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The aerospace industry is continually becoming more competitive. With an aircraft's large number of components, and the large supplier base used to fabricate these components, it can be a daunting task to manage the quality status of all parts in an accurate, timely and actionable manner. This paper focuses on a proof of concept for an aircraft fuselage assembly to monitor the process capability of machined parts at an aircraft original equipment manufacturer (OEM) and their supply chain. Through the use of standardized measurement plans and statistical analysis of the measured output, the paper will illustrate how stakeholders can understand the process performance details at a workcell level, as well as overall line and plant performance in real time. This ideal process begins in the product engineering phase using simulation to analyze the tolerance specifications and assembly process strategy, with one of the outputs being a production measurement plan.

The effects of thermal expansion and gravity on assembly processes in automotive manufacturing can and often do cause unexpected variation. Not only do these effects cause assembly issues, they can also create non-conformance and warranty problems later in the product lifecycle. Using 3D CAD models, advances in simulation allow engineers to design out these influences through a combination of tooling, process and tolerance changes to reduce costs. This whitepaper examines the process of simulating the effect of both thermal expansion and gravity on automotive structures. Using real life examples, a number of solutions were determined and tested in a simulated environment to reduce product variation and account for unavoidable environmental variation.

Quality itself is no longer a differentiator among aerospace manufacturers. High quality is expected and achievable. With enough time and money, any manufacturer can turn around a high-quality product. Around the globe, the focus of manufacturing quality is shifting to a discussion about the cost of quality and how to manage it. The question being asked by manufacturers is no longer how to achieve quality, but how to achieve it within cost and time constraints. The aerospace manufacturer that can achieve quality with the least expense, while producing products the fastest, is the one that will win in today's tough, global market. This paper will describe the “closed-loop” approach to dimensional engineering, utilizing virtual simulations and tolerance analyses, and how such an approach can link cost factors with tolerance adjustments so that users have the data they need to make the most strategic business decisions regarding the balance between quality and cost.

Users of a well-thought-out dimensional engineering (DE) process and the latest simulation-based tolerance analysis tools can greatly reduce the need for physical prototypes through virtual analysis. This presentation will highlight how tolerance analysis tools used as part of a DE process enable users to complete the development and launch of new and enhanced products in far less time than the competition. Don Jasurda, an experienced industry speaker, will describe how simulation-based tools used in a “closed-loop” DE process enable users to identify potential engineering issues in the virtual world instead of using physical prototypes. He will highlight real-life case study examples where automotive OEMs and suppliers have been able to use such tools to: Quickly predict and respond to the affects of variation and its impact on product quality.

Simulation-based tolerance analysis is the accepted standard for dimensional engineering in aerospace today. Sophisticated 3D model-based tolerance analysis processes enable engineers to measure variation in complex, often large, assembled products quickly and accurately. Best-in-class manufacturers have adopted Quality Intelligence Management tools for collecting and consolidating this measurement data. Their goal is to completely understand dimensional fit characteristics and quality status before commencing the build process. This results in shorter launch cycles, improved process capabilities, reduced scrap and less production downtime. This paper describes how to use simulation-based approaches to correlate the theoretical tolerance analysis results produced during engineering simulations to actual as-built results. This allows engineers to validate or adjust as-designed simulation parameters to more closely align to production process capabilities.