Ford Motor Company Limited

Ford Global Technolgoies, LLC

Raja Shekar Sohmshetty

Zhiyong Cedric Xia

Shawn Michael Morgans

Matthew John Zaluzec

Krishnaswamy Venkatesh Prasad

Michael James Freeman

Lawrence J Dupuis

Saravanan Subramanian

Nicholas P Warrick

Theodore John Coon

Amir T Chator

A method of conducting vehicle usage data analysis is provided. The method includes providing usage data about at least one vehicle to a database. The usage data may be analyzed and compared to a member of a set of vehicle development models to determine whether to update a vehicle development model. The usage data may also be analyzed to determine whether to transmit a communication to a vehicle.

System and method of conducting vehicle usage data analysis

In one or more embodiments, a weldability of a stack-up for use in vehicle part production may be determined. The determination may include receiving general stack-up information, welding standards data for forming a stack-up, and one or more inputs defining one or more stack-up design variables. Additionally, standardized stack-up information may be generated based on the general stack-up information, the one or more design variables, and the welding standards data. Furthermore, historical welding data may be received for predicting a weldability of the stack-up. Predictive logic may be applied to the standardized stack-up information based on the historical welding data to obtain one or more weldability predictions for the stack-up. The one or more weldability predictions may be transmitted for use in vehicle part production.

Weldability prediction and recommendation systems and methods

A computer-implemented method for recommending one or more materials used in designing and manufacturing parts may include receiving data from at least three data sources. The data sources may include a sourcing, manufacturing, and design data source. The data source data may be standardized to obtain a collection of data including a dataset of materials for consideration in recommending one or more materials for use in one or more parts. The method may also include receiving optimization metrics and constraints for the dataset of materials. Optimization values for each material based on the dataset of materials and the one or more optimization metrics may be determined. An optimization algorithm on each material may be performed based at least on the optimization values and the constraints to obtain one or more recommended materials from the dataset of materials for use in a design of one or more parts.

Computerized system and method for recommending part materials

Various embodiments may include determining a material utilization for one or more assemblies having a plurality of parts. Offal data for one or more parts comprising one or more part assemblies and a blank material utilization status for each of the one or more part assemblies may be received. The blank material utilization status for the one or more part assemblies may be based on a blank material utilization status for each of the one or more parts. The offal data may be standardized to obtain standardized offal data. One or more offal utilization assignments for the part assemblies having a plurality of parts may be determined based on the standardized offal data and the blank material utilization status for the part assemblies. The offal utilization assignments may then be transmitted for assignment to the one or more part assemblies.

Computer-implemented method and system for determining a material utilization for part assemblies

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Canton, MI, United States of America

Raja Shekar Sohmshetty