Statistical Process Control for Multistage Manufacturing and Service Operations: A Review

Manufacturing and service processes today usually involve several process stages and operations. With an emphasis on achieving satisfactory product and service quality, using statistical methods for multistage process surveillance and fault diagnosis has become a necessity. Statistical process control methods have been widely recognized as effective approaches for process monitoring and diagnosis. However, most conventional SPC methods focus on single stage monitoring without considering the multistage scenario. In this paper we attempt to offer comprehensive references and a bibliography of statistical control methods for multistage manufacturing and service operations; evaluations with respect to existing methods are also given along with suggestions for future research topics

[1]  J. A. Robinson,et al.  Analysis of Variation Transmission in Manufacturing Processes—Part I , 1999 .

[2]  Uday M. Apte,et al.  Quality Management at Kentucky Fried Chicken , 1995 .

[3]  William H. Woodall,et al.  The State of Statistical Process Control as We Proceed into the 21st Century , 2000 .

[4]  Yong Chen,et al.  Diagnosability Study of Multistage Manufacturing Processes Based on Linear Mixed-Effects Models , 2003, Technometrics.

[5]  D. Wyckoff.  New Tools for Achieving Service Quality , 1984 .

[6]  Yu Ding,et al.  A comparison of process variation estimators for in-process dimensional measurements and control , 2005 .

[7]  S. Zenios,et al.  Operations, Quality, and Profitability in the Provision of Banking Services , 1999 .

[8]  R. B. Chase,et al.  Linking the customer contact model to service quality , 1998 .

[9]  Fugee Tsung,et al.  A Change Point Approach for Phase I Analysis in Multistage Processes , 2008, Technometrics.

[10]  Randolph M. Russell,et al.  Efficiency and Productivity Measures for High Contact Services , 1998 .

[11]  Shan Li,et al.  Detecting multiple special causes from multivariate data with applications to fault detection in manufacturing , 2007 .

[12]  K. Tsui,et al.  Identification and Quantification in Multivariate Quality Control Problems , 1994 .

[13]  Kenneth L. Bernhardt,et al.  Comments on Christian Grönroos' Strategic management and marketing in the service sector , 1984 .

[14]  Douglas M. Hawkins,et al.  Regression Adjustment for Variables in Multivariate Quality Control , 1993 .

[15]  Daniel W. Apley,et al.  Autocorrelated process monitoring using triggered cuscore charts , 2002 .

[16]  Darek Ceglarek,et al.  A Knowledge-Based Diagnostic Approach for the Launch of the Auto-Body Assembly Process , 1994 .

[17]  A. Parasuraman,et al.  SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. , 1988 .

[18]  Qiang Huang,et al.  State space modeling of dimensional variation propagation in multistage machining process using differential motion vectors , 2003, IEEE Trans. Robotics Autom..

[19]  G. S. May,et al.  Sequential modeling of via formation in photosensitive dielectric materials for MCM-D applications , 1999 .

[20]  Ching-Lai Hwang,et al.  Group decision making under multiple criteria , 1987 .

[21]  Douglas C. Montgomery,et al.  Research Issues and Ideas in Statistical Process Control , 1999 .

[22]  Michèle Basseville,et al.  Detection of abrupt changes: theory and application , 1993 .

[23]  Joyce S. Mehring.  ACHIEVING MULTIPLE TIMELINESS GOALS FOR AUTO LOANS: A CASE FOR PROCESS CONTROL , 1995 .

[24]  Bart Van Looy,et al.  Dealing with productivity and quality indicators in a service environment: some field experiences , 1997 .

[25]  Ann S. Marucheck,et al.  Assessing the outcomes of quality improvement interventions , 1995 .

[26]  Robert D. Plante,et al.  A self-starting procedure for monitoring process quality in multistage manufacturing systems , 2006 .

[27]  Daniel W. Apley,et al.  Diagnostics in Disassembly Unscrewing Operations , 1998 .

[28]  Chankon Kim,et al.  Methods of Measuring Health-Care Service Quality , 2000 .

