Modelling robustness for manufacturing processes: a critical review

References

• Abbasi, B., S. Shadrokh, and J. Arkat. 2006. “Bi-objective Resource-constrained Project Scheduling with Robustness and Makespan Criteria.” Applied Mathematics and Computation 180: 146–152.
   Web of Science ®Google Scholar
• Abellan-Nebot, J. V., J. Liu, and F. R. Subiron. 2011. “Design of Multi-station Manufacturing Processes by Integrating the Stream-of-variation Model and Shop-floor Data.” Journal of Manufacturing Systems 30: 70–82.
   Web of Science ®Google Scholar
• Agrawal, R., J. F. Lawless, and R. J. Mackay. 1999. “Analysis of Variation Transmission in Manufacturing Processes-part II.” Journal of Quality Technology 31(2): 143–154.
   Web of Science ®Google Scholar
• Ali, S., A. A. Maciejewski, H. J. Siegel, and J.-K. Kim. 2003. “Definition of a Robustness Metric for Resource Allocation.” Proceedings of the International Parallel and Distributed Processing symposium, IEE, Computer Society: 1–10.
   Google Scholar
• Aomar, R. A. 2006. “Incorporating Robustness into Genetic Algorithm Search of Stochastic Simulation Outputs.” Simulation Modeling Practice and Theory 14(3): 201–223.
   Web of Science ®Google Scholar
• Archimede, B., P. Charbonnaud, and N. Mercier. 2003. “Robustness Evaluation of Multisite Distributed Schedule with Perturbed Virtual Jobshops.” Production Planning & Control 14(1): 55–67.
   Web of Science ®Google Scholar
• Baker, J. W., M. S. Schubert, and M. H. Faber. 2008. “On the Assessment of Robustness.” Structural Safety 30(3): 253–267.
   Web of Science ®Google Scholar
• Beyer, H.-G., and B. Sendhoff. 2007. “Robust Optimization – A Comprehensive Survey.” Computer Methods in Applied Mechanics and Engineering 196: 3190–3218.
   Web of Science ®Google Scholar
• Boer, J. H. D., A. K. Smilde, and D. A. Doornbos. 1990. “Introduction of a Robustness Coefficient in Optimization Procedure: Implementation in Mixture Design Problems Part1: Theory.” Chemometrics and Intelligent Laboratory Systems 7: 223–236.
   Web of Science ®Google Scholar
• Borkowski, J. J., and J. M. Lucas. 1997. “Designs of Mixed Resolution for Process Robustness Studies.” Technometrics 39(1): 63–70.
   Web of Science ®Google Scholar
• Box, G. E. P., and R. D. Meyer. 1986. “Dispersion Effects from Fractional Designs.” Technometrics 28(1): 19–28.
   Web of Science ®Google Scholar
• Boyles, R. A. 1991. “The Taguchi Capability Indices.” Journal of Quality Technology 23: 17.
   Web of Science ®Google Scholar
• Caro, S., F. Bennis, and P. Wenger. 2005. “Tolerance Synthesis of Mechanisms: A Robust Design Approach.” Transactions of the ASME 127: 86–94.
   Web of Science ®Google Scholar
• Ceglarek, D., and J. Shi. 1998. “Variation Design Evaluation of Sheet Metal Joints for Dimensional Integrity.” ASME Journal of Manufacturing Science Engineering 120: 452–460.
   Web of Science ®Google Scholar
• Chalupnik, M. J., D. C. Wynn, C. M. Eckert, and P. J. Clarkson. 2007. “Understanding Design Process Robustness: A Modeling Approach.” International Conference on Engineering Design, ICED’ 07, Paris.
   Google Scholar
• Chan, K. Y., T. S. Dillon, and C. K. Kwong. 2012. “Handling Uncertainties in Modeling Manufacturing Processes with Hybrid Swarm Intelligence.” International Journal of Production Research 50(6): 1714–1725.
