Bracketing brackets with bras and kets

TL;DR

This paper introduces a data-driven hierarchical clustering method to reduce the variety of brackets in aircraft manufacturing by 30%, maintaining sufficient accuracy, thus streamlining production and reducing costs.

Contribution

It presents a novel similarity measure based on 'bra' and 'ket' components for clustering brackets, enabling efficient standardization in aerospace manufacturing.

Findings

Reduced bracket set by 30% while maintaining accuracy

Hierarchical clustering effectively groups similar brackets

Method applicable to other large-scale component standardization

Abstract

Brackets are an essential component in aircraft manufacture and design, joining parts together, supporting weight, holding wires, and strengthening joints. Hundreds or thousands of unique brackets are used in every aircraft, but manufacturing a large number of distinct brackets is inefficient and expensive. Fortunately, many so-called "different" brackets are in fact very similar or even identical to each other. In this manuscript, we present a data-driven framework for constructing a comparatively small group of representative brackets from a large catalog of current brackets, based on hierarchical clustering of bracket data. We find that for a modern commercial aircraft, the full set of brackets can be reduced by 30\% while still describing half of the test set sufficiently accurately. This approach is based on designing an inner product that quantifies a multi-objective similarity between two brackets, which are the "bra" and the "ket" of the inner product. Although we demonstrate this algorithm to reduce the number of brackets in aerospace manufacturing, it may be generally applied to any large-scale component standardization effort.