LGJul 31, 2020

Bracketing brackets with bras and kets

arXiv:2008.12247v12 citations
Originality Synthesis-oriented
AI Analysis

This addresses cost and efficiency problems in aerospace manufacturing by standardizing components, though it is incremental as it applies existing clustering methods to a new domain.

The authors tackled the inefficiency of manufacturing many unique brackets in aircraft by developing a data-driven framework to reduce the number of distinct brackets through hierarchical clustering, achieving a 30% reduction while maintaining accuracy for half of the test set.

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.

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