   Web of Science ®Google Scholar
• Chen, L. H., and Y. H. Chen. 1996. “A Design Procedure for a Robust Job Shop Manufacturing System under Constraint Using Computer Simulation Experiments.” Computers and Industrial Engineering 30(1): 1–12.
   Web of Science ®Google Scholar
• Chen, J.-M., and J.-C. Tsou. 2003. “An Optimal Design for Process Quality Improvement: Modeling and Application.” Production Planning & Control 14(7): 603–612.
   Web of Science ®Google Scholar
• Cheng, H., Y. Li, K.-F. Zhang, W.-Q. Mu, and B.-F. Liu. 2011. “Variation Modeling of Aeronautical Thin-Walled Structures with Multi-State Riveting.” Journal of Manufacturing Systems 30: 101–115.
   Web of Science ®Google Scholar
• de Souza, T., and B. Rolfe. 2008. “Multivariate Modelling of Variability in Sheet Metal Forming.” Journal of Materials Processing Ttechnology 203(1–3): 1–12.
   Web of Science ®Google Scholar
• Dejaegher, B., J. Smeyers-Verbeke, and Y. Vander Heyden. 2005. “The Variance of Screening and Supersaturated Design Results as a Measure for Method Robustness.” Analytica Chimica Acta 544: 268–279.
   Web of Science ®Google Scholar
• Dessai, S., and M. Hulme. 2007. “Assessing the Robustness of Adaptation Decisions to Climate Change Uncertainties: A Case Study on Water Resources Management in the East of England.” Global Environmental Change 17: 59–72.
   Web of Science ®Google Scholar
• Ding, Y., D. Ceglarek, and J. Shi. 2002. “Design Evaluation of Multi-station Assembly Processes by Using State Space Approach.” Journal of Mechanical Design 124: 408–418.
   Web of Science ®Google Scholar
• Dou, X., and W. Wang. 2010. “Robust Control of Multistage Printing Systems.” Control Engineering Practice 18: 219–229.
   Web of Science ®Google Scholar
• Du, X., P. K. Venigella, and D. Liu. 2009. “Robust Mechanism Synthesis with Random and Interval Variables.” Mechanism and Machine Theory 44(7): 1321–1337.
   Web of Science ®Google Scholar
• Egmont-Petersen, M., J. L. Talmon, and A. Hasman. 1997. “Robustness Metrics for Measuring the Influence of Additive Noise on the Performance of Statistical Classifiers.” International Journal of Medical Informatics 46: 103–112.
   PubMed Web of Science ®Google Scholar
• Engel, J. 1992. “Modelling Variation in Industrial Experiments.” Applied Statistics 41: 579–593.
   Web of Science ®Google Scholar
• English, J. R., and G. D. Taylor. 1993. “Process Capability Analysis: A Robustness Study.” International Journal of Production Research 31(7): 1621–1635.
   Web of Science ®Google Scholar
• Etienne, E. C. 2009. “The Analysis and Evaluation of a Quality System Using the Six Sigma Benchmark: Evidence for the Robustness of Six Sigma Processes.” International Journal of Productivity and Quality Management 4(2): 178–198.
   Google Scholar
• Falamaki, C., and J. Veysizadeh. 2008. “Taguchi Design of Experiments Approach to the Manufacture of One-step Alumina Microfilter/Membrane Supports by the Centrifugal Casting Technique.” Ceramics International 34: 1653–1659.
   Web of Science ®Google Scholar
• Fong, D. Y. T., and J. F. Lawless. 1998. “The Analysis of Process Variation Transmission with Multivariate Measurements.” Statistica Sinica 8: 151–164.
   Web of Science ®Google Scholar
• Frederickson, G. N., and R. Solis-Oba. 2006. “Efficient Algorithms for Robustness in Resource Allocation and Scheduling Problems.” Theoretical Computer Science 352: 250–265.
