Application of Metrology, Statistics, Root Cause Analysis, and Cost of Quality to Enable Quality Improvements and Implementation of Statistical Process Controls for Acceptance of Large Complex Assemblies (SAE Paper 2021-01-0025)

For new aircraft production, initial production typically reveals difficulty in achieving some assembly level tolerances which in turn lead to non-conformances at integration. With initial design, tooling, build plans, automation, and contracts with suppliers and partners being complete, the need arises to resolve these integration issues quickly and with minimum impact to production and cost targets.While root cause corrective action (RCCA) is a very well know process, this paper will examine some of the unique requirements and innovative solutions when addressing variation on large assemblies manufactured at various suppliers. Specifically, this paper will first review a completed airplane project (Project A) to improve fuselage circumferential and seat track joins and continue to the discussion on another application (Project B) on another aircraft type but having similar challenges. The use of Project A and B is used here to ensure proprietary protection of internal and supplier propriety information.One particularly innovative idea on both these projects is implementation of statistical process control for product acceptance as this provided and continues to provide additional incentive to invest more aggressively in quality improvements. For Project A, costs across the build cycle were overlaid with process capability to not only focus corrective action but also enlighten the program as to where increasing tolerances allowed focus on where it was really needed and avoid �false alarm�. This paper will detail how process capability requirements were adjusted to balance manufacturing capability with engineering requirements. For the Project B, this paper will review how these same principles are currently being applied to a fixed leading edge in concert with six sigma to address out of control variation.