Design of a Modular Cloud Storage Gaging System for  Automotive Manufacturing

Mark Jeffrey ZurSchmiede; Jeffrey Ward

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Conference: 2015 ASEE Annual Conference & Exposition
Location: Seattle, Washington
Publication Date: June 14, 2015
Start Date: June 14, 2015
End Date: June 17, 2015
ISBN: 978-0-692-50180-1
ISSN: 2153-5965
Conference Session: Instrumentation Division Technical Session 4
Tagged Division: Instrumentation
Page Count: 16
Page Numbers: 26.467.1 - 26.467.16
DOI: 10.18260/p.23805
Permanent URL: https://peer.asee.org/23805
Download Count: 451

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Paper Authors

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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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Abstract

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.

Citation
Format

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

TY  - CPAPER
AB  -                 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. 
AU  - Mark Jeffrey ZurSchmiede
AU  - Jeffrey Ward
CY  - Seattle, Washington
DA  - 2015/06/14
PB  - ASEE Conferences
TI  - Design of a Modular Cloud Storage Gaging System for  Automotive Manufacturing
UR  - https://peer.asee.org/23805
DO  - 10.18260/p.23805
ER  -