   Web of Science ®Google Scholar
• Frey, D. D., K. N. Otto, and J. A. Wysocki. 2000. “Evaluating Process Capability During the Design of Manufacturing Systems.” Journal of Manufacturing Science and Engineering 122: 513–519.
   Web of Science ®Google Scholar
• Genin, P., S. Lamouri, and A. Thomas. 2008. “Multi-facilities Tactical Planning Robustness with Experimental Design.” Production Planning & Control 19(2): 171–182.
   Web of Science ®Google Scholar
• Ghanmi, S., M.-F. Bouazizi, and N. Bouhaddi. 2007. “Robustness of Mechanical Systems against Uncertainties.” Finite Elements in Analysis and Design 43: 715–731.
   Web of Science ®Google Scholar
• Giloni, A., S. Seshadri, and J. S. Simonoff. 2006. “Robust Analysis of Variance: Process Design and Quality Improvement.” International Journal of Productivity and Quality Management 1(3): 306–319.
   Google Scholar
• Hendriks, M. W. B., J. H. Boer, and A. K. Smilde. 1996. Robustness of Analytical Chemical Methods and Pharmaceutical Technological Products. Amsterdam: Elsevier . 157–175.
   Google Scholar
• Hsieh, K.-L., and L.-I. Tong. 2006. “Incorporating Process Capability Index and Quality Loss Function into Analyzing the Process Capability for Qualitative Data.” International Journal of Advanced Manufacturing Technology 27: 1217–1222.
   Web of Science ®Google Scholar
• Hsieh, C. C., K. P. Oh, and H. I. Oh. 1990. “A Design Technique for Minimizing Net Build Errors.” Proceedings of Winter Annual Meeting of the American Society of Mechanical Engineers. Dallas, TX: ASME . 61–69.
   Google Scholar
• Hu, S. J., R. Webbink, J. Lee, and Y. Long. 2003. “Robustness Evaluation for Compliant Assembly Systems.” Transactions of the ASME 125: 262–267.
   Web of Science ®Google Scholar
• Huang, Y.-F. 2000. “Determination of the Best Mean in the Taguchi Quality Selection Model.” Production Planning & Control 11(6): 565–571.
   Web of Science ®Google Scholar
• Huang, W., T. Phoomboplab, and D. Ceglarek. 2007. “Process Capability Surrogate Model-based Tolerance Synthesis for Multi-station Manufacturing Systems.” IIE Transactions 41: 309–322.
   Web of Science ®Google Scholar
• Jensen, M. T. 2001. “Improving Robustness and Flexibility of Tardiness and Total Flow-time Job Shops Using Robustness Measures.” Applied Soft Computing 1(1): 35–52.
   Google Scholar
• Jones, P. 1990. “Designs for Minimizing the Effect of Environmental Variables.” PhD thesis, University of Wisconsion, Madison, USA.
   Google Scholar
• Jung, D., and B. Lee. 2002. “Development of a Simple and Efficient Method for Robust Optimization.” International Journal of Numerical Methods in Engineering 53(9): 2201–2215.
   Web of Science ®Google Scholar
• Kackar, R. N. and M. S. Phadke. 1981. An Introduction to Off-line and On-line Quality Control Methods. Technical Memorandum. Holmdel, NJ: AT & T Bell Laboratories.
   Google Scholar
• Kacker, R. 1985. “Offline Quality Control, Parameter Design and the Taguchi Method.” Journal of Quality Technology 17(4): 176–188.
   Web of Science ®Google Scholar
• Kane, V. E. 1986. “Process Capability Indices.” Journal of Quality Technology 18(1): 41–52.
   Web of Science ®Google Scholar
• Kathiravan, N., S. R. Devadasan, B. Michael, and S. K. Goyal. 2008. “Total Quality Function Deployment in a Rubber Processing Company: A Sample Application Study.” Production Planning & Control 19(1): 53–66.
   Web of Science ®Google Scholar
• Kazmer, D., and C. Roser. 1999. “Evaluation of Product and Process Design Robustness.” Research in Engineering Design 11: 20–30.
