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Abstract
Recalls and defective parts are a major problem for manufacturers and a major challenge in information management. Increasingly complex supply chains have created a situation where parts ' data is distributed across a volatile network of suppliers' databases. The challenge of parts tracking in this environment requires maintaining data views across constantly-restructuring networks of information systems as new suppliers are contracted and subassemblies are outsourced. In this paper we present a method for manufacturers to efficiently and automatically index all component parts in their products, allowing for complex changes to the supply chain, and enabling highly efficient reverse-lookups for recalls. Our method improves parts lookup and search time by subdividing all component part indexes into a distributed, versioned matrix of tables which models the structure ofthe supply chain, We introduce a method of reverse-indexing component parts using manufacturing time to pinpoint products for selective recalls, running in a fraction of the time of a traditional database search. We evaluate our method for applicability to the automotive industry using statistically re-generated data from a major automobile manufacturer to simulate a supply chain 7 layers deep, comprising 1000 individual component parts, indexing a distributed dataset totaling approximately ITB in size. © 2007 IEEE.