Professor Joseph Voelkel received his B.S. in Mathematics from Rensselaer Polytechnic Insittute, his M.S. in Industrial Engineering/Management Sciences from Northwestern University, and his Ph.D. in Statistics from the Univeristy of Wisconsin-Madison. He has taught courses in experimental design, regression analysis, reliability statistics, statistical computing, theory of statistics, multivariate analysis, statistical process control, and capstone.
His research interests are oriented toward statistical methodology in the engineering and physical sciences, especially in experimental design and statistical process control.
His consulting and training through RIT have included a wide range of clients, including those in the films, optics, electronics, resin, plastics, automotive, laser, and bearing industries. The list includes Bausch & Lomb, Borden, DuPont, General Motors, ITT, Mobil, Motorola, Tenneco, and Xerox. His focus on continual process improvement includes explaining fundamental statistical methods, mentoring Six-Sigma-project teams, teaching advanced statistical techniques, and developing novel statistical methods to solve client-specific problems.
He is a Fellow of the American Society for Quality, and a member of the American Statistical Association and the Institute of Mathematical Statistics. He also serves on the editorial board of Quality Engineering. He has been actively involved in the Statistics Division of the American Society for Quality, and in the Quality and Productivity Section of the American Statistical Association.
Voelkel, J. G. (2007), Fractional Factorial Designs, in Encyclopedia of Statistics in Quality and Reliability, Ruggeri, F. Kenett, R. and Faltin, F. W. (eds), John Wiley & Sons Ltd, Chichester, UK, 695–704.
Voelkel, J. G. (2005), The Efficiencies of Fractional Factorial Designs, Technometrics, 47, 488–494.
Voelkel. J.G. (2003), Gauge R&R Analysis for Two-Dimensional Data with Circular Tolerances. Journal of Quality Technology, 35, 153–167.
Huang, P., Chen, D., and Voelkel, J. O. (1998), Minimum Aberration Split-Plot Designs, Technometrics, 40, 314–326.
PARTIAL CLIENT LIST
|Bausch & Lomb, Contact Lens Division||General Motors|
|Avery Dennison||Goulds Pumps, ITT|
|Bausch & Lomb, Personal Products Division||IBM|
|Borden Corporation, R&D||Labelon Corporation|
|Carleton Technologies||Laboratory for Laser Energetics, University of Rochester|
|CellTech||Latex Foam International|
|DuPont Dow Elastomers L.L.C.||Motorola, Automotive and Industrial Electronics Group|
|DuPont, Imaging Systems||Tenneco Packaging|
|Eastman Kodak Company||The Torrington Company|
|ExxonMobil Corporation, Films Division||Xerox Corporation|
All seminars can either be taught as is, or customized with corporate examples and/or supplemental material.
Design and Analysis of Engineering and Scientific Experiments. Offered twice per year to the public. Also taught on a contract basis. A four-day, hands-on, course that shows how to design and analyze the important class of two-level designs. Participants leave with the confidence to run experiments using a modern software package. Numerous examples and case studies, as well as physical experiments. Participants also learn the theory behind the techniques to avoid pitfalls in their use.
Harnessing SPC and ANOVA to Improve Complex Processes. Offered twice per year to the public. Also taught on a contract basis. A four-day, hands-on, course that shows how the power of ANOVA can be used to study complex processes. Numerous examples and case studies, and an in-depth in-class study drive home key points. Examples range from simple one-way ANOVA to complex components of variance studies, and include appropriate SPC for processes such as multiple-cavity molds. Participants leave with the confidence to run experiments using a modern software package.
Response Surface Methods. Offered on a contract basis. Participants are assumed to have had a previous seminar in regression or experimental design. A two-day, hands-on course that shows how to run experiments to optimize products and processes. Surfaces and 1st and 2nd order models; designs, including central composite, Box-Behnken, 3k, and 3k–p; analysis techniques; handling multiple responses and tradoffs—the desirability-function approach.
Mixture Experiments. Offered on a contract basis. Participants are assumed to have had a previous seminar in regression or experimental design. A three-day, hands-on course that shows how to design and analyze experiments with formulations. Mixtures; constrained mixtures; simplex-lattice, simplex-centroid, extreme vertices, and D-optimal designs; ratios and slack-variable parameterizations. Taught using Design-Expert software from Stat-Ease®.
Advanced Topics in Experimental Design and Modeling. Offered on a contract basis. Participants are assumed to have academic courses in experimental design at the level of Montgomery’s text and regression at the level of Draper and Smith’s text. Topics include extended structure diagrams for design and ANOVA modeling, including split-plot and strip-plot designs as special cases; special topics in fractional-factorial designs, including exploitation of Plackett-Burman designs and analysis, and design and analysis of minimum-aberration split-plot designs; D- and related optimality criteria, including examples of non-standard uses; generalized linear models, including maximum-likelihood estimation for generalized non-linear modeling cases; and possibly other topics chosen by the participants. Examples from the participants are encouraged and will be used as possible in the seminar.