modelling approaches are reviewed, and a discussion is presented on how these elements can be combined with data acquisition instruments and communication protocols in a framework for building a digital twin of the battery manufacturing chain. The challenges and emerging techniques provided here is expected to give scientists and engineers from both industry and academia a guide toward more intelligent and interconnected battery manufacturing processes in the future.publishedVersio