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SAE - Total Quality Assurance of Aerospace Components Applying Process Capability Analysis

Total Quality Assurance of Aerospace Components Applying Process Capability Analysis

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. This establishes clear guidelines for consistency in the inspection process.

The measured data generated during the inspections is aggregated, analyzed and reported as a process capability index. This index is monitored in real time to track quality status across the organization. Issues are identified, reported and resolved using root cause drill downs to find the source within seconds or minutes of the measurements being made.

By showing production variation based on data, aircraft manufacturers are creating actionable reporting and quality tracking for process capability at their production sites, on a continuous and nearly instantaneous basis.

  • Introduction
  • Understanding the Cost of Quality
  • Variation: Root of the Problem
  • Use of Quality Management Systems
  • Process Capability Index as Quality Metric
  • Overall Quality Process
  • Closed-Loop Quality Process
  • Using a Quality System for Problem Identification
  • Process Summary: Simulation to Solution
  • CONCLUSIONS

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