http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Stream of variation modeling and analysis for multistage manufacturing processes
1 online resource (469 pages) : illustrations
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 corrective action only after variations occur. Learn how the Stream of Variation (SoV) methodology helps reduce or even eliminate variations throughout the entire MMP in Jianjun Shi's Stream of Variation Modeling and Analysis for Multistage Manufacturing.
What Is Stream of Variation for Multistage Manufacturing Processes?; BASIS OF MATRIX THEORY AND MULTIVARIATE STATISTICS; Basics of Matrix Theory; Basics of Multivariate Statistical Analysis; Statistical Inferences in Mean Vectors and Linear Models; Principle Component Analysis and Factor Analysis; VARIATION PROPAGATION MODELING IN MMP; State Space Modeling for Assembly Processes; State Space Modeling for Machining Processes; Factor Analysis Method for Variability Modeling; VARIATION SOURCE DIAGNOSIS; Diagnosability Analysis for Variation Source Identification; Diagnosis through Variation Pattern Matching; Estimation-Based Diagnosis; DESIGN FOR VARIATION REDUCTION; Optimal Sensor Placement and Distribution; Design Evaluation and Process Capability Analysis; Optimal Fixture Layout Design; Process-Oriented Tolerance Synthesis; QUALITY AND RELIABILITY INTEGRATION AND ADVANCED TOPICS; Quality and Reliability Chain Modeling and Analysis; Quality-Oriented Maintenance for Multiple Interactive System Components; Additional Topics on Stream of Variation; INDEX
Includes bibliographical references and index.
Boca Raton, FL : CRC Press/Taylor & Francis, ©2007