In the realm of sustainable construction, Life Cycle Assessment (LCA) plays a key role as a tool for quantifying the environmental impacts of building materials and products. The integration of LCA and Building Information Modeling (BIM) makes it possible to evaluate the environmental performance of buildings at the design stage. This integration can help to improve the LCA process for buildings thanks to the potential for automation and interoperability. The goal of this study is to establish a BIM-based LCA workflow using the Industry Foundation Classes (IFC) open file format. The interoperability of BIM data exchange is achieved by applying IFC. The steps of the assessment process are described in accordance with the LCA phases outlined in the ISO 14040 standard. The impact assessment and results interpretation phases are automated by means of a program code for IFC file processing. The proposed BIM-based LCA is validated for a case study of a BIM model constructed for a three-story educational building. The GWP of the building materials and products of envelope and load-bearing structures at the A1–A3 life cycle stages are calculated for the purpose of proposed workflow testing. The resulting workflow allows for the calculation of negative environmental impacts to be agile, depending on the goal and scope set.
This paper presents a method for creating the system architecture of existing industrial objects based on Model-Based Systems Engineering (MBSE) principles. The method aims to form a digital representation of physical objects, which is crucial in the digital transformation of industrial enterprises. It allows for the accurate reflection of all components, processes, functions, and interrelationships within an object. The methodology includes stages of data collection, structuring, development of ontological models, and the integration of a comprehensive system architecture into the digital space. This method was tested using a small hydroelectric power plant, revealing its key advantages and disadvantages and identifying areas for further improvement. The main findings indicate a significant improvement in understanding the system architecture for scenario modeling and digital operation of the objects. Despite challenges such as the need for multiple iterations and high data requirements, the methodology demonstrates the potential for applying MBSE in the digital transformation of existing industrial objects.