# Grasshopper Algorithmic Modelling: Parametric Design for Product Platform Customisation
## 1 Introduction  
Industrial progress has been marked by the incorporation of technologies that have transformed societies and production processes [1]. In the field of industrial design, these advances have generated the need for more agile methodologies. These methodologies allow an efficient response to current market demands, characterised by high variability and a growing demand for customisation. Among these, artificial intelligence, advanced automation, and intelligent manufacturing stand out for their ability to drive adaptation to a constantly changing market [2, 3, 4, 5, 6, 7, 8, 9]. Industrial product design is characterised by a high demand for customisation and scalability based on user segments and profiles. In response, companies and manufacturers frequently employ product platform strategies. These platforms make it possible to generate product variants that adapt to the market in a more efficient and structured way. This is achieved through a combination of standardisation and customisation indesign and manufacture. On the one hand, the standardisation of components, modules, or manufacturing processes facilitates mass production and promotes economies of scale. This approach contributes to reducing costs and reducing development times. On the other hand, these platforms offer flexibility to introduce customisable elements that adapt to specific user demands, satisfying more individualised market segment needs. This balance between standardisation and customisation makes product platforms a useful strategy to optimise the use of technical, human, and economic resources. Additionally, it improves competitiveness in an increasingly dynamic market. However, although they offer the advantages mentioned above, the platform design process is highly complex. This is particularly evident in the generation and management of product variants, as well as in the adaptation of solutions to specific user requirements. These requirements are linked to multiple contexts of use, variants of products, and configurations. This situation increases workload and makes design activities more difficult. Generally, such projects require engineering teams to plan extensively to achieve a proper integration between standardised and customisable components. This level of complexity is usually addressed through the application of specific design methodologies. The implementation of these methodologies requires a significant investment in technical, human, and temporal resources, particularly during the early stages of conceptualisation [10,11]. Within this framework, computational design, in its different parametric, algorithmic, or generative scopes, is a solution to address these limitations. This happens because of the possibility of automating repetitive tasks generating multiple design variants and configurations according to predefined criteria. These tools simplify the process and expand creative and technical possibilities by providing agile working environments. Traditionally, computational design resources for product platforms required advanced programming knowledge and specialised technical software. The utilisation of software such as Catia (Dassault Systemes, Velizy-Villacoublay, France), Ansys (Ansys Inc., Canonsburg, PA, USA), and Matlab, (MathWorks Inc., Natick, MA, USA) in conjunction with specific programming environments such as Java, Python, or C++, necessitates the possession of advanced coding and programming abilities. Consequently, these tools are predominantly used by multidisciplinary teams. However, recent developments in visual programming tools, such as Grasshopper (an integrated component in Rhinoceros 3D (Robert McNeel & Associates, Seattle, WA, USA) [12], Fusion 360 Generative Design (Autodesk Inc., San Francisco, CA, USA) [13] or Altair HyperWorks (Altair Engineering Inc., Troy, MI, USA) [14], are streamlining design processes through visual interfaces based on node manipulation and graphical flows.