## 1 Introduction  
In recent years, the architecture, engineering, and construction (AEC) sector has increasingly adopted parametric models--models that dynamically control the geometry and its behavior--and building information models (BIMs)--enhanced parametric models enriched with semantic data--to leverage computational design techniques [1]. These computerized methods have allowed architects to develop extraordinary and unique designs. While this freedom can lead to innovative architectural forms, it also introduces constructability challenges due to the complexity of these designs [2]. While computational design techniques have enabled the creation of complex, unique designs, they have also facilitated the prefabrication of various building components and systems. However, the computerization of prefabrication processes by design teamspresents its own challenges, as most designers often lack detailed construction knowledge [3,4]. Consequently, identifying and addressing constructability issues has become a primary concern in projects featuring highly complex architecture with prefabricated components. In this context, the constructability of prefabricated facade systems is particularly challenging, as it involves both design complexity and the intricacies of prefabrication processes. Moreover, this responsibility is often given to the design team, including architects and computational designers, increasing their accountability to finalize construction details and address constructability issues as early as possible in a project [4]. Addressing constructability issues relies heavily on relevant construction knowledge and experience, according to [5]. Therefore, it is essential for designers to develop effective methods for integrating the necessary constructability knowledge into their workflows, particularly within computational design processes. As [PERSON] et al. [6] suggest, most constructability challenges during the design phase arise due to (1) the lack of constructability knowledge; (2) insufficient information; and (3) poor coordination with other disciplines. These issues become particularly crucial in traditional project delivery models, where computational designers often work in silos, bearing primary responsibility for resolving constructability challenges. Even in more collaborative projects, the absence of a systematic approach for receiving and incorporating constructability knowledge into the computational design process often leaves outcomes dependent on the personal interpretation and understanding of individual designers. To address this issue, some efforts have been made to introduce methods ensuring that necessary experts' knowledge is considered during the design process. For instance, refs. [7,8] propose methods for establishing checklists for constructability criteria to enhance the quality of the computerized design process using BIM, while [9,10] focus on general constructability considerations incorporated into the design for manufacturing and assembly (DfMA) process. However, as noted by [11], the existing research still lacks methods that integrate constructability knowledge as a driving factor in the computerized design process. Therefore, it is essential to explore methods for systematically integrating experts' knowledge into the computational design process. For this purpose, the feature-based modeling (FBM) approach has shown the potential to be a viable tool for integrating the necessary knowledge into the computational design processes [12]. However, despite the great potential of FBM approaches to convey expert knowledge into the design process and its proven success in other engineering fields, only a few AEC studies have detailed how to develop such features and implement them in models computationally [12, 13, 14, 15, 16, 17]. Furthermore, a systematically structured method for formalizing and developing design constructability constraints and features for prefabricated building components is still lacking.