Our Vision - AI4BI
Glass and façade construction is highly technological in the field of industrial production and further processing of glass, since glass is a brittle material and poor processing quality can lead to fatal events in its assembly, construction and / or operation. As a result, high-precision machines are used for glass processing in order to refine the brittle material in such a way that it exhibits the highest quality. Starting with the washing of the glass, through cutting and breaking, thermal / chemical tempering and lamination to a laminated or laminated safety glass. The machine technology for glass finishing is constantly being improved and optimised to customer specifications. Due to the high degree of digitization, AI technologies can be easily integrated and used for a faster and more systematic improvement of production and manufacturing. Process parameters can be easily optimized on the basis of existing data (if necessary in real time) and thus the production process can be improved. In addition, in-line scanners can be used to provide additional data regarding factory production control to create a valid and quantitative categorization of new building products. The idea lies in the in-line observation of patterns in the glass, such as NiS inclusions, cut edges or broken glass edges, and the possibility to derive quantitative statements regarding fracture strength without testing them experimentally.
Data-Driven Material Modelling
Modern materials are also used in glass and façade construction, in particular a wide variety of polymers, but their constitutive modelling is much more complicated than established building materials due to their thermomechanics. For more than ten years now, diverse experimental and methodological work has provided the basis for an improved understanding of the material and load-bearing behaviour of these materials by engineers, whereby the most up-to-date methods place the highest demands on the engineer and the tools available to him, such as finite element software. AI-supported modelling of the technical properties of these materials is one of the most recent developments in the field of research. In this case, large amounts of data (often already collected by the approval procedures) are used to characterize the material under quasi-static, aged and cyclically fatigued boundary conditions and an AI-based constitutive model is calibrated instead of the well-known phenomenological one. The appropriate keyword for this is "Data-Driven Material Modelling".
Adhesive bonding in façade construction is becoming increasingly popular as it offers an aesthetically pleasing solution for the façade without damaging the glass through drilling. Silicone adhesives, which exhibit complex material behaviour and failure, are often used. It is worth taking a closer look, especially in numerical calculations, since modern material models and failure formulations can help you get more out of it than obsolete concepts such as ETAG 002.