2.830J Control of Manufacturing Processes (SMA 6303), Spring 2004

The objective of this subject is to understand the nature of manufacturing process variation and the methods for its control. First, a general process model for control is developed to understand the limitations a specific process places on the type of control used. A general model for process varia...

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Main Author: Hardt, D. E. (David E.)
Language:en-US
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/1721.1/56569
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author Hardt, D. E. (David E.)
author_facet Hardt, D. E. (David E.)
author_sort Hardt, D. E. (David E.)
collection MIT
description The objective of this subject is to understand the nature of manufacturing process variation and the methods for its control. First, a general process model for control is developed to understand the limitations a specific process places on the type of control used. A general model for process variation is presented and three methods are developed to minimize variations: Statistical Process Control, Process Optimization and in-process Feedback Control. These are considered in a hierarchy of cost-performance tradeoffs, where performance is based on changes in process capability. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 6306 (Manufacturing Physics III: Process Optimisation and Control).
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spelling mit-1721.1/565692019-09-12T16:47:22Z 2.830J Control of Manufacturing Processes (SMA 6303), Spring 2004 Control of Manufacturing Processes (SMA 6303) Hardt, D. E. (David E.) Process control manufacturing process discrete system feedback control theory empirical and adaptive modeling off-line optimization statistical process control real-time control 2.830J 2.830 141901 Mechanical Engineering The objective of this subject is to understand the nature of manufacturing process variation and the methods for its control. First, a general process model for control is developed to understand the limitations a specific process places on the type of control used. A general model for process variation is presented and three methods are developed to minimize variations: Statistical Process Control, Process Optimization and in-process Feedback Control. These are considered in a hierarchy of cost-performance tradeoffs, where performance is based on changes in process capability. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 6306 (Manufacturing Physics III: Process Optimisation and Control). 2010-07-15T17:23:28Z 2010-07-15T17:23:28Z 2004-06 2010-07-15T17:23:28Z 2.830J-Spring2004 2.830J IMSCP-MD5-60162a7346db42b8494dd99088e21f74 http://hdl.handle.net/1721.1/56569 en-US http://www.core.org.cn/OcwWeb/Mechanical-Engineering/2-830JSpring2004/CourseHome/index.htm This site (c) Massachusetts Institute of Technology 2003. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license"). The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions. text/html Spring 2004
spellingShingle Process control
manufacturing process
discrete system feedback control theory
empirical and adaptive modeling
off-line optimization
statistical process control
real-time control
2.830J
2.830
141901
Mechanical Engineering
Hardt, D. E. (David E.)
2.830J Control of Manufacturing Processes (SMA 6303), Spring 2004
title 2.830J Control of Manufacturing Processes (SMA 6303), Spring 2004
title_full 2.830J Control of Manufacturing Processes (SMA 6303), Spring 2004
title_fullStr 2.830J Control of Manufacturing Processes (SMA 6303), Spring 2004
title_full_unstemmed 2.830J Control of Manufacturing Processes (SMA 6303), Spring 2004
title_short 2.830J Control of Manufacturing Processes (SMA 6303), Spring 2004
title_sort 2 830j control of manufacturing processes sma 6303 spring 2004
topic Process control
manufacturing process
discrete system feedback control theory
empirical and adaptive modeling
off-line optimization
statistical process control
real-time control
2.830J
2.830
141901
Mechanical Engineering
url http://hdl.handle.net/1721.1/56569
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