Shoebox catalytic converter design to securely mount thinwall substrates with uniform mounting mat Gap Bulk Density (GBD) around the substrate is developed and validated. Computational Fluid Dynamic (CFD) analysis, using heat transfer predictions with and without chemical reaction, allows to carefully select the mounting mat material for the targeted shell skin temperature. CFD analysis enables to design the converter inlet and outlet cones to obtain uniform exhaust gas flow to achieve maximum converter performance and reduce mat erosion. Finite Element Analysis (FEA) is used to design and optimize manufacturing tool geometry and control process. FEA gives insight to simulate the canning process using displacement control to identify and optimize the closing speed and load to achieve uniform mat Gap Bulk Density between the shell and the substrate. Thermal fatigue analysis provides information for cone design and enables to optimize the system design with the right steel material for the converter. Optimized soft tools are used to produce the shoebox converter shells and inner cones. Tolerance stacking of the shell profile, substrate contour profile and the mounting mat basis weight are properly chosen to demonstrate the worst case canning situations for brick breakage and on-road durability. i.e: Smallest shell (with negative tolerance), largest raw substrate (+ 1.5 mm on the profile) and the heaviest mounting mat (+ 8% basis weight tolerance) have been used to evaluate the substrate breakage (maximum GBD). Whereas largest shell profile, smallest substrate, and lowest basis weight mounting mat combinations (lowest GBD) are assembled to establish the converter high temperature durability. This provides the maximum confidence level of the canning process. This paper presents the capability to design, develop, manufacture, and test shoebox catalytic converter for thinwall substrates and the use of Computational Analysis and Engineering (CAE) to compliment converter design process from concept to manufacturing.