With strict government requirements for automobile fuel economy and global climate warming concerns, powertrain design becomes ever more challenging and complicated. New technologies come out daily, and each component, small or large, is scrutinized for weight, cost, performance, etc. To meet these ever demanding requirements, Computer Aided Engineering (CAE) becomes very critical in the product development process. It not only saves tremendous developing time and cost, but also helps discover new and innovative ideas very quickly. Digital product development process is an industrial norm nowadays. Parts are modeled in 3D in a Computer Aided Design (CAD) system, and then they are passed to and modeled in a Finite Elements Analysis (FEA) software package for analysis. If the analysis results do not meet the requirements, engineers either modify the FEA models or 3D CAD geometry for re-analysis. The process could be very time-consuming and inefficient between, often times, heterogeneous systems. There exists some CAD / CAE integrated software packages, such as Dassault Systemes CATIA, where FEA models are directly linked to the 3D CAD geometry. Yet, complicated mesh definitions would still involve a lot of manual work in order to meet vigorous analysis requirements. In this paper, a parametric customized mesh pattern definition method is developed, which can precisely formulate according to strict analysis mesh requirements, and automatically adapt to a range of analysis model geometries. Along with this parametric meshing technique, CAE analysis templates are developed to embed analysis standards into models driven by parameter tables, part geometry instances, other parametric analysis models, etc. Furthermore, the CAD / CAE integrated template can be implemented in optimization processes, so the improvement of geometric models can be directly driven and assessed by optimization algorithms. This technology makes possible to automate highly customized and complicated mesh creation, resulting in mesh generation efficiency gains of up to 80%. Large numbers of design iterations can be analytically investigated in a compressed time frame, the consistency of analysis can be insured, and CAD designers can optimize designs without having direct CAE experience, and CAE engineers can achieve consistent analysis results by strictly following standard sophisticated mesh requirements.