Concurrent design for optimal quality and cycle time

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001.

Bibliographic Details
Main Author: Wei, Yu-Feng, 1970-
Other Authors: Anna C. Thornton.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2005
Subjects:
Online Access:http://hdl.handle.net/1721.1/8859
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author Wei, Yu-Feng, 1970-
author2 Anna C. Thornton.
author_facet Anna C. Thornton.
Wei, Yu-Feng, 1970-
author_sort Wei, Yu-Feng, 1970-
collection MIT
description Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001.
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spelling mit-1721.1/88592019-04-12T13:59:52Z Concurrent design for optimal quality and cycle time Wei, Yu-Feng, 1970- Anna C. Thornton. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Massachusetts Institute of Technology. Dept. of Mechanical Engineering. Mechanical Engineering. Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001. Includes bibliographical references (p. 113-116). Product and manufacturing system design are the core issues in product development and dominate the profitability of a company. In order to assess and optimize the product and manufacturing system design, an objective evaluation framework is needed. Despite the many existing tools for product and manufacturing system design, there is a missing link between the product design and the production performances under system variability. The goal of the thesis is to explore and understand the interactions among part design and tolerancing, processes and system variability, and system control decision, then provide an integrated model to assess the total cost in a system. This model will be used to aid part design, tolerancing, batching, as well as strategy analysis in process improvement. A two-stage modeling approach is used to tackle the problem: quality prediction and production prediction. The quality prediction model projects the process variations into the output quality variations at each manufacturing stage, then predict the yield rate from the stochastic behavior of the variations and the tolerance. The production prediction model projects the demand rate and variability, processing times and variability, yield rates and batch-sizes into the manufacturing cycle time and inventories. After the performances are predicted through the previous two models, concurrent optimization of part design, tolerance, and batch-sizes are achieved by varying them to find the minimum cost. A case study at Boeing Tube shop is used to illustrate this approach. The result shows that the costless decisions in part design, tolerancing, and batch- sizes can significantly improve the system performance. In addition, conducting them separately or without using the system performance as the evaluation criteria may only lead to the local optima. by Yu-Feng Wei. Ph.D. 2005-08-23T15:53:54Z 2005-08-23T15:53:54Z 2001 2001 Thesis http://hdl.handle.net/1721.1/8859 48747365 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 116 p. 9669729 bytes 9669488 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology
spellingShingle Mechanical Engineering.
Wei, Yu-Feng, 1970-
Concurrent design for optimal quality and cycle time
title Concurrent design for optimal quality and cycle time
title_full Concurrent design for optimal quality and cycle time
title_fullStr Concurrent design for optimal quality and cycle time
title_full_unstemmed Concurrent design for optimal quality and cycle time
title_short Concurrent design for optimal quality and cycle time
title_sort concurrent design for optimal quality and cycle time
topic Mechanical Engineering.
url http://hdl.handle.net/1721.1/8859
work_keys_str_mv AT weiyufeng1970 concurrentdesignforoptimalqualityandcycletime