   Web of Science ®Google Scholar
• Kim, P., and Y. Ding. 2004. “Optimal Design of Fixture Layout in Multistation Assembly Processes.” IEEE Transactions on Automation Science and Engineering 1(2): 133–145.
   Web of Science ®Google Scholar
• Kim, D.-H., and K.-J. Kim. 2009. “Robustness Indices and Robust Prioritization in QFD.” Expert Systems with Applications 36: 2651–2658.
   Web of Science ®Google Scholar
• Koc, M., A. Agcayazi, and J. Carsley. 2011. “An Experimental Study on Robustness and Process Capability of the Warm Hydroforming Process.” Journal of Manufacturing Science and Engineering 133: 1–13.
   Web of Science ®Google Scholar
• Kuperman, A. 2011. “Testing Motion controllers’ Robustness by Emulating Electrical and Mechanical Parameter Variations of Motor Drives.” Simulation Modeling Practice and Theory 19: 1783–1794.
   Web of Science ®Google Scholar
• Lawless, J. F., R. J. Mackay, and J. A. Robinson. 1999. “Analysis of Variation Transmission in Manufacturing Processes-part I.” Journal of Quality Technology 31(2): 131–142.
   Web of Science ®Google Scholar
• Lee, Y., and J. A. Nelder. 2003. “Robust Design via Generalized Linear Models.” Journal of Quality Technology 35: 2–12.
   Web of Science ®Google Scholar
• Leung, S. C. H., and Y. Wu. 2004. “A Robust Optimization Model for Stochastic Aggregate Production Planning.” Production Planning & Control 15(5): 502–514.
   Web of Science ®Google Scholar
• Li, Z., and S. Zhou. 2006. “Robust Method of Multiple Variation Sources Identification in Manufacturing Processes for Quality Improvement.” Transactions of the ASME 128: 326–336.
   Web of Science ®Google Scholar
• Li, J., C. Zhang, R. Liang, and B. Wang. 2008. “Robust Design of Composites Manufacturing Processes with Process Simulation and Optimization Methods.” International Journal of Production Research 46(8): 2087–2104.
   Web of Science ®Google Scholar
• Lin, J. L., and C. L. Lin. 2002. “The Use of the Orthogonal Array with Grey Relational Analysis to Optimize the Electrical Discharge Machining Process with Multiple Performance Characteristics.” International Journal of Machine Tools and Manufacture 42: 237–244.
   Web of Science ®Google Scholar
• Loose, J.-P., N. Chen, and S. Zhou. 2009. “Surrogate Modeling of Dimensional Variation Propagation in Multistage Assembly Processes.” IIE Transactions 41: 893–904.
   Web of Science ®Google Scholar
• Lucas, J. M. 1994. “How to Achieve a Robust Process Using Response Surface Methodology.” Journal of Quality Technology 25: 248–260.
   Web of Science ®Google Scholar
• Madu, I. E., and C. N. Madu. 1999. “Design Optimization Using Signal-to-noise Ratio.” Simulation Practice and Theory 7: 349–372.
   Google Scholar
• Mayer, R. J., and P. C. Benjamin. 1992. “Using the Taguchi Paradigm for Manufacturing System Design Using Simulation Experiments.” Computers & Industrial Engineering 22(2): 195–209.
   Web of Science ®Google Scholar
• McCullagh, P., and J. A. Nelder. 1989. Generalized Linear Models. 2nd ed. London: Chapman and Hall.
   Google Scholar
• Mondal, S. C., J. Maiti, and P. K. Ray. 2010. “Development of a Measurement Metric for Manufacturing Process Robustness.” International Journal of Productivity and Quality Management 6: 156–181.
   Google Scholar
• Montgomery, D. C. 1995. Design and Analysis of Experiments. 5th ed. New York: John Wiley & Sons.
   Google Scholar
• Mouton, S., Y. Ledoux, D. Teissandier, and P. Sebastian. 2010. “Composite Part Design Based on Numerical Simulation of the Manufacturing Process.” International Journal of Advanced Manufacturing Technology. published online.
