International Business Machines Corporation

Michael D Patek

Jayant R Kalagnanam

Moninder Singh

Ghassan Chidiac

Sudhir Verma

Fabio Dennis White

Yuk Wah Wong

Automated mapping of part numbers associated with parts in a bill of materials (BOM) submitted by a BOM originator to internal part numbers assigned to those parts by a BOM receiver is performed by one or more computers connected to one or more networks through one or more network interfaces. A first receive component receives one or more data sets containing historical data on bills of materials received in the past by the BOM receiver. A second receive component receives one or more data sets containing known mappings between internal part numbers used by the BOM receiver, and part numbers used by various BOM originators. A third receive component receives one or more data sets containing information of various parameters and their values describing the parts to which the BOM receiver has assigned internal part numbers. A fourth receive component receives one or more methods of automatically learning models for predicting internal part numbers from the above mentioned historical BOM data, mapping data and part parametric data. A learning component learns the models from the data. A fifth receive component receives a BOM from a requesting process. The BOM has one or more parts with a missing internal part number. A mapping component applies the learned models to the received BOM to automatically determine internal part numbers for all unmapped BOM originator part numbers. A release process assigns internal part numbers to all unmapped parts in the BOM and releases the BOM to the requesting process.

System and method for automated part-number mapping

Automated mapping of part numbers associated with parts in a bill of materials (BOM) to internal part numbers assigned by a BOM receiver. Historical data on bills of materials, known part number mappings, and parametric data describing the parts associated with bills of materials re received. Prediction models, for predicting BOM receiver internal part numbers, are learned from the historical BOM data, known part number mappings data and parametric data. The learned models are applied to unmapped BOM originator part numbers to assign BOM receiver internal part numbers.

System for automated part-number mapping

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Philadelphia, PA, United States of America

Michael D Patek