Statistical process control Research


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Personnel

Timothy M. (Tim) Young
Professor
Process analytics

Groups and Facilities


(1 mention)

Manufacturing Excellence 
Assisting industries, with a focus on statistical process control, lean manufacturing, and real-time process modeling.


   

Recent Publications

Statistical process control as a method for improvement for the treated wood industries.  Young, T. M., P. Lebow, S. Lebow, and A. M. Taylor.  2020.  Forest Products Journal.

Accurately estimating and improving costs for the cellulosic biomass supply chain with Statistical Process Control and the Taguchi Loss Function Metzner C., M. Platzer, T. M. Young, B. Bichescu, et al.  2019.  BioResources, BioResources. 14(2): 2961-2976. [Abstract]

Detecting special-cause variation ‘events’ from process data signatures using control bands Young, T. M., O. Khaliukova, N. O. Andre, A. Petutschnigg, and T. G. Rials.  2019.  Journal of Applied Statistics, 46(16):3032-3043. [Abstract]

A protocol for implementing statistical process control in the treated wood industry.  Young, T. M., P. K. Lebow, G. Kirker, and A. M. Taylor.  2019.  American Wood Protection Association proceedings.

SPC Handbook for the Treated Wood Industries.  Young, T. M., P. K. Lebow, S. Lebow, and A. M. Taylor.  2019.  UTIA AgResearch Publication. [Abstract]

Strategies for continuous improvement and improved competitiveness for the sustainable bio-based industries.  Metzner C.  2018.  M.S. Thesis. [Abstract]

A protocol for implementing statistical process control in the treated wood industry.  Young, T. M., P. K. Lebow, G. Kirker, and A. M. Taylor.  2018.  Seattle WA, Proceedings 104th Annual Meeting of the American Wood Protection Association.

Statistical process control for residential wood.  Young, T. M., P. K. Lebow, and S. Lebow.  2017.  American Wood Protection Association (AWPA) Conference, Vol. 113: 234-244 Birmingham, AL.

Reducing variation, the role of statistical process control in advancing product quality.  Young, T. M.  2008.  Engineered Wood Association. 11(2):41-42.

Continuous Improvement using statistical process control in the forest products industry .  Young, T. M.  2008.  Fifth Edition. The University of Tennessee, Knoxville. 321p. Precursor for a potential textbook.

Applications of real-time statistical process control and other statistical methods for improved lumber drying quality.  Young, T. M., and B. H. Bond.  2008.  Proc. Quality Drying for the 21st Century: Energy and Market Realities, Bellingham, WA. November 15-17, 2006. Forest Products Society. Madison, WI. p. 123-130.

Real-Time Statistical Process Control and Components of Variance Systems for Reducing Lumber Thickness Variation in Hardwood Sawmills Young, T. M., and A.M. Taylor.  2007.  International Scientific Conference on Hardwood Processing, September 24–25–26, 2007 Quebec City, Canada. Pages 171-180. Proceedings available on-line at.