   Google Scholar
• Mukherjee, I., and P. K. Ray. 2006. “A Review of Optimization Techniques in Metal Cutting Processes.” Computers & Industrial Engineering 50: 15–34.
   Web of Science ®Google Scholar
• Myers, R. H., and D. C. Montgomery. 1997. “A Tutorial on Generalized Linear Models.” Journal of Quality Technology 29: 274–291.
   Web of Science ®Google Scholar
• Myers, R. H., and D. C. Montgomery. 2002. Response Surface Methodology: Process and Product Optimization Using Designed Experiments. New York: John Wiley.
   Google Scholar
• Myers, R. H., A. I. Khuri, and G. G. Vining. 1992. “Response Surface Alternatives to the Taguchi Robust Parameter Design Approach.” The American Statiscian 46: 131–139.
   Web of Science ®Google Scholar
• Myers, R., Y. Kim, and K. Griffiths. 1997. “Response Surface Methods and the Use of Noise Variables.” Journal of Quality Technology 29: 429–440.
   Web of Science ®Google Scholar
• Myers, W. R., W. A. Brenneman, and R. H. Myers. 2005. “A Dual-response Approach to Robust Parameter Design for a Generalized Linear Model.” Journal of Quality Technology 37: 130–138.
   Web of Science ®Google Scholar
• Nair, A., and J. M. Vidal. 2011. “Supply Network Topology and Robustness against Disruptions – An Investigation Using Multi-Agent Model.” International Journal of Production Research 49(5): 1391–1404.
   Web of Science ®Google Scholar
• Nelder, J. A., and Y. Lee. 1991. “Generalized Linear Models for the Analysis of Taguchi-type Experiments.” Applied Stochastic Models and Data Analysis 7: 107–120.
   Google Scholar
• Phadke, S. M. 1989. Quality Engineering Using Robust Design. Englewood Cliffs, NJ: Prentice Hall.
   Google Scholar
• Ramadan, H. S., H. Siguerdidjane, M. Petit, and R. Kaczmarek. 2012. “Performance Enhancement and Robustness Assessment of VSC-HVDC Transmission Systems Controllers Under Uncertainties.” Electrical Power and Energy Systems 35: 34–46.
   Web of Science ®Google Scholar
• Ramakrishnan, R., and L. Karunamoorthy. 2006. “Multi Response Optimization of Wire EDM Operations Using Robust Design of Experiments.” International Journal of Advanced Manufacturing Technology 29: 105–112.
   Web of Science ®Google Scholar
• Robinson, T. J., C. M. Borror, and R. H. Myers. 2004. “Robust Parameter Design: A Review.” Quality and Reliability Engineering International 20: 81–101.
   Web of Science ®Google Scholar
• Robinson, T. J., S. S. Wulff, D. C. Montgomery, and A. I. Khuri. 2006. “Robust Parameter Design Using Generalized Linear Mixed Model.” Journal of Quality Technology 38(1): 65–75.
   Web of Science ®Google Scholar
• Rodriguez, L. C., R. B. Garcia, A. M. G. Campana, and J. M. Bosque Sendra. 1998. “A New Approach to a Complete Robustness Test of Experimental Nominal Conditions of Chemical Testing Procedures for Internal Analytical Quality Assessment.” Chemometrics and Intelligent Laboratory System 41: 57–68.
   Web of Science ®Google Scholar
• Rong, Q., D. Ceglarek, and J. Shi. 2000. “Dimensional Fault Diagnosis for Compliant Beam Structure Assemblies.” Journal of Manufacturing Science and Engineering 122: 773–780.
   Web of Science ®Google Scholar
• Ross, P. J. 1996. Taguchi Techniques for Quality Engineering. 2nd ed. New York: McGraw-Hill.
   Google Scholar
• Rossi, A. 2010. “A Robustness Measure of the Configuration of Multi-purpose Machines.” International Journal of Production Research 18(4): 1013–1033.
