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 Processes.
The unified methodology outlined in this book addresses all aspects of variation reduction in a MMP, which consists of state space modeling, design analysis and synthesis, engineering-driven statistical methods for process monitoring and root-cause diagnosis, and quick failure recovery and defect prevention. Coverage falls into five sections, beginning with a review of matrix theory and multivariate statistics followed by variation propagation modeling with applications in assembly and machining processes. The third section focuses on diagnosing the sources of variation while the fourth section explains design methods to reduce variability. The final section assembles advanced SoV-related topics and the integration of quality and reliability.
Introducing a powerful and industry-proven method, this book fuses statistical knowledge with the engineering knowledge of product quality and unifies the design of processes and products to achieve more predictable and reliable manufacturing processes.
Table of Contents
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
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
"The book can be used as a major reference or text book for researchers, engineers, and students who are interested in manufacturing design and analysis. This book can also be used as a text book for senior undergraduate students or graduate students in advanced quality control courses or manufacturing design courses."
– Anatoliy Swishchuk, in Zentralblatt MATH, 2008