Design of a Modular Cloud Storage Gaging System for Automotive Manufacturing
Author(s) -
Mark ZurSchmiede,
J. Scott Ward
Publication year - 2015
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/p.23805
Subject(s) - modular design , cloud computing , software , automotive industry , fixture , computer science , construct (python library) , database , engineering , mechanical engineering , operating system , aerospace engineering , programming language
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.
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