Standardized design principles and emerging opportunities for AI-integrated CAD systems.

Artificial Intelligence (AI) in the automotive industry is growing and transforming in different segments of the industry. Still there is a significant gap persisting in the standardization of design principles and the incorporation of manufacturing constraints in system. However current development in AI CAD systems is isolated and non-parametric way, in contrary the conventional way of CAD methodology is knowledge based and systematic parametric steps which is agile to the iterative improvement. Hence it will be challenging in integration and adoption of these AI CAD systems in the well-established product development cycle. The research focuses on identifying the scope of AI integration which includes generative design, automated error detection, and design pattern-dependent learning systems, but also stresses the importance of standardized policies to address fundamental questions of system coherence, uniformity, and broad applicability. This research paper studies the adoption of Knowledge Based Engineering (KBE) which leverages the AI to develop and integrate AI parametric CAD development. By synthesizing insights from industry use cases and academic research, we outline a set of core design standards and manufacturability constraints tailored for AI integration. The outcome of this paper could be a guiding principle for the emerging opportunities and challenges posed by AI in CAD systems and devise a framework for the future intelligent systems of standardized designs. This study also serves as a basis for developing AI agents can provide valuable insights to automotive industry to create more sustainable and resilient Product Development systems Keyword: Artificial Intelligence (AI), AI Agents, AI in CAD, Product Development systems, Automotive Product Development, Incorporation, Manufacturing Constraints, Guidelines