Statistical control and design optimization in slitting process

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.

Bibliographic Details
Main Author: Tanuwijaya, Willy Perdana
Other Authors: David E. Hardt.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2011
Subjects:
Online Access:http://hdl.handle.net/1721.1/62512
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author Tanuwijaya, Willy Perdana
author2 David E. Hardt.
author_facet David E. Hardt.
Tanuwijaya, Willy Perdana
author_sort Tanuwijaya, Willy Perdana
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description Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.
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spelling mit-1721.1/625122019-04-10T18:33:29Z Statistical control and design optimization in slitting process Optimization and robustness of slitting process Tanuwijaya, Willy Perdana David E. Hardt. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Mechanical Engineering. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 75). The incorrect slitting is the defect waste in slitting process which does not meet the single pack width and crease-to-edge width requirements. It is the highest contributor to the overall defect waste in slitting process at Company X Jurong (CXJ). To address this problem, the key input and output variables were identified. The inputs are the tension settings and knives' positioning, and the output is crease-to-edge width. The objectives are to optimize the tension settings and to achieve a centered process by a proper calibration of knives' positioning. The Design of Experiments (DoE) was conducted to study the significance of tension towards crease-to-edge width variance. For 200 mL pack size, it was found that the variance is constant within the allowable setting range. For 250 mL pack size, it was found that the overall average variance best represents the variance of the data within the allowable range. However, the process is currently off-centered. Therefore, a proper training for detecting any mean shift happening in the process to the operators utilizing the digital camera measurement system is recommended. by Willy Perdana Tanuwijaya. M.Eng. 2011-04-25T16:11:24Z 2011-04-25T16:11:24Z 2010 2010 Thesis http://hdl.handle.net/1721.1/62512 712602441 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 75 p. application/pdf Massachusetts Institute of Technology
spellingShingle Mechanical Engineering.
Tanuwijaya, Willy Perdana
Statistical control and design optimization in slitting process
title Statistical control and design optimization in slitting process
title_full Statistical control and design optimization in slitting process
title_fullStr Statistical control and design optimization in slitting process
title_full_unstemmed Statistical control and design optimization in slitting process
title_short Statistical control and design optimization in slitting process
title_sort statistical control and design optimization in slitting process
topic Mechanical Engineering.
url http://hdl.handle.net/1721.1/62512
work_keys_str_mv AT tanuwijayawillyperdana statisticalcontrolanddesignoptimizationinslittingprocess
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