   Web of Science ®Google Scholar
• Sabuncuoglu, I., and S. Goren. 2009. “Hedging Production Schedules Against Uncertainty in Manufacturing Environment with a Review of Robustness and Stability Research.” International Journal of Computer Integrated Manufacturing 22(2): 138–157.
   Web of Science ®Google Scholar
• Santa-Eulalia, L. A., D. Ait-Kadi, S. D’Amours, J.-M. Frayret, and S. Lemieux. 2011. “Agent-based Experimental Investigations of the Robustness of Tactical Planning and Control Policies in a Softwood Lumber Supply Chain.” Production Planning & Control 22(8): 782–799.
   Web of Science ®Google Scholar
• Sarkar, S., S. Mitra, and B. Bhattacharyya. 2005. “Parametric Analysis and Optimization of Wire Electrical Discharge Machining of γ-Titanium Aluminide Alloy.” Journal of Material Processing Technology 159: 286–294.
   Web of Science ®Google Scholar
• Shi, J., and S. Zhou. 2009. “Quality Control and Improvement for Multistage Systems: A Survey.” IIE Transactions 41: 744–753.
   Web of Science ®Google Scholar
• Shoemaker, A., and K. Tsui. 1992. “Taguchi’s Parameter Design: A Panel Discussion.” Technometrics 34(2): 127–161 . Edited by Nair.
   Web of Science ®Google Scholar
• Shoemaker, A. C., and K. L. Tsui. 1993. “Response Model Analysis for Robust Design Experiments.” Communication in Statistics Simulation 22: 1065–1078.
   Google Scholar
• Steinberg, D. M., and D. Bursztyn. 1998. “Noise Factors, Dispersion Effects, and Robust Design.” Statistica Sinica 8: 67–85.
   Web of Science ®Google Scholar
• Suri, R., and K. Otto. 2001. “Manufacturing System Robustness Through Integrated Modeling.” Transactions of the ASME 123: 630–636.
   Web of Science ®Google Scholar
• Swierenga, H., A. P. D. Weijer, R. J. V. Wijk, and L. M. C. Buydew. 1999. “Strategy for Constructing Robust Multivariate Calibration Models.” Chemometrics and Intelligent Laboratory Systems 49: 1–17.
   Web of Science ®Google Scholar
• Taflanidis, A. A., D. C. Angelidea, and J. T. Scruggs. 2009. “Simulation Based Robust Design of Mass Dampers for Response Mitigation of Tension Leg Platforms.” Engineering Structures 31(4): 847–857.
   Web of Science ®Google Scholar
• Taguchi, G. 1986. Introduction to Quality Engineering. Dearborn, MI: Asian Productivity Organization Distributed by American Supplier Institute.
   Google Scholar
• Taguchi, G. 1987. System of Experimental Design: Engineering Methods to Optimize Quality and Minimize Cost. White Plains, NY: UNIPUB/Kraus International.
   Google Scholar
• Taguchi, G., and Y. Wu. 1980. Introduction to Off-Line Quality Control. Romulus, MI: Central Japan Quality Control Association . 48174.
   Google Scholar
• Taguchi, G., S. Chowdhury, and S. Taguchi. 2000. Robust Engineering. New York: McGraw-Hill.
   Google Scholar
• Tsui, K.-L. 1996. “A Multistep Analysis Procedure for Robust Design.” Statistica Sinica 6: 631–648.
   Web of Science ®Google Scholar
• Tuovinen, J.-P., D. Simpson, L. Emberson, M. Ashmore, and G. Gerosa. 2007. “Robustness of Modeled Ozone Exposures and Doses.” Environmental Pollution 146: 578–586.
   PubMed Web of Science ®Google Scholar
• Tveit, T.-M. 2005. “Experimental Design Methods and Flow Sheet Synthesis of Energy Systems.” Applied Thermal Engineering 25: 283–293.
