Evaluation of parametric CAD models from a manufacturing perspective to aid simulation driven design

Abstract: Scania are known among to be the world’s leading supplier of transport solutions for heavy trucks and buses. Scania’s goal is to develop combustion engines that achieve low-pollutant emissions as well as lower carbon-footprint with higher efficiency. To achieve the above Scania has invested resources in Simulation Driven Design of parametric CAD models which drives design innovation rather than following the design. This enables in creating flexible and robust models in their design process. This master thesis is being conducted in collaboration with Scania exhaust after treatment systems department, focusing on developing a methodology to automatically evaluate the cost and manufacturability of a parametric model, which is intended for an agile working environment with fast iterations within Scania. From the thesis methodology’s data collection process literature study, former thesis work and interviews with designers and cost engineers at Scania, a proposed method is developed that can be implemented during the design process. The method involved four different phase they are Design phase, Analysis phase, Validation phase and Improvement phase. The proposed method is evaluated to check the method feasibility for evaluation on parameteric CAD parts for manufacturability and costing. This proposed method is applied on two different parts of a silencer as part of a case study which is mainly to evaluate the results from Improvement phase. The focus of this thesis is to realise the proposed method through simulation software like sheet metal stamping/forming simulation, cost evaluating tool where the simulation driven design process is achieved. This is done with the help of collaboration between parameteric CAD models and the above simulation software under a common MDO framework through DOE study run or optimisation study runs. The resultant designs is later considered to be improved design in terms of manufacturability and costing.