Using Real-Time Data for Increasing the Efficiency of the Automated Fibre Placement Process

Abstract

The Automated Fibre Placement (AFP) process has grown in popularity with an increasing install base that realistically began within the last decade. This growing popularity stems from the technique’s promise of higher deposition rates (>10kg/hr), enhanced quality, and reduction of intensive manual labour. However, AFP machines are still relatively few in number as compared to other automated routes for fabrication; with only a few airframers and suppliers proactively developing the technique. The purpose of this paper is to report on the non-value adding activities that detrimentally impact on production rate capability. For example, inspection is typically carried out manually and can account for a large percentage of the cycle time. The risk therefore, is that by not adequately addressing non-value adding activities, a costly level of investment could be needed to achieve the production rates required. We provide a longitudinal case study, accounting for the non-value adding tasks that surround the process. Our results show that, by percentage, these activities have been targeted and reduced over a two year period. We are also able to demonstrate, through coefficient of variation, how the AFP process has stabilized over the two years. A 92% learning curve has emerged that better represents cycle time reductions for each successive part, as opposed to the 80% learning curve traditionally adopted.