# Grasshopper Algorithmic Modelling: Parametric Design for Product Platform Customisation
## 2 Background
The growing demand for customised solutions has driven the use of algorithmic modelling tools such as GH. These tools make it possible to create products tailored to the individual needs of users, optimising aesthetics and functionality by automating parameters. In the scientific literature, GH has been used specifically to customise origami-inspired structures [60]. It has also been used to design surfboard and paddleboard fins that optimise performance and suit surfers' personal preferences [61]. Other uses include generating revolving mesh shapes from customised revolution profiles based on material density and mesh patterns [62], performing isogeometric analysis (IGA) in engineering by optimising the design and analysis cycle [43], and creating product designs with Voronoi patterns inspired by nature and traditional Chinese culture [63]. GH has also been used to optimise the creative and production process in furniture design with greater flexibility and responsiveness to market demands [59], create complex and customised patterns in textile design by improving efficiency and adaptability in the textile industry [64], and design bottles that adapt their shape and texture according to user tactile preferences, combining Kansei engineering and design [65]. Furthermore, GH has been used to design ornamental patterns based on traditional cultural motifs [66] and to design ergonomic seating by integrating anthropometric and ergonomic data to optimise product shape, functionality, and customisation [67]. Although numerous applications of GH have been explored in other areas of design, the current literature on its use in platform design is limited. Product platforms are currently the strategies followed by the industry to manage their product portfolios in the marketplace [10; 11]. They offer significant advantages, such as reducing development time and costs through component reuse and increasing product variety without adding excessive production complexity. Moreover, they facilitate mass customisation to address diverse consumer needs. However, product platform design also presents important challenges. These include the complexity of managing interdependent components, the need for efficient modularisation strategies, and the difficulty of balancing standardisation with customisation. In this sense, GH could streamline the product platform design process by automating the generation of multiple customised product variants through a single algorithm. By integrating parametric modelling, GH enables designers to define rules and constraints that ensure consistency across platform variants. It also facilitates real-time visualisation of design alternatives while allowing adjustments to parameters such as dimensions, materials, and functional characteristics. Finally, it is interesting to consider the relationship between design parameters and manufacturing criteria from the early stages of the process. Decisions taken during parametric modelling condition the technical and economic feasibility of the product. Certain combinations of geometries, materials, or configurations may be complex or unfeasible to manufacture with conventional technologies. Therefore, incorporating manufacturing criteria into algorithmic models allows the constraints of the production process to be considered in the conceptual design phase.