[29]  Gongxu Zhang,et al.  A new diagnosis theory with two kinds of quality , 1990 .

[30]  Tze Leung Lai.  Sequential multiple hypothesis testing and efficient fault detection-isolation in stochastic systems , 2000, IEEE Trans. Inf. Theory.

[31]  Jianjun Shi,et al.  Stream of Variation Modeling and Analysis for Multistage Manufacturing Processes , 2006 .

[32]  B. J. Mandel.  The Regression Control Chart , 1969 .

[33]  Andrew C. Palm,et al.  Some Perspectives and Challenges for Control Chart Methods , 1997 .

[34]  John B. Jensen,et al.  Improving the application of quality conformance tools in service firms , 1996 .

[35]  T. R. Bement,et al.  Taguchi techniques for quality engineering , 1995 .

[36]  Andrzej J. Strojwas,et al.  Monitoring multistage integrated circuit fabrication processes , 1996 .

[37]  Pam Armstrong,et al.  A Model For Analyzing Quality in the Service Delivery Process , 1995 .

[38]  Yong Chen,et al.  Statistical estimation and testing for variation root-cause identification of multistage manufacturing Processes , 2004, IEEE Transactions on Automation Science and Engineering.

[39]  D. Hawkins.  Multivariate quality control based on regression-adjusted variables , 1991 .

[40]  Kailash C. Kapur,et al.  Design of Multiple Cause-Selecting Charts for Multistage Processes with Model Uncertainty , 2004 .

[41]  Kwok-Leung Tsui,et al.  Effects of estimation errors on cause-selecting charts , 2005 .

[42]  Fugee Tsung,et al.  Statistical monitoring of multi-stage processes based on engineering models , 2008 .

[43]  Qiang Huang,et al.  Diagnosis of multi-operational machining processes through variation propagation analysis , 2002 .

[44]  Robert D. Plante,et al.  Process and Product Improvement in Manufacturing Systems with Correlated Stages , 2002, Manag. Sci..

[45]  C. Hwang,et al.  Group Decision Making Under Multiple Criteria: Methods and Applications , 1986 .

[46]  William H. Woodall,et al.  A review and analysis of cause-selecting control charts , 1993 .

[47]  Melvin J. Hinich,et al.  Time Series Analysis by State Space Methods , 2001 .

[48]  Lloyd S. Nelson,et al.  Control Chart for Multiple Stream Processes , 1986 .

[49]  William H. Woodall,et al.  Introduction to Statistical Quality Control, Fifth Edition , 2005 .

[50]  Yu Ding,et al.  Fault Diagnosis of Multistage Manufacturing Processes by Using State Space Approach , 2002 .

[51]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[52]  Kwok-Leung Tsui,et al.  Run-Length Performance of Regression Control Charts with Estimated Parameters , 2004 .

[53]  Darek Ceglarek,et al.  Fixture Failure Diagnosis for Autobody Assembly Using Pattern Recognition , 1996 .

[54]  A. Parasuraman,et al.  A Conceptual Model of Service Quality and Its Implications for Future Research , 1985 .

[55]  Joanne M. Sulek,et al.  Measuring performance in multi-stage service operations: An application of cause selecting control charts , 2006 .

[56]  S. Zenios,et al.  Performance of financial institutions : efficiency, innovation, regulation , 2000 .

[57]  Fred Spiring,et al.  Introduction to Statistical Quality Control , 2007, Technometrics.

[58]  Yu Ding,et al.  Diagnosability Analysis of Multi-Station Manufacturing Processes , 2002 .

[59]  George C. Runger,et al.  Designing a Multivariate EWMA Control Chart , 1997 .

[60]  Jionghua Jin,et al.  State Space Modeling of Sheet Metal Assembly for Dimensional Control , 1999 .

[61]  Douglas C. Montgomery,et al.  A review of multivariate control charts , 1995 .

[62]  Lianjie Shu,et al.  ON MULTISTAGE STATISTICAL PROCESS CONTROL , 2003 .