This presentation was held at the 2020 NAFEMS UK Conference "Inspiring Innovation through Engineering Simulation". The conference covered topics ranging from traditional FEA and CFD, to new and emerging areas including artificial intelligence, machine learning and EDA.

Resource Abstract

Appropriate tolerancing is a critical component of reaching the best manufacturing cost for a component, with tight tolerancing being a common reason for the selection of more expensive manufacturing processes. During a standard design and development process, it is generally difficult for an engineer to understand the impact of tightening or loosing tolerances on manufacturing process selection and the resulting manufacturing cost. This is especially true for newer engineers or those with limited experience in manufacturing. Ideally, an engineer with limited manufacturing experience would be able to investigate an extensive list of manufacturing and tolerances combinations and receive feedback on the cost from internal experts or suppliers to help build their intuition. Completing this process, though, is time prohibitive and requires the involvement of many individuals. Automation of this process using available software tools would be a natural solution.

A geometry-based manufacturing and costing analysis solution which can read PMI based tolerances and includes common heuristics for manufacturing process selection can provide visibility to the impacts of tolerances on manufacturing process selection, cycle time, and cost more quickly and consistently than consulting an expert. By automating such a software with a multi-discipline design optimization toolset, it now becomes feasible to understand the impacts of tolerance changes on manufacturing process requirements and find better solutions for both tolerancing and manufacturing options. In this study, tolerance and manufacturing options are investigated for a manufactured part through the automation of the aPriori costing software using a multi-disciplinary design optimization toolset. With this investigation it is possible to see opportunities for manufacturing improvement by using cost as the primary metric. Additionally, the output of such an analysis enables those with limited experience in manufacturing to make informed decisions regarding the manufacturing implications of tolerancing, thus providing an opportunity to further democratize aspects of the engineering process.