# Enhancing 3D Printing with Procedural Generation and STL Formatting Using Python
## 3 Materials and Methods
The Involute method of generating gears uses an involute because it is a curve that fits well with the tooth profile of the gear/pinion and defines the path of the end of the stressed thread unwinding from the wheel. The algorithm draws the gear tooth profile using mathematical equations that describe the evolute curve. Three-dimensional scanning and artificial intelligence (AI) are vital in personalizing three-dimensional models in various fields such as medicine, industry, fashion, and entertainment. These technologies contribute to personalization in 3D scanning by collecting accurate data. Three-dimensional scanners use structured light, laser, or photogrammetry to create precise three-dimensional models of actual objects. The scanning provides detailed geometric and texture data, which forms the basis for further processing and personalization. Furthermore, given real-time personalization, users can scan their bodies, personal objects, or other objects of interest and immediately receive digital models for further modification. Three-dimensional scanning makes it possible to create models that perfectly reproduce the unique characteristics of the scanned object, which is particularly important in medicine (e.g., the creation of prostheses and implants) and fashion (e.g., tailored clothing). In terms of artificial intelligence, given automatic data analysis and processing, AI algorithms can analyze 3D scan data, identify relevant features, and automatically remove unwanted artifacts. AI can also classify and segment different parts of the model, facilitating further processing. In terms of optimization and personalization, machine learning makes it possible to customize 3D models based on collected data and user preferences. For example, algorithms can suggest optimal changes to the model based on the analysis of historical data. Considering medicine, artificial intelligence can help personalize prostheses by analyzing the patient's anatomy and suggesting the best solutions. In terms of data-driven model generation, generative adversarial networks (GANs) can create new personalized 3D models based on existing data and user preferences. Artificial intelligence can simulate different scenarios and predict how changes to the model will affect its appearance and functionality. In terms of interactive design, AI algorithms can support users in the design process by offering interactive tools that suggest changes and improvements in real-time. With AI, users can easily experiment with different model variations and quickly see the effects of their decisions. Considering medicine, 3D scanning and AI can create personalized prostheses, dental implants, or orthopedic devices and plan surgeries based on 3D models of a patient's organs. Looking at fashion, they can scan a customer's body, create clothes that fit their physique perfectly, and personalize fashion accessories such as eyewear or jewelry. Looking at the industry, they can help design machine parts and equipment tailored to specific manufacturing requirements. Furthermore, they can scan and analyze parts for reproduction or optimization. Considering entertainment, they create realistic character models for video games or films and personalize avatars in virtual reality. In summary, 3D scanning and artificial intelligence significantly improve the process of creating personalized 3D models, increasing their accuracy, efficiency, and customization. The process of creating a personalized 3D model and converting it to STL file format involves several key steps:  
* Data collection through 3D scanning to capture the geometry and surface details of the physical object with 3D scanners using structured light, laser scanning, or photogrammetry. The object is scanned to create a point cloud that represents the object's surface in 3D space. * Data processing for point cloud cleaning to remove noise and irrelevant data from the point cloud using software such as MeshLab and CloudCompare. Algorithms or hand tools remove outliers and unwanted points, smoothing the dataset.