   Web of Science ®Google Scholar
• Vining, G. G., and R. H. Myers. 1990. “Combining Taguchi and Response Surface Phillosophies: A Dual Response Approach.” Journal of Quality Technology 22(1): 38–45.
   Web of Science ®Google Scholar
• Vuchkov, I. N. and L. N. Boyadjieva. 1988. “First International Conference Workshop on Optimal Design and Analysis of Experiments.” The Robustness Against Tolerances of Performance Characteristics Described by Second Order Polynomials, Neuchatel, 293-309.
   Google Scholar
• Welch, W. J., S. M. Yu, and J. Sacks. 1990. “Computer Experiments for Quality Control by Parameter Design.” Journal of Quality Technology 22: 15–22.
   Web of Science ®Google Scholar
• Wortel, V. A. L., W. G. Hansen, and S. C. C. Wiedemann. 2001. “Optimising Multivariate Calibration by Robustness Criteria.” Journal of Near Infrared Spectroscopy 9: 141–151.
   Web of Science ®Google Scholar
• Wu, C. F. J., and M. Hamada. 2000. Experiments: Planning, Analysis, and Parameter Design Optimization. New York: John Wiley.
   Google Scholar
• Yang, T., Y. Kuo, and P. Chou. 2005. “Solving a Multi-response Simulation Problem Using a Dual-response System and Scatter Search Method.” Simulation Modeling Practice and Theory 13: 356–369.
   Web of Science ®Google Scholar
• Yeh, A. B. and S. K. Bhattacharya. 1998. “A Robust Process Capability Index.” Communications in Statistics – Simulation and Computation 27 (2): 565–589.
   Google Scholar
• Yuangyai, C., H. B. Nembhard, and G. Hayes. 2012. “Robust Parameter Design for Multiple-stage Nanomanufacturing.” IIE Transactions 44: 580–589.
   Web of Science ®Google Scholar
• Yue, J., J. A. Camelio, M. Chin, and W. Cai. 2007. “Product-oriented Sensitivity Analysis for Multistation Compliant Assemblies.” Transactions of the ASME 129: 844–851.
   Web of Science ®Google Scholar
• Zarkarian, A., J. W. Knight, and L. Baghdasaryan. 2007. “Modelling and Analysis of System Robustness.” Journal of Engineering Design 18(3): 243–263.
   Web of Science ®Google Scholar
• Zeaiter, M., J.-M. Roger, V. Bellon-Maurel, and D. N. Rutledge. 2004. “Robustness of Models Developed by Multivariate Calibration. Part 1: The Assessment of Robustness.” Trends in Analytical Chemistry 23(2): 157–170.
   Web of Science ®Google Scholar
• Zhang, M., D. Djurdjanovic, and J. Ni. 2007. “Diagnosibility and Sensitivity Analysis for Multi-station Machining Processes.” International Journal of Machine Tools and Manufacture 47: 646–657.
   Web of Science ®Google Scholar
• Zhang, L., J. Ni, and X. Lai. 2008. “Dimensional Errors of Rollers in the Stream of Variation Modeling in Cold Roll Forming Process of Quadrate Steel Tube.” International Journal of Advanced Manufacturing Technology 37: 1082–1092.
   Web of Science ®Google Scholar
• Zhou, S., Q. Huang, and J. Shi. 2003. “State Space Modeling of Dimensional Variation Propagation in Multistage Machining Process Using Differential Motion Vectors.” IEEE Transactions on Robotics and Automation 19(2): 296–309.
   Google Scholar
• Zhu, J., and K.-L. Ting. 2001. “Performance Distribution Analysis and Robust Design.” Journal of Mechanical Design 123(1): 11–17.
   Web of Science ®Google Scholar
• Zhu, Y., J. You, R. Alard, and P. Schonsleben. 2009. “Design Quality: A Key to Improve Quality in International Production Network.” Production Planning & Control 20(2): 168–177.
   Web of Science ®Google Scholar