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Design of a Modular Cloud Storage Gaging System for Automotive Manufacturing

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2015 ASEE Annual Conference & Exposition


Seattle, Washington

Publication Date

June 14, 2015

Start Date

June 14, 2015

End Date

June 17, 2015





Conference Session

Instrumentation Division Technical Session 4

Tagged Division


Page Count


Page Numbers

26.467.1 - 26.467.16



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Paper Authors


Mark Jeffrey ZurSchmiede Federal Screw Works

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Mark Jeffrey ZurSchmiede is a Computer Engineering Graduate Student at Grand Valley State University and a practicing software engineer at Federal Screw Works. After four years designing embedded software for the Aerospace and Medical industries, he took a new job at an automotive manufacturing facility. This latest project seeks to merge the automotive manufacturing world with embedded systems world by designing custom gaging solutions for the companies' automotive parts.

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Jeffrey Ward Grand Valley State University

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Design of a Modular Cloud Storage Gaging System for   Automotive Manufacturing    The proposed research project will involve the electrical and software design of an automated gaging system for automotive parts. Using an optical micrometer, the proposed gage will construct a virtual 3D image of a cylindrical part and then extract dimensional information from the 3D image. The design of the gaging system has two primary objectives. First, to record critical dimensions on every part that comes through a manufacturing line and provide alerts if the system has fallen outside of the maximum tolerances specified for any critical dimension. Second, to report the dimensions of all parts to a cloud­based database allowing managers to check process statistics remotely. All parts that are produced on manufacturing lines with this gaging system integrated must be marked with a serial number allowing any part run through the system to be matched to its dimensional data in the database as well any other critical information about the part.  In the past, common problems have arisen when trying to implement automated gaging. These include contaminants on the part corrupting the gaging system, uneven surfaces on the part causing probe tips to move in unpredictable ways and problems with the steel blanks such as warped thread blanks which cause a part to sit in a gaging fixture improperly. The gage design will account for all of these failure modes by using optics to eliminate mechanical problems and software filters to eliminate outliers in datasets.  In addition, the gage design will provide a shallow learning curve  in the manufacturing realm by using a Programmable Logic Controller (PLC) to control the state machine of the system with an embedded controller processing the data from the gage and responding to analysis requests from the PLC. 

ZurSchmiede, M. J., & Ward, J. (2015, June), Design of a Modular Cloud Storage Gaging System for Automotive Manufacturing Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23805

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