When facing the increasing demands of the housing market and balancing the requirements of sustainable development in the construction sector, building design methods should practise material conservation and adopt carbon reduction measures to alleviate the current environmental burden through the implementation of a circular economy approach. Volumetric modular timber design is recognised as a practical application to test the feasibility of a waste-reduced approach. Driven by the aim of further improving volumetric modular timber construction and increasing its use in a circular economy framework, this paper presents a case study review of 60 modular timber building projects constructed using volumetric modules. The dimensions, the architectural and structural design, and the manufacturing and assembly processes of the three-dimensional modular units were assessed to explore their potential for contributing to a circular built environment. The results show that the similarly sized modular volumetric timber units have the potential to serve different functions, and to be reused in subsequent projects. The stacking design allows modular volumetric units to be reused in a way that supports function conversion and satisfies project coordination criteria. The case studies illustrate that modular timber buildings are increasingly used for flexible design solutions, and to meet carbon emission reduction targets. The analysis results can address prevalent misconceptions regarding modular wood construction, provide interested parties with a better understanding, and promote the use of modular volumetric timber units in general.

A method for building slabs composed of discrete short timber slats is proposed. It involves simulating its principal stresses to locate and orient each building component. Those are assembled by a robotic arm in collaboration with a worker using an Augmented Reality head-mounted device. The prototype serves as a proof of concept and proved structurally viable, and future work involves interlocking the slats using halved joints and implementing a strategy to reuse wood production waste components as stock material.

The field of artificial intelligence (AI) has recently attracted the attention of many disciplines due to the exceptional accomplishments and rapidly emerging possibilities. Architecture, a discipline traditionally skeptical of new technologies, is intrigued by the results achieved with generative neural networks. The emergence of new technologies in the field of generative artificial intelligence has led to numerous scenarios among architects about possible applications of these technologies in their practice. A large number of these scenarios are based on the functionality of commercially available Large Language Models and their application to text to image and image to image transformations. A smaller number of scenarios are based on specific applications of AI technologies through the development of real software solutions. The paper critically analyzes existing scenarios through a review of existing research and a description of software solutions. The focus is on the application of Generative Neural Networks and the paper provides an overview of the functioning of the basic classes of neural networks that make up this technology. An analysis of how artificial neural networks work shows that they all depend on the data set used to train them. Today's neural networks use an enormous amount of data, but even that is limited to what is available in electronic format. The main source of general knowledge is online encyclopedias, while expert knowledge is provided by published articles that have a certain level of reliability. Architects who are mistrustful of this technology need to understand that better results can only be achieved through higher-quality training data sets and that their protectively guarded knowledge also comes from studying the work of other architects.