ABSTRACT

Variability arises in multistage manufacturing processes (MMPs) from a variety of sources. Variation reduction demands data fusion from product/process design, manufacturing process data, and quality measurement. Statistical process control (SPC), with a focus on quality data alone, only tells half of the story and is a passive method, taking corre

part |2 pages

Part I. Basis of Matrix Theory and Multivariate Statistics

part |2 pages

Part II. Variation Propagation Modeling in MMP

part |2 pages

Part III. Variation Source Diagnosis

part |2 pages

Part IV. Design for Variation Reduction

chapter 12|30 pages

Optimal Sensor Placement and Distribution*

chapter 14|28 pages

Optimal Fixture Layout Design*

chapter 15|26 pages

Process-Oriented Tolerance Synthesis*

part |2 pages

Part V. Quality and Reliability Integration and Advanced Topics

chapter 18|20 pages

Additional Topics on Stream of Variation

chapter |10 pages

Index

chapter |2 pages

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