1st Edition

Stream of Variation Modeling and Analysis for Multistage Manufacturing Processes

By Jianjun Shi Copyright 2007
    496 Pages 120 B/W Illustrations
    by CRC Press

    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.

    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

    Biography

    Jianjun Shi

    The author is one of the leading researchers engaged in addressing this issue … an excellent source for applied statisticians and engineers alike who are interested in the applications of multivariate statistical models. The treatment of the subject matter makes it not only a useful reference for researchers and practitioners in this field (quality monitoring and applied statistics), but also an excellent textbook for a graduate level advanced quality course … a useful resource for industrial practitioners … an excellent collection of materials for researchers, practitioners, and educators interested in advanced quality monitoring through the application of multivariate statistics and linear systems principles, and this book can be used as part of a graduate level advanced quality course.

    —Satish T.S. Bukkapatnam, Oklahoma State University, Technometrics, Vol. 51 No. 4, Nov. 2009