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

Author(s)
Hardt, D. E. (David E.)
Thumbnail
Download2-830JSpring2004/OcwWeb/Mechanical-Engineering/2-830JSpring2004/CourseHome/index.htm (14.68Kb)
Alternative title
Control of Manufacturing Processes (SMA 6303)
Terms of use
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.
Metadata
Show full item record
Abstract
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).
Date issued
2004-06
URI
http://hdl.handle.net/1721.1/56569
Other identifiers
2.830J-Spring2004
Other identifiers
2.830J
IMSCP-MD5-60162a7346db42b8494dd99088e21f74
Keywords
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
Collections

The following license files are associated with this item: